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RawCuts_01Library "RawCuts_01" A collection of functions by: mutantdog The majority of these are used within published projects, some useful variants have been included here aswell. This is volume one consisting mainly of smaller functions, predominantly the filters and standard deviations from Weight Gain 4000. Also included at the bottom are various snippets of related code for demonstration. These can be copied and adjusted according to your needs. A full up-to-date table of contents is located at the top of the main script. WEIGHT GAIN FILTERS A collection of moving average type filters with adjustable volume weighting. Based upon the two most common methods of volume weighting. 'Simple' uses the standard method in which a basic VWMA is analogous to SMA. 'Elastic' uses exponential method found in EVWMA which is analogous to RMA. Volume weighting is applied according to an exponent multiplier of input volume. 0 >> volume^0 (unweighted), 1 >> volume^1 (fully weighted), use float values for intermediate weighting. Additional volume filter switch for smoothing of outlier events. DIVA MODULAR DEVIATIONS A small collection of standard and absolute deviations. Includes the weightgain functionality as above. Basic modular functionality for more creative uses. Optional input (ct) for external central tendency (aka: estimator). Can be assigned to alternative filter or any float value. Will default to internal filter when no ct input is received. Some other useful or related functions included at the bottom along with basic demonstration use. weightgain_sma(src, len, xVol, fVol)   Simple Moving Average (SMA): Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Standard Simple Moving Average with Simple Weight Gain applied. weightgain_hsma(src, len, xVol, fVol)   Harmonic Simple Moving Average (hSMA): Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Harmonic Simple Moving Average with Simple Weight Gain applied. weightgain_gsma(src, len, xVol, fVol)   Geometric Simple Moving Average (gSMA): Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Geometric Simple Moving Average with Simple Weight Gain applied. weightgain_wma(src, len, xVol, fVol)   Linear Weighted Moving Average (WMA): Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Basic Linear Weighted Moving Average with Simple Weight Gain applied. weightgain_hma(src, len, xVol, fVol)   Hull Moving Average (HMA): Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Basic Hull Moving Average with Simple Weight Gain applied. diva_sd_sma(src, len, xVol, fVol, ct)   Standard Deviation (SD SMA): Diva / Weight Gain (Simple Volume)   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_sma().   Returns: diva_sd_wma(src, len, xVol, fVol, ct)   Standard Deviation (SD WMA): Diva / Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_wma().   Returns: diva_aad_sma(src, len, xVol, fVol, ct)   Average Absolute Deviation (AAD SMA): Diva / Weight Gain (Simple Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_sma().   Returns: diva_aad_wma(src, len, xVol, fVol, ct)   Average Absolute Deviation (AAD WMA): Diva / Weight Gain (Simple Volume) .   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_wma().   Returns: weightgain_ema(src, len, xVol, fVol)   Exponential Moving Average (EMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Exponential Moving Average with Elastic Weight Gain applied. weightgain_dema(src, len, xVol, fVol)   Double Exponential Moving Average (DEMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Double Exponential Moving Average with Elastic Weight Gain applied. weightgain_tema(src, len, xVol, fVol)   Triple Exponential Moving Average (TEMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Triple Exponential Moving Average with Elastic Weight Gain applied. weightgain_rma(src, len, xVol, fVol)   Rolling Moving Average (RMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Rolling Moving Average with Elastic Weight Gain applied. weightgain_drma(src, len, xVol, fVol)   Double Rolling Moving Average (DRMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Double Rolling Moving Average with Elastic Weight Gain applied. weightgain_trma(src, len, xVol, fVol)   Triple Rolling Moving Average (TRMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: Triple Rolling Moving Average with Elastic Weight Gain applied. diva_sd_ema(src, len, xVol, fVol, ct)   Standard Deviation (SD EMA): Diva / Weight Gain: (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_ema().   Returns: diva_sd_rma(src, len, xVol, fVol, ct)   Standard Deviation (SD RMA): Diva / Weight Gain: (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_rma().   Returns: weightgain_vidya_rma(src, len, xVol, fVol)   VIDYA v1 RMA base (VIDYA-RMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: VIDYA v1, RMA base with Elastic Weight Gain applied. weightgain_vidya_ema(src, len, xVol, fVol)   VIDYA v1 EMA base (VIDYA-EMA): Weight Gain (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.   Returns: VIDYA v1, EMA base with Elastic Weight Gain applied. diva_sd_vidya_rma(src, len, xVol, fVol, ct)   Standard Deviation (SD VIDYA-RMA): Diva / Weight Gain: (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_vidya_rma().   Returns: diva_sd_vidya_ema(src, len, xVol, fVol, ct)   Standard Deviation (SD VIDYA-EMA): Diva / Weight Gain: (Elastic Volume).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).      fVol (bool) : Volume smoothing filter.      ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_vidya_ema().   Returns: weightgain_sema(src, len, xVol, fVol)   Parameters:      src (float)      len (simple int)      xVol (float)      fVol (bool) diva_sd_sema(src, len, xVol, fVol)   Parameters:      src (float)      len (simple int)      xVol (float)      fVol (bool) diva_mad_mm(src, len, ct)   Median Absolute Deviation (MAD MM): Diva (no volume weighting).   Parameters:      src (float) : Source input.      len (int) : Length (number of bars).      ct (float) : Central tendency (optional, na = bypass). Internal: ta.median()   Returns: source_switch(slct, aux1, aux2, aux3, aux4)   Custom Source Selector/Switch function. Features standard & custom 'weighted' sources with additional aux inputs.   Parameters:      slct (string) : Choose from custom set of string values.      aux1 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.      aux2 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.      aux3 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.      aux4 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.   Returns: Float value, to be used as src input for other functions. colour_gradient_ma_div(ma1, ma2, div, bull, bear, mid, mult)   Colour Gradient for plot fill between two moving averages etc, with seperate bull/bear and divergence strength.   Parameters:      ma1 (float) : Input for fast moving average (eg: bullish when above ma2).      ma2 (float) : Input for slow moving average (eg: bullish when below ma1).      div (float) : Input deviation/divergence value used to calculate strength of colour.      bull (color) : Colour when ma1 above ma2.      bear (color) : Colour when ma1 below ma2.      mid (color) : Neutral colour when ma1 = ma2.      mult (int) : Opacity multiplier. 100 = maximum, 0 = transparent.   Returns: Colour with transparency (according to specified inputs)
Pine Script® library
by mutantdog
EphemerisLibrary "Ephemeris" TODO: add library description here mercuryElements() mercuryRates() venusElements() venusRates() earthElements() earthRates() marsElements() marsRates() jupiterElements() jupiterRates() saturnElements() saturnRates() uranusElements() uranusRates() neptuneElements() neptuneRates() rev360(x)   Normalize degrees to within [0, 360)   Parameters:      x (float) : degrees to be normalized   Returns: Normalized degrees scaleAngle(longitude, magnitude, harmonic)   Scale angle in degrees   Parameters:      longitude (float)      magnitude (float)      harmonic (int)   Returns: Scaled angle in degrees julianCenturyInJulianDays()   Constant Julian days per century   Returns: 36525 julianEpochJ2000()   Julian date on J2000 epoch start (2000-01-01)   Returns: 2451545.0 meanObliquityForJ2000()   Mean obliquity of the ecliptic on J2000 epoch start (2000-01-01)   Returns: 23.43928 getJulianDate(Year, Month, Day, Hour, Minute)   Convert calendar date to Julian date   Parameters:      Year (int) : calendar year as integer (e.g. 2018)      Month (int) : calendar month (January = 1, December = 12)      Day (int) : calendar day of month (e.g. January valid days are 1-31)      Hour (int) : valid values 0-23      Minute (int) : valid values 0-60 julianCenturies(date, epoch_start)   Centuries since Julian Epoch 2000-01-01   Parameters:      date (float) : Julian date to conver to Julian centuries      epoch_start (float) : Julian date of epoch start (e.g. J2000 epoch = 2451545)   Returns: Julian date converted to Julian centuries julianCenturiesSinceEpochJ2000(julianDate)   Calculate Julian centuries since epoch J2000 (2000-01-01)   Parameters:      julianDate (float) : Julian Date in days   Returns: Julian centuries since epoch J2000 (2000-01-01) atan2(y, x)   Specialized arctan function   Parameters:      y (float) : radians      x (float) : radians   Returns: special arctan of y/x eccAnom(ec, m_param, dp)   Compute eccentricity of the anomaly   Parameters:      ec (float) : Eccentricity of Orbit      m_param (float) : Mean Anomaly ?      dp (int) : Decimal places to round to   Returns: Eccentricity of the Anomaly planetEphemerisCalc(TGen, planetElementId, planetRatesId)   Compute planetary ephemeris (longtude relative to Earth or Sun) on a Julian date   Parameters:      TGen (float) : Julian Date      planetElementId (float ) : All planet orbital elements in an array. This index references a specific planet's elements.      planetRatesId (float ) : All planet orbital rates in an array. This index references a specific planet's rates.   Returns: X,Y,Z ecliptic rectangular coordinates and R radius from reference body. calculateRightAscensionAndDeclination(earthX, earthY, earthZ, planetX, planetY, planetZ)   Calculate right ascension and declination for a planet relative to Earth   Parameters:      earthX (float) : Earth X ecliptic rectangular coordinate relative to Sun      earthY (float) : Earth Y ecliptic rectangular coordinate relative to Sun      earthZ (float) : Earth Z ecliptic rectangular coordinate relative to Sun      planetX (float) : Planet X ecliptic rectangular coordinate relative to Sun      planetY (float) : Planet Y ecliptic rectangular coordinate relative to Sun      planetZ (float) : Planet Z ecliptic rectangular coordinate relative to Sun   Returns: Planet geocentric orbital radius, geocentric right ascension, and geocentric declination mercuryHelio(T)   Compute Mercury heliocentric longitude on date   Parameters:      T (float)   Returns: Mercury heliocentric longitude on date venusHelio(T)   Compute Venus heliocentric longitude on date   Parameters:      T (float)   Returns: Venus heliocentric longitude on date earthHelio(T)   Compute Earth heliocentric longitude on date   Parameters:      T (float)   Returns: Earth heliocentric longitude on date marsHelio(T)   Compute Mars heliocentric longitude on date   Parameters:      T (float)   Returns: Mars heliocentric longitude on date jupiterHelio(T)   Compute Jupiter heliocentric longitude on date   Parameters:      T (float)   Returns: Jupiter heliocentric longitude on date saturnHelio(T)   Compute Saturn heliocentric longitude on date   Parameters:      T (float)   Returns: Saturn heliocentric longitude on date neptuneHelio(T)   Compute Neptune heliocentric longitude on date   Parameters:      T (float)   Returns: Neptune heliocentric longitude on date uranusHelio(T)   Compute Uranus heliocentric longitude on date   Parameters:      T (float)   Returns: Uranus heliocentric longitude on date sunGeo(T)   Parameters:      T (float) mercuryGeo(T)   Parameters:      T (float) venusGeo(T)   Parameters:      T (float) marsGeo(T)   Parameters:      T (float) jupiterGeo(T)   Parameters:      T (float) saturnGeo(T)   Parameters:      T (float) neptuneGeo(T)   Parameters:      T (float) uranusGeo(T)   Parameters:      T (float) moonGeo(T_JD)   Parameters:      T_JD (float) mercuryOrbitalPeriod()   Mercury orbital period in Earth days   Returns: 87.9691 venusOrbitalPeriod()   Venus orbital period in Earth days   Returns: 224.701 earthOrbitalPeriod()   Earth orbital period in Earth days   Returns: 365.256363004 marsOrbitalPeriod()   Mars orbital period in Earth days   Returns: 686.980 jupiterOrbitalPeriod()   Jupiter orbital period in Earth days   Returns: 4332.59 saturnOrbitalPeriod()   Saturn orbital period in Earth days   Returns: 10759.22 uranusOrbitalPeriod()   Uranus orbital period in Earth days   Returns: 30688.5 neptuneOrbitalPeriod()   Neptune orbital period in Earth days   Returns: 60195.0 jupiterSaturnCompositePeriod() jupiterNeptuneCompositePeriod() jupiterUranusCompositePeriod() saturnNeptuneCompositePeriod() saturnUranusCompositePeriod() planetSineWave(julianDateInCenturies, planetOrbitalPeriod, planetHelio)   Convert heliocentric longitude of planet into a sine wave   Parameters:      julianDateInCenturies (float)      planetOrbitalPeriod (float) : Orbital period of planet in Earth days      planetHelio (float) : Heliocentric longitude of planet in degrees   Returns: Sine of heliocentric longitude on a Julian date
Pine Script® library
by Riester
Regression Channel Alternative MTF V2█ OVERVIEW This indicator is a predecessor to Regression Channel Alternative MTF , which is coded based on latest update of type, object and method. █ IMPORTANT NOTES This indicator is NOT true Multi Timeframe (MTF) but considered as Alternative MTF which calculate 100 bars for Primary MTF, can be refer from provided line helper. The timeframe scenarios are defined based on Position, Swing and Intraday Trader. Suppported Timeframe : W, D, 60, 15, 5 and 1. Channel drawn based on regression calculation. Angle channel is NOT supported. █ INSPIRATIONS These timeframe scenarios are defined based on Harmonic Trading : Volume Three written by Scott M Carney. By applying channel on each timeframe, MW or ABCD patterns can be easily identified manually. This can also be applied on other chart patterns. █ CREDITS Scott M Carney, Harmonic Trading : Volume Three (Reaction vs. Reversal) █ TIMEFRAME EXPLAINED Higher / Distal : The (next) longer or larger comparative timeframe after primary pattern has been identified. Primary / Clear : Timeframe that possess the clearest pattern structure. Lower / Proximate : The (next) shorter timeframe after primary pattern has been identified. Lowest : Check primary timeframe as main reference. █ FEATURES Color is determined by trend or timeframe. Some color is depends on chart contrast color. Color is determined by trend or timeframe. █ EXAMPLE OF USAGE / EXPLAINATION
Pine Script® indicator
by RozaniGhani-RG
7
Lyapunov Hodrick-Prescott Oscillator w/ DSL [Loxx]Lyapunov Hodrick-Prescott Oscillator w/ DSL is a Hodrick-Prescott Channel Filter that is modified using the Lyapunov stability algorithm to turn the filter into an oscillator. Signals are created using Discontinued Signal Lines. What is the Lyapunov Stability? As soon as scientists realized that the evolution of physical systems can be described in terms of mathematical equations, the stability of the various dynamical regimes was recognized as a matter of primary importance. The interest for this question was not only motivated by general curiosity, but also by the need to know, in the XIX century, to what extent the behavior of suitable mechanical devices remains unchanged, once their configuration has been perturbed. As a result, illustrious scientists such as Lagrange, Poisson, Maxwell and others deeply thought about ways of quantifying the stability both in general and specific contexts. The first exact definition of stability was given by the Russian mathematician Aleksandr Lyapunov who addressed the problem in his PhD Thesis in 1892, where he introduced two methods, the first of which is based on the linearization of the equations of motion and has originated what has later been termed Lyapunov exponents (LE). (Lyapunov 1992) The interest in it suddenly skyrocketed during the Cold War period when the so-called "Second Method of Lyapunov" (see below) was found to be applicable to the stability of aerospace guidance systems which typically contain strong nonlinearities not treatable by other methods. A large number of publications appeared then and since in the control and systems literature. More recently the concept of the Lyapunov exponent (related to Lyapunov's First Method of discussing stability) has received wide interest in connection with chaos theory . Lyapunov stability methods have also been applied to finding equilibrium solutions in traffic assignment problems. In practice, Lyapunov exponents can be computed by exploiting the natural tendency of an n-dimensional volume to align along the n most expanding subspace. From the expansion rate of an n-dimensional volume, one obtains the sum of the n largest Lyapunov exponents. Altogether, the procedure requires evolving n linearly independent perturbations and one is faced with the problem that all vectors tend to align along the same direction. However, as shown in the late '70s, this numerical instability can be counterbalanced by orthonormalizing the vectors with the help of the Gram-Schmidt procedure (Benettin et al. 1980, Shimada and Nagashima 1979) (or, equivalently with a QR decomposition). As a result, the LE λi, naturally ordered from the largest to the most negative one, can be computed: they are altogether referred to as the Lyapunov spectrum. The Lyapunov exponent "λ" , is useful for distinguishing among the various types of orbits. It works for discrete as well as continuous systems. λ < 0 The orbit attracts to a stable fixed point or stable periodic orbit. Negative Lyapunov exponents are characteristic of dissipative or non-conservative systems (the damped harmonic oscillator for instance). Such systems exhibit asymptotic stability; the more negative the exponent, the greater the stability. Superstable fixed points and superstable periodic points have a Lyapunov exponent of λ = −∞. This is something akin to a critically damped oscillator in that the system heads towards its equilibrium point as quickly as possible. λ = 0 The orbit is a neutral fixed point (or an eventually fixed point). A Lyapunov exponent of zero indicates that the system is in some sort of steady state mode. A physical system with this exponent is conservative. Such systems exhibit Lyapunov stability. Take the case of two identical simple harmonic oscillators with different amplitudes. Because the frequency is independent of the amplitude, a phase portrait of the two oscillators would be a pair of concentric circles. The orbits in this situation would maintain a constant separation, like two flecks of dust fixed in place on a rotating record. λ > 0 The orbit is unstable and chaotic. Nearby points, no matter how close, will diverge to any arbitrary separation. All neighborhoods in the phase space will eventually be visited. These points are said to be unstable. For a discrete system, the orbits will look like snow on a television set. This does not preclude any organization as a pattern may emerge. Thus the snow may be a bit lumpy. For a continuous system, the phase space would be a tangled sea of wavy lines like a pot of spaghetti. A physical example can be found in Brownian motion. Although the system is deterministic, there is no order to the orbit that ensues. For our purposes here, we transform the HP by applying Lyapunov Stability as follows: output = math.log(math.abs(HP / HP )) You can read more about Lyapunov Stability here: Measuring Chaos What is. the Hodrick-Prescott Filter? The Hodrick-Prescott (HP) filter refers to a data-smoothing technique. The HP filter is commonly applied during analysis to remove short-term fluctuations associated with the business cycle. Removal of these short-term fluctuations reveals long-term trends. The Hodrick-Prescott (HP) filter is a tool commonly used in macroeconomics. It is named after economists Robert Hodrick and Edward Prescott who first popularized this filter in economics in the 1990s. Hodrick was an economist who specialized in international finance. Prescott won the Nobel Memorial Prize, sharing it with another economist for their research in macroeconomics. This filter determines the long-term trend of a time series by discounting the importance of short-term price fluctuations. In practice, the filter is used to smooth and detrend the Conference Board's Help Wanted Index (HWI) so it can be benchmarked against the Bureau of Labor Statistic's (BLS) JOLTS, an economic data series that may more accurately measure job vacancies in the U.S. The HP filter is one of the most widely used tools in macroeconomic analysis. It tends to have favorable results if the noise is distributed normally, and when the analysis being conducted is historical. What are DSL Discontinued Signal Line? A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy : comparing the value to it's smoothed (slightly lagging) state, the idea of current momentum/state is made. Discontinued signal line is inheriting that simple signal line idea and it is extending it : instead of having one signal line, more lines depending on the current value of the indicator. "Signal" line is calculated the following way : When a certain level is crossed into the desired direction, the EMA of that value is calculated for the desired signal line When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods. In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level. Included: Bar coloring Alerts Signals Loxx's Expanded Source Types
Pine Script® indicator
by loxx
8
Weight Gain 4000 - (Adjustable Volume Weighted MA) - [mutantdog]Short Version: This is a fairly self-contained system based upon a moving average crossover with several unique features. The most significant of these is the adjustable volume weighting system, allowing for transformations between standard and weighted versions of each included MA. With this feature it is possible to apply partial weighting which can help to improve responsiveness without dramatically altering shape. Included types are SMA, EMA, WMA, RMA, hSMA, DEMA and TEMA. Potentially more will be added in future (check updates below). In addition there are a selection of alternative 'weighted' inputs, a pair of Bollinger-style deviation bands, a separate price tracker and a bunch of alert presets. This can be used out-of-the-box or tweaked in multiple ways for unusual results. Default settings are a basic 8/21 EMA cross with partial volume weighting. Dev bands apply to MA2 and are based upon the type and the volume weighting. For standard Bollinger bands use SMA with length 20 and try adding a small amount of volume weighting. A more detailed breakdown of the functionality follows. Long Version: ADJUSTABLE VOLUME WEIGHTING In principle any moving average should have a volume weighted analogue, the standard VWMA is just an SMA with volume weighting for example. Actually, we can consider the SMA to be a special case where volume is a constant 1 per bar (the value is somewhat arbitrary, the important part is that it's constant). Similar principles apply to the 'elastic' EVWMA which is the volume weighted analogue of an RMA. In any case though, where we have standard and weighted variants it is possible to transform one into the other by gradually increasing or decreasing the weighting, which forms the basis of this system. This is not just a simple multiplier however, that would not work due to the relative proportions being the same when set at any non zero value. In order to create a meaningful transformation we need to use an exponent instead, eg: volume^x , where x is a variable determined in this case by the 'volume' parameter. When x=1, the full volume weighting applies and when x=0, the volume will be reduced to a constant 1. Values in between will result in the respective partial weighting, for example 0.5 will give the square root of the volume. The obvious question here though is why would you want to do this? To answer that really it is best to actually try it. The advantages that volume weighting can bring to a moving average can sometimes come at the cost of unwanted or erratic behaviour. While it can tend towards much closer price tracking which may be desirable, sometimes it needs moderating especially in markets with lower liquidity. Here the adjustability can be useful, in many cases i have found that adding a small amount of volume weighting to a chosen MA can help to improve its responsiveness without overpowering it. Another possible use case would be to have two instances of the same MA with the same length but different weightings, the extent to which these diverge from each other can be a useful indicator of trend strength. Other uses will become apparent with experimentation and can vary from one market to another. THE INCLUDED MODES At the time of publication, there are 7 included moving average types with plans to add more in future. For now here is a brief explainer of what's on offer (continuing to use x as shorthand for the volume parameter), starting with the two most common types. SMA: As mentioned above this is essentially a standard VWMA, calculated here as sma(source*volume^x,length)/sma(volume^x,length). In this case when x=0 then volume=1 and it reduces to a standard SMA. RMA: Again mentioned above, this is an EVWMA (where E stands for elastic) with constant weighting. Without going into detail, this method takes the 1/length factor of an RMA and replaces it with volume^x/sum(volume^x,length). In this case again we can see that when x=0 then volume=1 and the original 1/length factor is restored. EMA: This follows the same principle as the RMA where the standard 2/(length+1) factor is replaced with (2*volume^x)/(sum(volume^x,length)+volume^x). As with an RMA, when x=0 then volume=1 and this reduces back to the standard 2/(length+1). DEMA: Just a standard Double EMA using the above. TEMA: Likewise, a standard Triple EMA using the above. hSMA: This is the same as the SMA except it uses harmonic mean calculations instead of arithmetic. In most cases the differences are negligible however they can become more pronounced when volume weighting is introduced. Furthermore, an argument can be made that harmonic mean calculations are better suited to downtrends or bear markets, in principle at least. WMA: Probably the most contentious one included. Follows the same basic calculations as for the SMA except uses a WMA instead. Honestly, it makes little sense to combine both linear and volume weighting in this manner, included only for completeness and because it can easily be done. It may be the case that a superior composite could be created with some more complex calculations, in which case i may add that later. For now though this will do. An additional 'volume filter' option is included, which applies a basic filter to the volume prior to calculation. For types based around the SMA/VWMA system, the volume filter is a WMA-4, for types based around the RMA/EVWMA system the filter is a RMA-2. As and when i add more they will be listed in the updates at the bottom. WEIGHTED INPUTS The ohlc method of source calculations is really a leftover from a time when data was far more limited. Nevertheless it is still the method used in charting and for the most part is sufficient. Often the only important value is 'close' although sometimes 'high' and 'low' can be relevant also. Since we are volume weighting however, it can be useful to incorporate as much information as possible. To that end either 'hlc3' or 'hlcc4' tend to be the best of the defaults (in the case of 24/7 charting like crypto or intraday trading, 'ohlc4' should be avoided as it is effectively the same as a lagging version of 'hlcc4'). There are many other (infinitely many, in fact) possible combinations that can be created, i have included a few here. The premise is fairly straightforward, by subtracting one value from another, the remaining difference can act as a kind of weight. In a simple case consider 'hl2' as simply the midrange ((high+low)/2), instead of this using 'high+low-open' would give more weight to the value furthest from the open, providing a good estimate of the median. An even better estimate can be achieved by combining that with 'high+low-close' to give the included result 'hl-oc2'. Similarly, 'hlc3' can be considered the basic mean of the three significant values, an included weighted version 'hlc2-o2' combines a sum with subtraction of open to give an estimated mean that may be more accurate. Finally we can apply a similar principle to the close, by subtracting the other values, this one potentially gets more complex so the included 'cc-ohlc4' is really the simplest. The result here is an overbias of the close in relation to the open and the midrange, while in most cases not as useful it can provide an estimate for the next bar assuming that the trend continues. Of the three i've included, hlc2-o2 is in my opinion the most useful especially in this context, although it is perhaps best considered to be experimental in nature. For that reason, i've kept 'hlcc4' as the default for both MAs. Additionally included is an 'aux input' which is the standard TV source menu and, where possible, can be set as outputs of other indicators. THE SYSTEM This one is fairly obvious and straightforward. It's just a moving average crossover with additional deviation (bollinger) bands. Not a lot to explain here as it should be apparent how it works. Of the two, MA1 is considered to be the fast and MA2 is considered to be the slow. Both can be set with independent inputs, types and weighting. When MA1 is above, the colour of both is green and when it's below the colour of both is red. An additional gradient based fill is there and can be adjusted along with everything else in the visuals section at the bottom. Default alerts are available for crossover/crossunder conditions along with optional marker plots. MA2 has the option for deviation bands, these are calculated based upon the MA type used and volume weighted according to the main parameter. In the case of a unweighted SMA being used they will be standard Bollinger bands. An additional 'source direct' price tracker is included which can be used as the basis for an alert system for price crossings of bands or MAs, while taking advantage of the available weighted inputs. This is displayed as a stepped line on the chart so is also a good way to visualise the differences between input types. That just about covers it then. The likelihood is that you've used some sort of moving average cross system before and are probably still using one or more. If so, then perhaps the additional functionality here will be of benefit. Thanks for looking, I welcome any feedack
Pine Script® indicator
by mutantdog
1
PivotsLibrary "Pivots" This Library focuses in functions related to pivot highs and lows and some of their applications (i.e. divergences, zigzag, harmonics, support and resistance...) pivots(srcH, srcL, length) Delivers series of pivot highs, lows and zigzag.   Parameters:      srcH : Source series to look for pivot highs. Stricter applications might source from 'close' prices. Oscillators are also another possible source to look for pivot highs and lows. By default 'high'      srcL : Source series to look for pivot lows. By default 'low'      length : This value represents the minimum number of candles between pivots. The lower the number, the more detailed the pivot profile. The higher the number, the more relevant the pivots. By default 10   Returns: zigzagArray(pivotHigh, pivotLow) Delivers a Zigzag series based on alternating pivots. Ocasionally this line could paint a few consecutive lows or highs without alternating. That happens because it's finding a few consecutive Higher Highs or Lower Lows. If to use lines entities instead of series, that could be easily avoided. But in this one, I'm more interested outputting series rather than painting/deleting line entities.   Parameters:      pivotHigh : Pivot high series      pivotLow : Pivot low series   Returns: zigzagLine(srcH, srcL, colorLine, widthLine) Delivers a Zigzag based on line entities.   Parameters:      srcH : Source series to look for pivot highs. Stricter applications might source from 'close' prices. Oscillators are also another possible source to look for pivot highs and lows. By default 'high'      srcL : Source series to look for pivot lows. By default 'low'      colorLine : Color of the Zigzag Line. By default Fuchsia      widthLine : Width of the Zigzag Line. By default 4   Returns: Zigzag printed on screen divergence(h2, l2, h1, l1, length) Calculates divergences between 2 series   Parameters:      h2 : Series in which to locate divs: Highs      l2 : Series in which to locate divs: Lows      h1 : Series in which to locate pivots: Highs. By default high      l1 : Series in which to locate pivots: Lows. By default low      length : Length used to calculate Pivots: By default 10   Returns:
Pine Script® library
by gliderfund
2
AB=CD Reciprocal Ratios Table (Source Code)This table indicator was intended as helper / reference for using ABCD Pattern. Indikator berjadual bertujuan sebagai bantuan / rujukan untuk kegunaan ABCD Pattern. The values shown in table was based on Harmonic Trading : Volume One book written by Scott M Carney. Details of value, refer Chapter 4 : The AB=CD Pattern (Page 41). These values are known as AB=CD Reciprocal Ratios. Nilai yang ditunjukkan dalam jadual adalah berdasarkan buku Harmonic Trading : Volume One ditulis oleh Scott M Carney. Nilai secara menyeluruh, rujuk Chapter 4 : The AB=CD Pattern (Muka surat 41). Nilai berikut dipanggil sebagai AB=CD Reciprocal Ratios Indicator features : 1. List AB=CD Reciprocal Ratios. 2. Font size small for mobile app and font size normal for desktop. Kemampuan indikator : 1. Senarai AB=CD Reciprocal Ratio. 2. Saiz font kecil untuk mobile app dan saiz size normal untuk desktop. FAQ 1. Credits / Kredit Scott M Carney, 2. Code Usage / Penggunaan Kod Free to use for personal usage but credits are most welcomed especially for credits to Scott M Carney/ Bebas untuk kegunaan peribadi tetapi kredit adalah amat dialu-alukan terutamanya kredit kepada Scott M Carney. Settings with appropriate value. Setting dengan nilai yang sesuai. Default Settings. Setting asal. Settings with different table position. Setting dengan posisi jadual yang berbeza.
Pine Script® indicator
by RozaniGhani-RG
1
Using The AM/GM Inequality To Estimate VolatilityA volatility indicator derived from the AM/GM inequality. I don't think it will be necessary to describe the usage and interpretation of such indicator, and I don't think it is super useful, however, this is not the case of the script, which contains three ways to compute the geometric mean, with a classic, a simple, and an efficient way. The AM/GM inequality is also a really interesting concept, and I'll try to"prove" it in this post by using DSP. I also added more comments in the script in order to highlight some stuff. The AM/GM Inequality When we talk about the mean, we are referring to the "arithmetic" one by default, but there exist more types of means. Two other ones include the "geometric" and "harmonic" means, both are part of the Pythagorean means with the arithmetic mean. Each one of them as several properties, but the most interesting aspect is their inequality, that is: HM <= GM <= AM The arithmetic mean is the one with the highest value, while the harmonic mean is the one with the lowest value. In the case each data point is equal to each other, all the means have the same value. In our case, the inequality of interest is the inequality between the geometric and arithmetic mean, where the geometric mean is lower or equal than the arithmetic one. Many proofs/explanations exist, I'll try my version using DSP, where instead of thinking about means, we think about rolling means, which allows us to interpret them as low-pass filters. So we end up having the geometric moving average (GMA) and arithmetic moving average (SMA). We know that GMA <= SMA , the SMA has a unity passband, this implies that the GMA has a passband lower than 1 (for non-equal input values), this explains why the GMA is smaller than the SMA. In order for a FIR filter to have a passband lower than 1, the sum of the filter coefficients must be lower than 1. In order to further proves this consider the following equation: sqrt(a×b) = k×a + k×b Here sqrt(a×b) is the geometric mean of a and b , the right-hand side of the equation is a weighted sum between a and b and coefficient k , we want to solve the equation with respect to k , if k×2 < 1 then we have the proof that GMA < SMA . The solution with respect to k is: k = sqrt(a×b)/(a+b) which always gives a number lower than 0.5, as such k×2 < 1 and thus the passband is lower than 1. If our input values are equal to each other, we end up with the following solution for k : k = sqrt(a×a)/(a+a) = a/(2×a) = 0.5 as such the GMA has the coefficients of an SMA as long as the input values are equal to each other. Because of this inequality, we can subtract the SMA to a GMA and take the square root of the result in order to have a volatility indicator, however, both moving averages are still pretty close to each other, which gives a very small result for the indicator. Uwu I am a bit tired, better indicators coming up
Pine Script® indicator
by alexgrover
2
Musical Harmonics - Start with a low.Octaves double from one octave to another, so start with octaves beginning with the number one, for example: 1 doubled is 2, 2 doubled is 4, 4 double is 8 and then we go on to this sequence: 1,2,4,8,16,32,64,126,256,512,1024,2048,etc,etc Find one of the numbers near a range, so for example on this chart Ethereum was trading at 190.31. That price is in between the octaves of 126 and 256. The number I use as the low for the indicator is 126. Working on updating with labels and such
Pine Script® indicator
by itsjustanalysis
5
Verified Astro-Table SimplifiedThis script, titled the **Financial Astrological Ephemeris Table**, is designed to be a high-precision astronomical dashboard for TradingView. Unlike standard indicators that rely on price formulas, this script serves as a **digital bridge** between professional Swiss Ephemeris data and your trading chart. Here is a detailed breakdown of what the script provides and how to maximize its utility. --- **1. What the Script Provides** **A. 100% Ephemeris Synchronization** Most "Astro" indicators in TradingView use "mean motion" math, which drifts over time. This script uses **Static Switch Logic**. By hard-coding the data from the Swiss Ephemeris, the script ensures that the degrees you see on your chart match the physical reality of the sky. * **Sun & Moon**: Accurate to the degree for the current period. * **Saturn & Outer Planets**: Corrects the "sign drift" found in other scripts, keeping Saturn in its true position (late Pisces for 2025). **B. Sign & Degree Tracking** The script translates raw longitude (0–360°) into the traditional 12-sign zodiac format (`Sign` + `Degree`). This allows you to immediately identify where planets are transiting relative to key price levels. **C. The Sun-Relative House System** The script calculates an **Equal House System** based on the Sun's current position. * This treats the Sun as the "Rising" point for the day's dashboard, showing you how other planets are "angled" relative to the Sun's current solar light. **D. Stability and Performance** Because the script uses `barstate.islast`, it only calculates for the most recent candle. This prevents "Runtime Errors" and ensures your TradingView platform remains fast and responsive, even on low-powered laptops. --- **2. How to Use it Effectively** **A. Identifying Confluence with Price** Watch for "Degree Hits." If the table shows **Saturn at 25° Pisces** and your asset is hitting a major resistance level at a number ending in **25** (or a harmonic like 2.50), it signifies a moment of "Astro-Price Confluence." These are often high-probability reversal points. **B. Customizing the Visual Experience** You can tailor the dashboard to your specific chart layout via the **Settings (Gear Icon)**: * **Position**: Move the table to any corner (Top Right, Bottom Left, etc.) so it doesn't block your price action. * **Transparency**: Adjust the "Background Color" to make the table more subtle or more prominent. * **Text Size**: If you trade on a mobile device, set the text to "Normal." If you use a 4K monitor, set it to "Tiny" to save space. **C. Managing the "Switch" Data** To keep the script accurate for the long term, I will update the `get_pdf_lon` block once a month (or once a year) with the new coordinates from the Swiss Ephemeris. **D. Directional Trading (The "Dir" Column)** The script includes a "Direction" column. Use this to track if a planet is **Direct (D)** or **Retrograde (Rx)**. **Strategy**: If a planet is listed as "D," its influence is considered "forward-moving" and predictable. If you update the code to show "Rx," expect the market sectors associated with that planet to experience "re-evaluations" or delays. --- ### Summary of Benefits for the User 1. **Eliminates Guesswork**: You no longer have to flip between an Ephemeris and TradingView; the data is on your screen. 2. **Historical Analysis**: You can manually change the data in the script to a historical date to see exactly how the "Astro-Weather" looked during a previous market crash or rally.
Pine Script® indicator
by Patiently_Pippin_
BTC - BEAM: Adaptive Multiple (Open-Source)Title: BTC - BEAM: Adaptive Multiple Cycle Oscillator | RM Overview & Philosophy The BTC - BEAM (Bitcoin Economics Adaptive Multiple) is a premier macro-valuation tool designed to identify the "Logarithmic Pulse" of Bitcoin's 4-year cycles. Unlike standard oscillators that lose relevance as the network grows, BEAM uses an adaptive baseline that tracks Bitcoin’s fundamental growth curve with precision. It identifies the harmonic distance between the current price and its multi-year mean, helping you spot the rare windows of deep capitulation and terminal euphoria. Methodology This edition is a hardened, gap-proof and Open-Source implementation of the canonical BEAM model. 1. The 1400-Day Anchor (200 Weeks): The model is anchored to a 1400-day Simple Moving Average. On the Weekly chart, this aligns with the legendary 200-week moving average—the historical "floor" of the Bitcoin network. It represents one full halving cycle of data. 2. Daily-Lock Architecture: Even when viewed on the 1W chart, the script performs its calculations using Daily data. This ensures that the oscillator captures the exact peak day of a cycle, providing a "high-resolution" signal within a "low-noise" weekly environment. 3. Logarithmic Normalization: We calculate the natural logarithm of the price-to-mean relationship, scaled by a factor of 2.5: Score = ln(Price / 1400d MA) / 2.5 This creates a standardized "Multiple" that remains comparable across all Bitcoin eras. How to Read the Chart (1W Context) 🟧 The BEAM Line (Orange): Tracks the "macro heat" of the market. On the 1W chart, look for the slope of this line to identify cycle acceleration. 🔴 The Cycle Ceiling (Score > 1.0): Historical Cycle Tops. When the weekly candle sustains in this zone, the market has reached a state of unsustainable mania. Every major blow-off top has been captured in this red corridor. 🟢 The Cycle Floor (Score < 0.1): Generational Accumulation. On the 1W chart, these zones appear as extended "green troughs." These are the only times in history where Bitcoin is fundamentally "too cheap" relative to its 4-year trend. The Status Dashboard The bottom-right monitor provides immediate cycle classification: • BEAM Score: The exact logarithmic multiple. • Cycle Regime: ACCUMULATION , NEUTRAL , or OVERHEATED . Credits BitcoinEcon: For the original concept of the BEAM adaptive model. ⚠️ RECOMMENDATION: While this indicator captures daily data, it is strongly recommended to be viewed on the Weekly (1W) Timeframe. The 1W chart filters market noise and perfectly reveals the long-term "Cycle Narrative." Disclaimer This script is for research and educational purposes only. Macro indicators provide structural context; they are not crystal balls. Always manage your risk according to your personal financial plan. Tags bitcoin, btc, beam, macro, cycle, halving, log-growth, valuation, on-chain, Rob Maths
Pine Script® indicator
by Rob_Maths
ORB Fusion🎯 CORE INNOVATION: INSTITUTIONAL ORB FRAMEWORK WITH FAILED BREAKOUT INTELLIGENCE ORB Fusion represents a complete institutional-grade Opening Range Breakout system combining classic Market Profile concepts (Initial Balance, day type classification) with modern algorithmic breakout detection, failed breakout reversal logic, and comprehensive statistical tracking. Rather than simply drawing lines at opening range extremes, this system implements the full trading methodology used by professional floor traders and market makers—including the critical concept that failed breakouts are often higher-probability setups than successful breakouts . The Opening Range Hypothesis: The first 30-60 minutes of trading establishes the day's value area —the price range where the majority of participants agree on fair value. This range is formed during peak information flow (overnight news digestion, gap reactions, early institutional positioning). Breakouts from this range signal directional conviction; failures to hold breakouts signal trapped participants and create exploitable reversals. Why Opening Range Matters: 1. Information Aggregation : Opening range reflects overnight news, pre-market sentiment, and early institutional orders. It's the market's initial "consensus" on value. 2. Liquidity Concentration : Stop losses cluster just outside opening range. Breakouts trigger these stops, creating momentum. Failed breakouts trap traders, forcing reversals. 3. Statistical Persistence : Markets exhibit range expansion tendency —when price accepts above/below opening range with volume, it often extends 1.0-2.0x the opening range size before mean reversion. 4. Institutional Behavior : Large players (market makers, institutions) use opening range as reference for the day's trading plan. They fade extremes in rotation days and follow breakouts in trend days. Historical Context: Opening Range Breakout methodology originated in commodity futures pits (1970s-80s) where floor traders noticed consistent patterns: the first 30-60 minutes established a "fair value zone," and directional moves occurred when this zone was violated with conviction. J. Peter Steidlmayer formalized this observation in Market Profile theory, introducing the "Initial Balance" concept—the first hour (two 30-minute periods) defining market structure. 📊 OPENING RANGE CONSTRUCTION Four ORB Timeframe Options: 1. 5-Minute ORB (0930-0935 ET): Captures immediate market direction during "opening drive"—the explosive first few minutes when overnight orders hit the tape. Use Case: • Scalping strategies • High-frequency breakout trading • Extremely liquid instruments (ES, NQ, SPY) Characteristics: • Very tight range (often 0.2-0.5% of price) • Early breakouts common (7 of 10 days break within first hour) • Higher false breakout rate (50-60%) • Requires sub-minute chart monitoring Psychology: Captures panic buyers/sellers reacting to overnight news. Range is small because sample size is minimal—only 5 minutes of price discovery. Early breakouts often fail because they're driven by retail FOMO rather than institutional conviction. 2. 15-Minute ORB (0930-0945 ET): Balances responsiveness with statistical validity. Captures opening drive plus initial reaction to that drive. Use Case: • Day trading strategies • Balanced scalping/swing hybrid • Most liquid instruments Characteristics: • Moderate range (0.4-0.8% of price typically) • Breakout rate ~60% of days • False breakout rate ~40-45% • Good balance of opportunity and reliability Psychology: Includes opening panic AND the first retest/consolidation. Sophisticated traders (institutions, algos) start expressing directional bias. This is the "Goldilocks" timeframe—not too reactive, not too slow. 3. 30-Minute ORB (0930-1000 ET): Classic ORB timeframe. Default for most professional implementations. Use Case: • Standard intraday trading • Position sizing for full-day trades • All liquid instruments (equities, indices, futures) Characteristics: • Substantial range (0.6-1.2% of price) • Breakout rate ~55% of days • False breakout rate ~35-40% • Statistical sweet spot for extensions Psychology: Full opening auction + first institutional repositioning complete. By 10:00 AM ET, headlines are digested, early stops are hit, and "real" directional players reveal themselves. This is when institutional programs typically finish their opening positioning. Statistical Advantage: 30-minute ORB shows highest correlation with daily range. When price breaks and holds outside 30m ORB, probability of reaching 1.0x extension (doubling the opening range) exceeds 60% historically. 4. 60-Minute ORB (0930-1030 ET) - Initial Balance: Steidlmayer's "Initial Balance"—the foundation of Market Profile theory. Use Case: • Swing trading entries • Day type classification • Low-frequency institutional setups Characteristics: • Wide range (0.8-1.5% of price) • Breakout rate ~45% of days • False breakout rate ~25-30% (lowest) • Best for trend day identification Psychology: Full first hour captures A-period (0930-1000) and B-period (1000-1030). By 10:30 AM ET, all early positioning is complete. Market has "voted" on value. Subsequent price action confirms (trend day) or rejects (rotation day) this value assessment. Initial Balance Theory: IB represents the market's accepted value area . When price extends significantly beyond IB (>1.5x IB range), it signals a Trend Day —strong directional conviction. When price remains within 1.0x IB, it signals a Rotation Day —mean reversion environment. This classification completely changes trading strategy. 🔬 LTF PRECISION TECHNOLOGY The Chart Timeframe Problem: Traditional ORB indicators calculate range using the chart's current timeframe. This creates critical inaccuracies: Example: • You're on a 5-minute chart • ORB period is 30 minutes (0930-1000 ET) • Indicator sees only 6 bars (30min ÷ 5min/bar = 6 bars) • If any 5-minute bar has extreme wick, entire ORB is distorted The Problem Amplifies: • On 15-minute chart with 30-minute ORB: Only 2 bars sampled • On 30-minute chart with 30-minute ORB: Only 1 bar sampled • Opening spike or single large wick defines entire range (invalid) Solution: Lower Timeframe (LTF) Precision: ORB Fusion uses `request.security_lower_tf()` to sample 1-minute bars regardless of chart timeframe: ``` For 30-minute ORB on 15-minute chart: - Traditional method: Uses 2 bars (15min × 2 = 30min) - LTF Precision: Requests thirty 1-minute bars, calculates true high/low ``` Why This Matters: Scenario: ES futures, 15-minute chart, 30-minute ORB • Traditional ORB: High = 5850.00, Low = 5842.00 (range = 8 points) • LTF Precision ORB: High = 5848.50, Low = 5843.25 (range = 5.25 points) Difference: 2.75 points distortion from single 15-minute wick hitting 5850.00 at 9:31 AM then immediately reversing. LTF precision filters this out by seeing it was a fleeting wick, not a sustained high. Impact on Extensions: With inflated range (8 points vs 5.25 points): • 1.5x extension projects +12 points instead of +7.875 points • Difference: 4.125 points (nearly $200 per ES contract) • Breakout signals trigger late; extension targets unreachable Implementation: ```pinescript getLtfHighLow() => float ha = request.security_lower_tf(syminfo.tickerid, "1", high) float la = request.security_lower_tf(syminfo.tickerid, "1", low) ``` Function returns arrays of 1-minute high/low values, then finds true maximum and minimum across all samples. When LTF Precision Activates: Only when chart timeframe exceeds ORB session window: • 5-minute chart + 30-minute ORB: LTF used (chart TF > session bars needed) • 1-minute chart + 30-minute ORB: LTF not needed (direct sampling sufficient) Recommendation: Always enable LTF Precision unless you're on 1-minute charts. The computational overhead is negligible, and accuracy improvement is substantial. ⚖️ INITIAL BALANCE (IB) FRAMEWORK Steidlmayer's Market Profile Innovation: J. Peter Steidlmayer developed Market Profile in the 1980s for the Chicago Board of Trade. His key insight: market structure is best understood through time-at-price (value area) rather than just price-over-time (traditional charts). Initial Balance Definition: IB is the price range established during the first hour of trading, subdivided into: • A-Period : First 30 minutes (0930-1000 ET for US equities) • B-Period : Second 30 minutes (1000-1030 ET) A-Period vs B-Period Comparison: The relationship between A and B periods forecasts the day: B-Period Expansion (Bullish): • B-period high > A-period high • B-period low ≥ A-period low • Interpretation: Buyers stepping in after opening assessed • Implication: Bullish continuation likely • Strategy: Buy pullbacks to A-period high (now support) B-Period Expansion (Bearish): • B-period low < A-period low • B-period high ≤ A-period high • Interpretation: Sellers stepping in after opening assessed • Implication: Bearish continuation likely • Strategy: Sell rallies to A-period low (now resistance) B-Period Contraction: • B-period stays within A-period range • Interpretation: Market indecisive, digesting A-period information • Implication: Rotation day likely, stay range-bound • Strategy: Fade extremes, sell high/buy low within IB IB Extensions: Professional traders use IB as a ruler to project price targets: Extension Levels: • 0.5x IB : Initial probe outside value (minor target) • 1.0x IB : Full extension (major target for normal days) • 1.5x IB : Trend day threshold (classifies as trending) • 2.0x IB : Strong trend day (rare, ~10-15% of days) Calculation: ``` IB Range = IB High - IB Low Bull Extension 1.0x = IB High + (IB Range × 1.0) Bear Extension 1.0x = IB Low - (IB Range × 1.0) ``` Example: ES futures: • IB High: 5850.00 • IB Low: 5842.00 • IB Range: 8.00 points Extensions: • 1.0x Bull Target: 5850 + 8 = 5858.00 • 1.5x Bull Target: 5850 + 12 = 5862.00 • 2.0x Bull Target: 5850 + 16 = 5866.00 If price reaches 5862.00 (1.5x), day is classified as Trend Day —strategy shifts from mean reversion to trend following. 📈 DAY TYPE CLASSIFICATION SYSTEM Four Day Types (Market Profile Framework): 1. TREND DAY: Definition: Price extends ≥1.5x IB range in one direction and stays there. Characteristics: • Opens and never returns to IB • Persistent directional movement • Volume increases as day progresses (conviction building) • News-driven or strong institutional flow Frequency: ~20-25% of trading days Trading Strategy: • DO: Follow the trend, trail stops, let winners run • DON'T: Fade extremes, take early profits • Key: Add to position on pullbacks to previous extension level • Risk: Getting chopped in false trend (see Failed Breakout section) Example: FOMC decision, payroll report, earnings surprise—anything creating one-sided conviction. 2. NORMAL DAY: Definition: Price extends 0.5-1.5x IB, tests both sides, returns to IB. Characteristics: • Two-sided trading • Extensions occur but don't persist • Volume balanced throughout day • Most common day type Frequency: ~45-50% of trading days Trading Strategy: • DO: Take profits at extension levels, expect reversals • DON'T: Hold for massive moves • Key: Treat each extension as a profit-taking opportunity • Risk: Holding too long when momentum shifts Example: Typical day with no major catalysts—market balancing supply and demand. 3. ROTATION DAY: Definition: Price stays within IB all day, rotating between high and low. Characteristics: • Never accepts outside IB • Multiple tests of IB high/low • Decreasing volume (no conviction) • Classic range-bound action Frequency: ~25-30% of trading days Trading Strategy: • DO: Fade extremes (sell IB high, buy IB low) • DON'T: Chase breakouts • Key: Enter at extremes with tight stops just outside IB • Risk: Breakout finally occurs after multiple failures Example: [/b> Pre-holiday trading, summer doldrums, consolidation after big move. 4. DEVELOPING: Definition: Day type not yet determined (early in session). Usage: Classification before 12:00 PM ET when IB extension pattern unclear. ORB Fusion's Classification Algorithm: ```pinescript if close > ibHigh: ibExtension = (close - ibHigh) / ibRange direction = "BULLISH" else if close < ibLow: ibExtension = (ibLow - close) / ibRange direction = "BEARISH" if ibExtension >= 1.5: dayType = "TREND DAY" else if ibExtension >= 0.5: dayType = "NORMAL DAY" else if close within IB: dayType = "ROTATION DAY" ``` Why Classification Matters: Same setup (bullish ORB breakout) has opposite implications: • Trend Day : Hold for 2.0x extension, trail stops aggressively • Normal Day : Take profits at 1.0x extension, watch for reversal • Rotation Day : Fade the breakout immediately (likely false) Knowing day type prevents catastrophic errors like fading a trend day or holding through rotation. 🚀 BREAKOUT DETECTION & CONFIRMATION Three Confirmation Methods: 1. Close Beyond Level (Recommended): Logic: Candle must close above ORB high (bull) or below ORB low (bear). Why: • Filters out wicks (temporary liquidity grabs) • Ensures sustained acceptance above/below range • Reduces false breakout rate by ~20-30% Example: • ORB High: 5850.00 • Bar high touches 5850.50 (wick above) • Bar closes at 5848.00 (inside range) • Result: NO breakout signal vs. • Bar high touches 5850.50 • Bar closes at 5851.00 (outside range) • Result: BREAKOUT signal confirmed Trade-off: Slightly delayed entry (wait for close) but much higher reliability. 2. Wick Beyond Level: Logic: [/b> Any touch of ORB high/low triggers breakout. Why: • Earliest possible entry • Captures aggressive momentum moves Risk: • High false breakout rate (60-70%) • Stop runs trigger signals • Requires very tight stops (difficult to manage) Use Case: Scalping with 1-2 point profit targets where any penetration = trade. 3. Body Beyond Level: Logic: [/b> Candle body (close vs open) must be entirely outside range. Why: • Strictest confirmation • Ensures directional conviction (not just momentum) • Lowest false breakout rate Example: Trade-off: [/b> Very conservative—misses some valid breakouts but rarely triggers on false ones. Volume Confirmation Layer: All confirmation methods can require volume validation: Volume Multiplier Logic: Rationale: [/b> True breakouts are driven by institutional activity (large size). Volume spike confirms real conviction vs. stop-run manipulation. Statistical Impact: [/b> • Breakouts with volume confirmation: ~65% success rate • Breakouts without volume: ~45% success rate • Difference: 20 percentage points edge Implementation Note: [/b> Volume confirmation adds complexity—you'll miss breakouts that work but lack volume. However, when targeting 1.5x+ extensions (ambitious goals), volume confirmation becomes critical because those moves require sustained institutional participation. Recommended Settings by Strategy: [/b> Scalping (1-2 point targets): [/b> • Method: Close • Volume: OFF • Rationale: Quick in/out doesn't need perfection Intraday Swing (5-10 point targets): [/b> • Method: Close • Volume: ON (1.5x multiplier) • Rationale: Balance reliability and opportunity Position Trading (full-day holds): [/b> • Method: Body • Volume: ON (2.0x multiplier) • Rationale: Must be certain—large stops require high win rate 🔥 FAILED BREAKOUT SYSTEM The Core Insight: [/b> Failed breakouts are often more profitable [/b> than successful breakouts because they create trapped traders with predictable behavior. Failed Breakout Definition: [/b> A breakout that: 1. Initially penetrates ORB level with confirmation 2. Attracts participants (volume spike, momentum) 3. Fails to extend (stalls or immediately reverses) 4. Returns inside ORB range within N bars Psychology of Failure: [/b> When breakout fails: • Breakout buyers are trapped [/b>: Bought at ORB high, now underwater • Early longs reduce: Take profit, fearful of reversal • Shorts smell blood: See failed breakout as reversal signal • Result: Cascade of selling as trapped bulls exit + new shorts enter Mirror image for failed bearish breakouts (trapped shorts cover + new longs enter). Failure Detection Parameters: [/b> 1. Failure Confirmation Bars (default: 3): [/b> How many bars after breakout to confirm failure? Logic: Settings: [/b> • 2 bars: Aggressive failure detection (more signals, more false failures) • 3 bars Balanced (default) • 5-10 bars: Conservative (wait for clear reversal) Why This Matters: Too few bars: You call "failed breakout" when price is just consolidating before next leg. Too many bars: You miss the reversal entry (price already back in range). 2. Failure Buffer (default: 0.1 ATR): [/b> How far inside ORB must price return to confirm failure? Formula: Why Buffer Matters: clear rejection [/b> (not just hovering at level). Settings: [/b> • 0.0 ATR: No buffer, immediate failure signal • 0.1 ATR: Small buffer (default) - filters noise • [b>0.2-0.3 ATR: Large buffer - only dramatic failures count Example: Reversal Entry System: [/b> When failure confirmed, system generates complete reversal trade: For Failed Bull Breakout (Short Reversal): [/b> Entry: [/b> Current close when failure confirmed Stop Loss: [/b> Extreme high since breakout + 0.10 ATR padding Target 1: [/b> ORB High - (ORB Range × 0.5) Target 2: Target 3: [/b> ORB High - (ORB Range × 1.5) Example: • ORB High: 5850, ORB Low: 5842, Range: 8 points • Breakout to 5853, fails, reverses to 5848 (entry) • Stop: 5853 + 1 = 5854 (6 point risk) • T1: 5850 - 4 = 5846 (-2 points, 1:3 R:R) • T2: 5850 - 8 = 5842 (-6 points, 1:1 R:R) • T3: 5850 - 12 = 5838 (-10 points, 1.67:1 R:R) [b>Why These Targets? [/b> • T1 (0.5x ORB below high): Trapped bulls start panic • T2 (1.0x ORB = ORB Mid): Major retracement, momentum fully reversed • T3 (1.5x ORB): Reversal extended, now targeting opposite side Historical Performance: [/b> Failed breakout reversals in ORB Fusion's tracking system show: • Win Rate: 65-75% (significantly higher than initial breakouts) • Average Winner: 1.2x ORB range • Average Loser: 0.5x ORB range (protected by stop at extreme) • Expectancy: Strongly positive even with <70% win rate Why Failed Breakouts Outperform: [/b> 1. Information Advantage: You now know what price did (failed to extend). Initial breakout trades are speculative; reversal trades are reactive to confirmed failure. 2. Trapped Participant Pressure: Every trapped bull becomes a seller. This creates sustained pressure. 3. Stop Loss Clarity: Extreme high is obvious stop (just beyond recent high). Breakout trades have ambiguous stops (ORB mid? Recent low? Too wide or too tight). 4. Mean Reversion Edge: Failed breakouts return to value (ORB mid). Initial breakouts try to escape value (harder to sustain). Critical Insight: [/b> "The best trade is often the one that trapped everyone else." Failed breakouts create asymmetric opportunity because you're trading against [/b> trapped participants rather than with [/b> them. When you see a failed breakout signal, you're seeing real-time evidence that the market rejected directional conviction—that's exploitable. 📐 FIBONACCI EXTENSION SYSTEM Six Extension Levels: [/b> Extensions project how far price will travel after ORB breakout. Based on Fibonacci ratios + empirical market behavior. 1. 1.272x (27.2% Extension): [/b> Formula: [/b> ORB High/Low + (ORB Range × 0.272) Psychology: [/b> Initial probe beyond ORB. Early momentum + trapped shorts (on bull side) covering. Probability of Reach: [/b> ~75-80% after confirmed breakout Trading: [/b> • First resistance/support after breakout • Partial profit target (take 30-50% off) • Watch for rejection here (could signal failure in progress) Why 1.272? [/b> Related to harmonic patterns (1.272 is √1.618). Empirically, markets often stall at 25-30% extension before deciding whether to continue or fail. 2. 1.5x (50% Extension): Formula: [/b> ORB High/Low + (ORB Range × 0.5) Psychology: [/b> Breakout gaining conviction. Requires sustained buying/selling (not just momentum spike). Probability of Reach: [/b> ~60-65% after confirmed breakout Trading: [/b> • Major partial profit (take 50-70% off) • Move stops to breakeven • Trail remaining position Why 1.5x? [/b> Classic halfway point to 2.0x. Markets often consolidate here before final push. If day type is "Normal," this is likely the high/low for the day. 3. 1.618x (Golden Ratio Extension): [/b> Formula: [/b> ORB High/Low + (ORB Range × 0.618) Psychology: [/b> Strong directional day. Institutional conviction + retail FOMO. Probability of Reach: [/b> ~45-50% after confirmed breakout Trading: [/b> • Final partial profit (close 80-90%) • Trail remainder with wide stop (allow breathing room) Why 1.618? [/b> Fibonacci golden ratio. Appears consistently in market geometry. When price reaches 1.618x extension, move is "mature" and reversal risk increases. 4. 2.0x (100% Extension): [/b> Formula: ORB High/Low + (ORB Range × 1.0) Psychology: [/b> Trend day confirmed. Opening range completely duplicated. Probability of Reach: [/b> ~30-35% after confirmed breakout Trading: Why 2.0x? [/b> Psychological level—range doubled. Also corresponds to typical daily ATR in many instruments (opening range ~ 0.5 ATR, daily range ~ 1.0 ATR). 5. 2.618x (Super Extension): Formula: [/b> ORB High/Low + (ORB Range × 1.618) Psychology: [/b> Parabolic move. News-driven or squeeze. Probability of Reach: [/b> ~10-15% after confirmed breakout [b>Trading: Why 2.618? [/b> Fibonacci ratio (1.618²). Rare to reach—when it does, move is extreme. Often precedes multi-day consolidation or reversal. 6. 3.0x (Extreme Extension): [/b> Formula: [/b> ORB High/Low + (ORB Range × 2.0) Psychology: [/b> Market melt-up/crash. Only in extreme events. [b>Probability of Reach: [/b> <5% after confirmed breakout Trading: [/b> • Close immediately if reached • These are outlier events (black swans, flash crashes, squeeze-outs) • Holding for more is greed—take windfall profit Why 3.0x? [/b> Triple opening range. So rare it's statistical noise. When it happens, it's headline news. Visual Example: ES futures, ORB 5842-5850 (8 point range), Bullish breakout: • ORB High : 5850.00 (entry zone) • 1.272x : 5850 + 2.18 = 5852.18 (first resistance) • 1.5x : 5850 + 4.00 = 5854.00 (major target) • 1.618x : 5850 + 4.94 = 5854.94 (strong target) • 2.0x : 5850 + 8.00 = 5858.00 (trend day) • 2.618x : 5850 + 12.94 = 5862.94 (extreme) • 3.0x : 5850 + 16.00 = 5866.00 (parabolic) Profit-Taking Strategy: Optimal scaling out at extensions: • Breakout entry at 5850.50 • 30% off at 1.272x (5852.18) → +1.68 points • 40% off at 1.5x (5854.00) → +3.50 points • 20% off at 1.618x (5854.94) → +4.44 points • 10% off at 2.0x (5858.00) → +7.50 points [b>Average Exit: Conclusion: [/b> Scaling out at extensions produces 40% higher expectancy than holding for home runs. 📊 GAP ANALYSIS & FILL PSYCHOLOGY [b>Gap Definition: [/b> Price discontinuity between previous close and current open: • Gap Up : Open > Previous Close + noise threshold (0.1 ATR) • Gap Down : Open < Previous Close - noise threshold Why Gaps Matter: [/b> Gaps represent unfilled orders [/b>. When market gaps up, all limit buy orders between yesterday's close and today's open are never filled. Those buyers are "left behind." Psychology: they wait for price to return ("fill the gap") so they can enter. This creates magnetic pull [/b> toward gap level. Gap Fill Statistics (Empirical): [/b> • Gaps <0.5% [/b>: 85-90% fill within same day • Gaps 0.5-1.0% [/b>: 70-75% fill within same day, 90%+ within week • Gaps >1.0% [/b>: 50-60% fill within same day (major news often prevents fill) Gap Fill Strategy: [/b> Setup 1: Gap-and-Go Gap opens, extends away from gap (doesn't fill). • ORB confirms direction away from gap • Trade WITH ORB breakout direction • Expectation: Gap won't fill today (momentum too strong) Setup 2: Gap-Fill Fade Gap opens, but fails to extend. Price drifts back toward gap. • ORB breakout TOWARD gap (not away) • Trade toward gap fill level • Target: Previous close (gap fill complete) Setup 3: Gap-Fill Rejection Gap fills (touches previous close) then rejects. • ORB breakout AWAY from gap after fill • Trade away from gap direction • Thesis: Gap filled (orders executed), now resume original direction [b>Example: Scenario A (Gap-and-Go): • ORB breaks upward to $454 (away from gap) • Trade: LONG breakout, expect continued rally • Gap becomes support ($452) Scenario B (Gap-Fill): • ORB breaks downward through $452.50 (toward gap) • Trade: SHORT toward gap fill at $450.00 • Target: $450.00 (gap filled), close position Scenario C (Gap-Fill Rejection): • Price drifts to $450.00 (gap filled) early in session • ORB establishes $450-$451 after gap fill • ORB breaks upward to $451.50 • Trade: LONG breakout (gap is filled, now resume rally) ORB Fusion Integration: [/b> Dashboard shows: • Gap type (Up/Down/None) • Gap size (percentage) • Gap fill status (Filled ✓ / Open) This informs setup confidence: • ORB breakout AWAY from unfilled gap: +10% confidence (gap becomes support/resistance) • ORB breakout TOWARD unfilled gap: -10% confidence (gap fill may override ORB) [b>📈 VWAP & INSTITUTIONAL BIAS [/b> [b>Volume-Weighted Average Price (VWAP): [/b> Average price weighted by volume at each price level. Represents true "average" cost for the day. [b>Calculation: Institutional Benchmark [/b>: Institutions (mutual funds, pension funds) use VWAP as performance benchmark. If they buy above VWAP, they underperformed; below VWAP, they outperformed. 2. [b>Algorithmic Target [/b>: Many algos are programmed to buy below VWAP and sell above VWAP to achieve "fair" execution. 3. [b>Support/Resistance [/b>: VWAP acts as dynamic support (price above) or resistance (price below). [b>VWAP Bands (Standard Deviations): [/b> • [b>1σ Band [/b>: VWAP ± 1 standard deviation - Contains ~68% of volume - Normal trading range - Bounces common • [b>2σ Band [/b>: VWAP ± 2 standard deviations - Contains ~95% of volume - Extreme extension - Mean reversion likely ORB + VWAP Confluence: [/b> Highest-probability setups occur when ORB and VWAP align: Bullish Confluence: [/b> • ORB breakout upward (bullish signal) • Price above VWAP (institutional buying) • Confidence boost: +15% Bearish Confluence: [/b> • ORB breakout downward (bearish signal) • Price below VWAP (institutional selling) • Confidence boost: +15% [b>Divergence Warning: • ORB breakout upward BUT price below VWAP • Conflict: Breakout says "buy," VWAP says "sell" • Confidence penalty: -10% • Interpretation: Retail buying but institutions not participating (lower quality breakout) 📊 MOMENTUM CONTEXT SYSTEM [b>Innovation: Candle Coloring by Position Rather than fixed support/resistance lines, ORB Fusion colors candles based on their [b>relationship to ORB : [b>Three Zones: [/b> 1. Inside ORB (Blue Boxes): [/b> [b>Calculation: • Darker blue: Near extremes of ORB (potential breakout imminent) • Lighter blue: Near ORB mid (consolidation) [b>Trading: [/b> Coiled spring—await breakout. [b>2. Above ORB (Green Boxes): [b>Calculation: 3. Below ORB (Red Boxes): Mirror of above ORB logic. [b>Special Contexts: [/b> [b>Breakout Bar (Darkest Green/Red): [/b> The specific bar where breakout occurs gets maximum color intensity regardless of distance. This highlights the pivotal moment. [b>Failed Breakout Bar (Orange/Warning): [/b> When failed breakout is confirmed, that bar gets orange/warning color. Visual alert: "reversal opportunity here." [b>Near Extension (Cyan/Magenta Tint): [/b> When price is within 0.5 ATR of an extension level, candle gets tinted cyan (bull) or magenta (bear). Indicates "target approaching—prepare to take profit." [b>Why Visual Context? [/b> Traditional indicators show lines. ORB Fusion shows [b>context-aware momentum [/b>. Glance at chart: • Lots of blue? Consolidation day (fade extremes). • Progressive green? Trend day (follow). • Green then orange? Failed breakout (reversal setup). This visual language communicates market state instantly—no interpretation needed. 🎯 TRADE SETUP GENERATION & GRADING [/b> [b>Algorithmic Setup Detection: [/b> ORB Fusion continuously evaluates market state and generates current best trade setup with: • Action (LONG / SHORT / FADE HIGH / FADE LOW / WAIT) • Entry price • Stop loss • Three targets • Risk:Reward ratio • Confidence score (0-100) • Grade (A+ to D) [b>Setup Types: [/b> [b>1. ORB LONG (Bullish Breakout): [/b> [b>Trigger: [/b> • Bullish ORB breakout confirmed • Not failed [b>Parameters: • Entry: Current close • Stop: ORB mid (protects against failure) • T1: ORB High + 0.5x range (1.5x extension) • T2: ORB High + 1.0x range (2.0x extension) • T3: ORB High + 1.618x range (2.618x extension) [b>Confidence Scoring: [b>Trigger: [/b> • Bearish breakout occurred • Failed (returned inside ORB) [b>Parameters: [/b> • Entry: Close when failure confirmed • Stop: Extreme low since breakout + 0.10 ATR • T1: ORB Low + 0.5x range • T2: ORB Low + 1.0x range (ORB mid) • T3: ORB Low + 1.5x range [b>Confidence Scoring: [b>Trigger: • Inside ORB • Close > ORB mid (near high) [b>Parameters: [/b> • Entry: ORB High (limit order) • Stop: ORB High + 0.2x range • T1: ORB Mid • T2: ORB Low [b>Confidence Scoring: [/b> Base: 40 points (lower base—range fading is lower probability than breakout/reversal) [b>Use Case: [/b> Rotation days. Not recommended on normal/trend days. [b>6. FADE LOW (Range Trade): Mirror of FADE HIGH. [b>7. WAIT: [b>Trigger: [/b> • ORB not complete yet OR • No clear setup (price in no-man's-land) [b>Action: [/b> Observe, don't trade. [b>Confidence: [/b> 0 points [b>Grading System: ``` Confidence → Grade 85-100 → A+ 75-84 → A 65-74 → B+ 55-64 → B 45-54 → C 0-44 → D ``` [b>Grade Interpretation: [/b> • [b>A+ / A: High probability setup. Take these trades. • [b>B+ / B [/b>: Decent setup. Trade if fits system rules. • [b>C [/b>: Marginal setup. Only if very experienced. • [b>D [/b>: Poor setup or no setup. Don't trade. [b>Example Scenario: [/b> ES futures: • ORB: 5842-5850 (8 point range) • Bullish breakout to 5851 confirmed • Volume: 2.0x average (confirmed) • VWAP: 5845 (price above VWAP ✓) • Day type: Developing (too early, no bonus) • Gap: None [b>Setup: [/b> • Action: LONG • Entry: 5851 • Stop: 5846 (ORB mid, -5 point risk) • T1: 5854 (+3 points, 1:0.6 R:R) • T2: 5858 (+7 points, 1:1.4 R:R) • T3: 5862.94 (+11.94 points, 1:2.4 R:R) [b>Confidence: LONG with 55% confidence. Interpretation: Solid setup, not perfect. Trade it if your system allows B-grade signals. [b>📊 STATISTICS TRACKING & PERFORMANCE ANALYSIS [/b> [b>Real-Time Performance Metrics: [/b> ORB Fusion tracks comprehensive statistics over user-defined lookback (default 50 days): [b>Breakout Performance: [/b> • [b>Bull Breakouts: [/b> Total count, wins, losses, win rate • [b>Bear Breakouts: [/b> Total count, wins, losses, win rate [b>Win Definition: [/b> Breakout reaches ≥1.0x extension (doubles the opening range) before end of day. [b>Example: [/b> • ORB: 5842-5850 (8 points) • Bull breakout at 5851 • Reaches 5858 (1.0x extension) by close • Result: WIN [b>Failed Breakout Performance: [/b> • [b>Total Failed Breakouts [/b>: Count of breakouts that failed • [b>Reversal Wins [/b>: Count where reversal trade reached target • [b>Failed Reversal Win Rate [/b>: Wins / Total Failed [b>Win Definition for Reversals: [/b> • Failed bull → reversal short reaches ORB mid • Failed bear → reversal long reaches ORB mid [b>Extension Tracking: [/b> • [b>Average Extension Reached [/b>: Mean of maximum extension achieved across all breakout days • [b>Max Extension Overall [/b>: Largest extension ever achieved in lookback period [b>Example: 🎨 THREE DISPLAY MODES [b>Design Philosophy: [/b> Not all traders need all features. Beginners want simplicity. Professionals want everything. ORB Fusion adapts. [b>SIMPLE MODE: [/b> [b>Shows: [/b> • Primary ORB levels (High, Mid, Low) • ORB box • Breakout signals (triangles) • Failed breakout signals (crosses) • Basic dashboard (ORB status, breakout status, setup) • VWAP [b>Hides: [/b> • Session ORBs (Asian, London, NY) • IB levels and extensions • ORB extensions beyond basic levels • Gap analysis visuals • Statistics dashboard • Momentum candle coloring • Narrative dashboard [b>Use Case: [/b> • Traders who want clean chart • Focus on core ORB concept only • Mobile trading (less screen space) [b>STANDARD MODE: [b>Shows Everything in Simple Plus: [/b> • Session ORBs (Asian, London, NY) • IB levels (high, low, mid) • IB extensions • ORB extensions (1.272x, 1.5x, 1.618x, 2.0x) • Gap analysis and fill targets • VWAP bands (1σ and 2σ) • Momentum candle coloring • Context section in dashboard • Narrative dashboard [b>Hides: [/b> • Advanced extensions (2.618x, 3.0x) • Detailed statistics dashboard [b>Use Case: [/b> • Most traders • Balance between information and clarity • Covers 90% of use cases [b>ADVANCED MODE: [b>Shows Everything: • All session ORBs • All IB levels and extensions • All ORB extensions (including 2.618x and 3.0x) • Full gap analysis • VWAP with both 1σ and 2σ bands • Momentum candle coloring • Complete statistics dashboard • Narrative dashboard • All context metrics [b>Use Case: [/b> • Professional traders • System developers • Those who want maximum information density [b>Switching Modes: [/b> Single dropdown input: "Display Mode" → Simple / Standard / Advanced Entire indicator adapts instantly. No need to toggle 20 individual settings. 📖 NARRATIVE DASHBOARD [b>Innovation: Plain-English Market State [/b> Most indicators show data. ORB Fusion explains what the data [b>means [/b>. [b>Narrative Components: [/b> [b>1. Phase: [/b> • "📍 Building ORB..." (during ORB session) • "📊 Trading Phase" (after ORB complete) • "⏳ Pre-Market" (before ORB session) [b>2. Status (Current Observation): [/b> • "⚠️ Failed breakout - reversal likely" • "🚀 Bullish momentum in play" • "📉 Bearish momentum in play" • "⚖️ Consolidating in range" • "👀 Monitoring for setup" [b>3. Next Level: Tells you what to watch for: • "🎯 1.5x @ 5854.00" (next extension target) • "Watch ORB levels" (inside range, await breakout) [b>4. Setup: [/b> Current trade setup + grade: • "LONG " (bullish breakout, A-grade) • "🔥 SHORT REVERSAL " (failed bull breakout, A+-grade) • "WAIT " (no setup) [b>5. Reason: [/b> Why this setup exists: • "ORB Bullish Breakout" • "Failed Bear Breakout - High Probability Reversal" • "Range Fade - Near High" [b>6. Tip (Market Insight): Contextual advice: • "🔥 TREND DAY - Trail stops" (day type is trending) • "🔄 ROTATION - Fade extremes" (day type is rotating) • "📊 Gap unfilled - magnet level" (gap creates target) • "📈 Normal conditions" (no special context) [b>Example Narrative: ``` 📖 ORB Narrative ━━━━━━━━━━━━━━━━ Phase | 📊 Trading Phase Status | 🚀 Bullish momentum in play Next | 🎯 1.5x @ 5854.00 📈 Setup | LONG Reason | ORB Bullish Breakout 💡 Tip | 🔥 TREND DAY - Trail stops ``` [b>Glance Interpretation: [/b> "We're in trading phase. Bullish breakout happened (momentum in play). Next target is 1.5x extension at 5854. Current setup is LONG with A-grade. It's a trend day, so trail stops (don't take early profits)." Complete market state communicated in 6 lines. No interpretation needed. [b>Why This Matters: Beginner traders struggle with "So what?" question. Indicators show lines and signals, but what does it mean [/b>? Narrative dashboard bridges this gap. Professional traders benefit too—rapid context assessment during fast-moving markets. No time to analyze; glance at narrative, get action plan. 🔔 INTELLIGENT ALERT SYSTEM [b>Four Alert Types: [/b> [b>1. Breakout Alert: [/b> [b>Trigger: [/b> ORB breakout confirmed (bull or bear) [b>Message: [/b> ``` 🚀 ORB BULLISH BREAKOUT Price: 5851.00 Volume Confirmed Grade: A ``` [b>Frequency: [/b> Once per bar (prevents spam) [b>2. Failed Breakout Alert: [/b> [b>Trigger: [/b> Breakout fails, reversal setup generated [b>Message: [/b> ``` 🔥 FAILED BULLISH BREAKOUT! HIGH PROBABILITY SHORT REVERSAL Entry: 5848.00 Stop: 5854.00 T1: 5846.00 T2: 5842.00 Historical Win Rate: 73% ``` [b>Why Comprehensive? [/b> Failed breakout alerts include complete trade plan. You can execute immediately from alert—no need to check chart. [b>3. Extension Alert: [b>Trigger: [/b> Price reaches extension level for first time [b>Message: [/b> ``` 🎯 Bull Extension 1.5x reached @ 5854.00 ``` [b>Use: [/b> Profit-taking reminder. When extension hit, consider scaling out. [b>4. IB Break Alert: [/b> [b>Trigger: [/b> Price breaks above IB high or below IB low [b>Message: [/b> ``` 📊 IB HIGH BROKEN - Potential Trend Day ``` [b>Use: [/b> Day type classification. IB break suggests trend day developing—adjust strategy to trend-following mode. [b>Alert Management: [/b> Each alert type can be enabled/disabled independently. Prevents notification overload. [b>Cooldown Logic: [/b> Alerts won't fire if same alert type triggered within last bar. Prevents: • "Breakout" alert every tick during choppy breakout • Multiple "extension" alerts if price oscillates at level Ensures: One clean alert per event. ⚙️ KEY PARAMETERS EXPLAINED [b>Opening Range Settings: [/b> • [b>ORB Timeframe [/b> (5/15/30/60 min): Duration of opening range window - 30 min recommended for most traders • [b>Use RTH Only [/b> (ON/OFF): Only trade during regular trading hours - ON recommended (avoids thin overnight markets) • [b>Use LTF Precision [/b> (ON/OFF): Sample 1-minute bars for accuracy - ON recommended (critical for charts >1 minute) • [b>Precision TF [/b> (1/5 min): Timeframe for LTF sampling - 1 min recommended (most accurate) [b>Session ORBs: [/b> • [b>Show Asian/London/NY ORB [/b> (ON/OFF): Display multi-session ranges - OFF in Simple mode - ON in Standard/Advanced if trading 24hr markets • [b>Session Windows [/b>: Time ranges for each session ORB - Defaults align with major session opens [b>Initial Balance: [/b> • [b>Show IB [/b> (ON/OFF): Display Initial Balance levels - ON recommended for day type classification • [b>IB Session Window [/b> (0930-1030): First hour of trading - Default is standard for US equities • [b>Show IB Extensions [/b> (ON/OFF): Project IB extension targets - ON recommended (identifies trend days) • [b>IB Extensions 1-4 [/b> (0.5x, 1.0x, 1.5x, 2.0x): Extension multipliers - Defaults are Market Profile standard [b>ORB Extensions: [/b> • [b>Show Extensions [/b> (ON/OFF): Project ORB extension targets - ON recommended (defines profit targets) • [b>Enable Individual Extensions [/b> (1.272x, 1.5x, 1.618x, 2.0x, 2.618x, 3.0x) - Enable 1.272x, 1.5x, 1.618x, 2.0x minimum - Disable 2.618x and 3.0x unless trading very volatile instruments [b>Breakout Detection: • [b>Confirmation Method [/b> (Close/Wick/Body): - Close recommended (best balance) - Wick for scalping - Body for conservative • [b>Require Volume Confirmation [/b> (ON/OFF): - ON recommended (increases reliability) • [b>Volume Multiplier [/b> (1.0-3.0): - 1.5x recommended - Lower for thin instruments - Higher for heavy volume instruments [b>Failed Breakout System: [/b> • [b>Enable Failed Breakouts [/b> (ON/OFF): - ON strongly recommended (highest edge) • [b>Bars to Confirm Failure [/b> (2-10): - 3 bars recommended - 2 for aggressive (more signals, more false failures) - 5+ for conservative (fewer signals, higher quality) • [b>Failure Buffer [/b> (0.0-0.5 ATR): - 0.1 ATR recommended - Filters noise during consolidation near ORB level • [b>Show Reversal Targets [/b> (ON/OFF): - ON recommended (visualizes trade plan) • [b>Reversal Target Mults [/b> (0.5x, 1.0x, 1.5x): - Defaults are tested values - Adjust based on average daily range [b>Gap Analysis: • [b>Show Gap Analysis [/b> (ON/OFF): - ON if trading instruments that gap frequently - OFF for 24hr markets (forex, crypto—no gaps) • [b>Gap Fill Target [/b> (ON/OFF): - ON to visualize previous close (gap fill level) [b>VWAP: • [b>Show VWAP [/b> (ON/OFF): - ON recommended (key institutional level) • [b>Show VWAP Bands [/b> (ON/OFF): - ON in Standard/Advanced - OFF in Simple • [b>Band Multipliers (1.0σ, 2.0σ): - Defaults are standard - 1σ = normal range, 2σ = extreme [b>Day Type: [/b> • [b>Show Day Type Analysis [/b> (ON/OFF): - ON recommended (critical for strategy adaptation) • [b>Trend Day Threshold [/b> (1.0-2.5 IB mult): - 1.5x recommended - When price extends >1.5x IB, classifies as Trend Day [b>Enhanced Visuals: • [b>Show Momentum Candles [/b> (ON/OFF): - ON for visual context - OFF if chart gets too colorful • [b>Show Gradient Zone Fills [/b> (ON/OFF): - ON for professional look - OFF for minimalist chart • [b>Label Display Mode [/b> (All/Adaptive/Minimal): - Adaptive recommended (shows nearby labels only) - All for information density - Minimal for clean chart • [b>Label Proximity [/b> (1.0-5.0 ATR): - 3.0 ATR recommended - Labels beyond this distance are hidden (Adaptive mode) [b>🎓 PROFESSIONAL USAGE PROTOCOL [/b> [b>Phase 1: Learning the System (Week 1) [/b> [b>Goal: [/b> Understand ORB concepts and dashboard interpretation [b>Setup: [/b> • Display Mode: STANDARD • ORB Timeframe: 30 minutes • Enable ALL features (IB, extensions, failed breakouts, VWAP, gap analysis) • Enable statistics tracking [b>Actions: [/b> • Paper trade ONLY—no real money • Observe ORB formation every day (9:30-10:00 AM ET for US markets) • Note when ORB breakouts occur and if they extend • Note when breakouts fail and reversals happen • Watch day type classification evolve during session • Track statistics—which setups are working? [b>Key Learning: [/b> • How often do breakouts reach 1.5x extension? (typically 50-60% of confirmed breakouts) • How often do breakouts fail? (typically 30-40%) • Which setup grade (A/B/C) actually performs best? (should see A-grade outperforming) • What day type produces best results? (trend days favor breakouts, rotation days favor fades) [b>Phase 2: Parameter Optimization (Week 2) [/b> [b>Goal: [/b> Tune system to your instrument and timeframe [b>ORB Timeframe Selection: • Run 5 days with 15-minute ORB • Run 5 days with 30-minute ORB • Compare: Which captures better breakouts on your instrument? • Typically: 30-minute optimal for most, 15-minute for very liquid (ES, SPY) [b>Volume Confirmation Testing: • Run 5 days WITH volume confirmation • Run 5 days WITHOUT volume confirmation • Compare: Does volume confirmation increase win rate? • If win rate improves by >5%: Keep volume confirmation ON • If no improvement: Turn OFF (avoid missing valid breakouts) [b>Failed Breakout Bars: [b>Goal: [/b> Develop personal trading rules based on system signals [b>Setup Selection Rules: [/b> Define which setups you'll trade: • [b>Conservative: [/b> Only A+ and A grades • [b>Balanced: [/b> A+, A, B+ grades • [b>Aggressive: [/b> All grades B and above Test each approach for 5-10 trades, compare results. [b>Position Sizing by Grade: [/b> Consider risk-weighting by setup quality: • A+ grade: 100% position size • A grade: 75% position size • B+ grade: 50% position size • B grade: 25% position size Example: If max risk is $1000/trade: • A+ setup: Risk $1000 • A setup: Risk $750 • B+ setup: Risk $500 This matches bet sizing to edge. [b>Day Type Adaptation: [/b> Create rules for different day types: Trend Days: • Take ALL breakout signals (A/B/C grades) • Hold for 2.0x extension minimum • Trail stops aggressively (1.0 ATR trail) • DON'T fade—reversals unlikely Rotation Days: • ONLY take failed breakout reversals • Ignore initial breakout signals (likely to fail) • Take profits quickly (0.5x extension) • Focus on fade setups (Fade High/Fade Low) Normal Days: • Take A/A+ breakout signals only • Take ALL failed breakout reversals (high probability) • Target 1.0-1.5x extensions • Partial profit-taking at extensions Time-of-Day Rules: [/b> Breakouts at different times have different probabilities: 10:00-10:30 AM (Early Breakout): • ORB just completed • Fresh breakout • Probability: Moderate (50-55% reach 1.0x) • Strategy: Conservative position sizing 10:30-12:00 PM (Mid-Morning): • Momentum established • Volume still healthy • Probability: High (60-65% reach 1.0x) • Strategy: Standard position sizing 12:00-2:00 PM (Lunch Doldrums): • Volume dries up • Whipsaw risk increases • Probability: Low (40-45% reach 1.0x) • Strategy: Avoid new entries OR reduce size 50% 2:00-4:00 PM (Afternoon Session): • Late-day positioning • EOD squeezes possible • Probability: Moderate-High (55-60%) • Strategy: Watch for IB break—if trending all day, follow [b>Phase 4: Live Micro-Sizing (Month 2) [/b> [b>Goal: [/b> Validate paper trading results with minimal risk [b>Setup: [/b> • 10-20% of intended full position size • Take ONLY A+ and A grade setups • Follow stop loss and targets religiously [b>Execution: [/b> • Execute from alerts OR from dashboard setup box • Entry: Close of signal bar OR next bar market order • Stop: Use exact stop from setup (don't widen) • Targets: Scale out at T1/T2/T3 as indicated [b>Tracking: [/b> • Log every trade: Entry, Exit, Grade, Outcome, Day Type • Calculate: Win rate, Average R-multiple, Max consecutive losses • Compare to paper trading results (should be within 15%) [b>Red Flags: [/b> • Win rate <45%: System not suitable for this instrument/timeframe • Major divergence from paper trading: Execution issues (slippage, late entries, emotional exits) • Max consecutive losses >8: Hitting rough patch OR market regime changed [b>Phase 5: Scaling Up (Months 3-6) [b>Goal: [/b> Gradually increase to full position size [b>Progression: [/b> • Month 3: 25-40% size (if micro-sizing profitable) • Month 4: 40-60% size • Month 5: 60-80% size • Month 6: 80-100% size [b>Milestones Required to Scale Up: [/b> • Minimum 30 trades at current size • Win rate ≥48% • Profit factor ≥1.2 • Max drawdown <20% • Emotional control (no revenge trading, no FOMO) [b>Advanced Techniques: [b>Multi-Timeframe ORB: Assumes first 30-60 minutes establish value. Violation: Market opens after major news, price discovery continues for hours (opening range meaningless). 2. [b>Volume Indicates Conviction: ES, NQ, RTY, SPY, QQQ—high liquidity, clean ORB formation, reliable extensions • [b>Large-Cap Stocks: AAPL, MSFT, TSLA, NVDA (>$5B market cap, >5M daily volume) • [b>Liquid Futures: CL (crude oil), GC (gold), 6E (EUR/USD), ZB (bonds)—24hr markets benefit from session ORBs • [b>Major Forex Pairs: [/b> EUR/USD, GBP/USD, USD/JPY—London/NY session ORBs work well [b>Performs Poorly On: [/b> • [b>Illiquid Stocks: <$1M daily volume, wide spreads, gappy price action • [b>Penny Stocks: [/b> Manipulated, pump-and-dump, no real price discovery • [b>Low-Volume ETFs: Exotic sector ETFs, leveraged products with thin volume • [b>Crypto on Sketchy Exchanges: Wash trading, spoofing invalidates volume analysis • [b>Earnings Days: [/b> ORB completes before earnings release, then completely resets (useless) • Binary Event Days: FDA approvals, court rulings—discontinuous price action [b>Known Weaknesses: [/b> • [b>Slow Starts: ORB doesn't complete until 10:00 AM (30-min ORB). Early morning traders have no signals for 30 minutes. Consider using 15-minute ORB if this is problematic. • [b>Failure Detection Lag: [/b> Failed breakout requires 3+ bars to confirm. By the time system signals reversal, price may have already moved significantly back inside range. Manual traders watching in real-time can enter earlier. • [b>Extension Overshoot: [/b> System projects extensions mathematically (1.5x, 2.0x, etc.). Actual moves may stop short (1.3x) or overshoot (2.2x). Extensions are targets, not magnets. • [b>Day Type Misclassification: [/b> Early in session, day type is "Developing." By the time it's classified definitively (often 11:00 AM+), half the day is over. Strategy adjustments happen late. • [b>Gap Assumptions: [/b> System assumes gaps want to fill. Strong trend days never fill gaps (gap becomes support/resistance forever). Blindly trading toward gaps can backfire on trend days. • [b>Volume Data Quality: Forex doesn't have centralized volume (uses tick volume as proxy—less reliable). Crypto volume is often fake (wash trading). Volume confirmation less effective on these instruments. • [b>Multi-Session Complexity: [/b> When using Asian/London/NY ORBs simultaneously, chart becomes cluttered. Requires discipline to focus on relevant session for current time. [b>Risk Factors: [/b> • [b>Opening Gaps: Large gaps (>2%) can create distorted ORBs. Opening range might be unusually wide or narrow, making extensions unreliable. • [b>Low Volatility Environments:[/b> When VIX <12, opening ranges can be tiny (0.2-0.3%). Extensions are equally tiny. Profit targets don't justify commission/slippage. • [b>High Volatility Environments:[/b> When VIX >30, opening ranges are huge (2-3%+). Extensions project unrealistic targets. Failed breakouts happen faster (volatility whipsaw). • [b>Algorithm Dominance:[/b> In heavily algorithmic markets (ES during overnight session), ORB levels can be manipulated—algos pin price to ORB high/low intentionally. Breakouts become stop-runs rather than genuine directional moves. [b>⚠️ RISK DISCLOSURE[/b> Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Opening Range Breakout strategies, while based on sound market structure principles, do not guarantee profits and can result in significant losses. The ORB Fusion indicator implements professional trading concepts including Opening Range theory, Market Profile Initial Balance analysis, Fibonacci extensions, and failed breakout reversal logic. These methodologies have theoretical foundations but past performance—whether backtested or live—is not indicative of future results. Opening Range theory assumes the first 30-60 minutes of trading establish a meaningful value area and that breakouts from this range signal directional conviction. This assumption may not hold during: • Major news events (FOMC, NFP, earnings surprises) • Market structure changes (circuit breakers, trading halts) • Low liquidity periods (holidays, early closures) • Algorithmic manipulation or spoofing Failed breakout detection relies on patterns of trapped participant behavior. While historically these patterns have shown statistical edges, market conditions change. Institutional algorithms, changing market structure, or regime shifts can reduce or eliminate edges that existed historically. Initial Balance classification (trend day vs rotation day vs normal day) is a heuristic framework, not a deterministic prediction. Day type can change mid-session. Early classification may prove incorrect as the day develops. Extension projections (1.272x, 1.5x, 1.618x, 2.0x, etc.) are probabilistic targets derived from Fibonacci ratios and empirical market behavior. They are not "support and resistance levels" that price must reach or respect. Markets can stop short of extensions, overshoot them, or ignore them entirely. Volume confirmation assumes high volume indicates institutional participation and conviction. In algorithmic markets, volume can be artificially high (HFT activity) or artificially low (dark pools, internalization). Volume is a proxy, not a guarantee of conviction. LTF precision sampling improves ORB accuracy by using 1-minute bars but introduces additional data dependencies. If 1-minute data is unavailable, inaccurate, or delayed, ORB calculations will be incorrect. The grading system (A+/A/B+/B/C/D) and confidence scores aggregate multiple factors (volume, VWAP, day type, IB expansion, gap context) into a single assessment. This is a mechanical calculation, not artificial intelligence. The system cannot adapt to unprecedented market conditions or events outside its programmed logic. Real trading involves slippage, commissions, latency, partial fills, and rejected orders not present in indicator calculations. ORB Fusion generates signals at bar close; actual fills occur with delay. Opening range forms during highest volatility (first 30 minutes)—spreads widen, slippage increases. Execution quality significantly impacts realized results. Statistics tracking (win rates, extension levels reached, day type distribution) is based on historical bars in your lookback window. If lookback is small (<50 bars) or market regime changed, statistics may not represent future probabilities. Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively (100+ trades minimum) before risking capital. Start with micro position sizing (5-10% of intended size) for 50+ trades to validate execution quality matches expectations. Never risk more than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every single trade without exception. Understand that most retail traders lose money—sophisticated indicators do not change this fundamental reality. They systematize analysis but cannot eliminate risk. The developer makes no warranties regarding profitability, suitability, accuracy, reliability, or fitness for any purpose. Users assume full responsibility for all trading decisions, parameter selections, risk management, and outcomes. By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses. [b>═══════════════════════════════════════════════════════════════════════════════[/b> [b>CLOSING STATEMENT[/b> [b>═══════════════════════════════════════════════════════════════════════════════[/b> Opening Range Breakout is not a trick. It's a framework. The first 30-60 minutes reveal where participants believe value lies. Breakouts signal directional conviction. Failures signal trapped participants. Extensions define profit targets. Day types dictate strategy. Failed breakouts create the highest-probability reversals. ORB Fusion doesn't predict the future—it identifies [b>structure[/b>, detects [b>breakouts[/b>, recognizes [b>failures[/b>, and generates [b>probabilistic trade plans[/b> with defined risk and reward. The edge is not in the opening range itself. The edge is in recognizing when the market respects structure (follow breakouts) versus when it violates structure (fade breakouts). The edge is in detecting failures faster than discretionary traders. The edge is in systematic classification that prevents catastrophic errors—like fading a trend day or holding through rotation. Most indicators draw lines. ORB Fusion implements a complete institutional trading methodology: Opening Range theory, Market Profile classification, failed breakout intelligence, Fibonacci projections, volume confirmation, gap psychology, and real-time performance tracking. Whether you're a beginner learning market structure or a professional seeking systematic ORB implementation, this system provides the framework. "The market's first word is its opening range. Everything after is commentary." — ORB Fusion
Pine Script® indicator
by DskyzInvestments
10
Trend Break Targets [MarkitTick]Trend Break Targets Trend Break Targets is a technical analysis tool designed to assist traders in identifying trendline breakouts and projecting potential price targets based on market geometry. Unlike fully automated indicators that guess trendlines, this tool provides you with precise control by allowing you to manually Pivot Point the trendline to specific points in time, while automating the complex math of target projection and structure mapping. Theoretical Basis & Concepts This indicator is grounded in classic technical analysis principles found in foundational trading literature. It automates the following methodology: Drawing a trend line between two key points to represent dynamic support or resistance. Identifying a breakout when the price closes above or below this line, potentially signaling a change in trend. Calculating a price target by measuring the vertical distance between the breakout line and the last high/low (pivot), then projecting that same distance in the direction of the breakout. This concept is based on methods and "Measured Move" theories explained in classic books such as "Technical Analysis of Stock Trends" by Edwards & Magee, "Technical Analysis of the Financial Markets" by John Murphy, and in Thomas Bulkowski's Price Pattern Studies. How It Works Pivot Pointed Trendline Construction The script draws a trendline between two user-defined points in time (Start Date and End Date). It calculates the slope between these points and extends the line infinitely to the right, allowing you to define the exact structure (e.g., a resistance trendline on a wedge). Breakout Detection The script monitors the "Price Source" (High, Low, or Close) relative to the extended trendline. A Bullish Breakout (BC) occurs when the Close crosses above a bearish trendline. A Bearish Breakout (BC) occurs when the Close crosses below a bullish trendline. Dynamic Target Projection (The Math) Upon a confirmed breakout, the script automatically calculates three distinct targets by identifying the most significant "Swing Point" (Pivot) prior to the breakout. Distance (D): The vertical distance between the Trendline and the Pivot Price at the specific bar where the pivot occurred. Target 1 (T1): The Breakout Price +/- (Distance × 1.0). This represents a classic 1:1 measured move. Target 2 (T2): The Breakout Price +/- (Distance × 1.618). Based on the Golden Ratio extension. Target 3 (T3): The Breakout Price +/- (Distance × 2.618). Market Structure (CHOCH) The script includes an optional Change of Character (CHOCH) module. This runs independently of the trendline logic, identifying local Swing Highs and Swing Lows based on the "Swing Detection Length." It plots dashed lines and labels to visualize immediate shifts in market structure. How to Use This Tool This is an interactive tool that requires user input to define the setup. Identify a Setup: Locate a clear trend, wedge, or flag pattern on your chart. Set Pivot Points: Go to the Indicator Settings. Input the exact Start Date and End Date corresponding to the two main touches of your trendline. Monitor for Breakout: The script will extend the line. Wait for a "BC" label to appear. Trade Management: Once "BC" prints, the T1, T2, and T3 lines will instantly render. These can be used as potential take-profit zones or areas to tighten stop-losses. Settings & Configuration Indicator Settings Start/End Date: The timestamp Pivot Points for your trendline. Price Source: Determines what price (High or Low) Pivot Points the line and triggers the breakout. Pivot Left/Right: Adjusts the sensitivity for finding the "Pivot Before Break" used for target calculations. Extend Target Line: How far forward the target lines are drawn. Visual Style Colors: Fully customizable colors for the Trendline, Breakout Labels, and each Target level (T1, T2, T3). Gold Bullish Reversal This analysis dissects a confirmed bullish reversal on Gold using a custom Trend Break system. The setup identifies a transition from a bearish corrective phase to bullish momentum, validated by a structural break and a geometric target projection. Trend Identification (The Pivot Points) The descending white trendline serves as the primary dynamic resistance, defining the bearish correction. Pivot Points: The line is drawn connecting two significant swing highs, marked by Label 1 and Label 2. Logic: These points represent the "lower highs" characteristic of the previous downtrend. As long as price remained below this trajectory, the bearish bias was intact. The Trigger: Breakout & Confirmation The transition occurs at the candle marked BC (Breakout Candle). Breakout Criteria: The indicator logic dictates that a signal is only valid when the bar closes above the trendline. This filters out intraday wicks and ensures genuine buyer commitment. CHOCH Confluence: Immediately following the breakout, a CHOCH (Change of Character) label appears. This signals a shift in market structure, indicating that the internal lower-high/lower-low sequence has been violated, adding probability to the reversal. Target Projection: The Measured Move The vertical green lines (T1, T2) represent profit objectives derived from the depth of the prior move. The logic calculates the distance between the breakout line and the lowest pivot prior to the break. T1 (Standard Target): This is a 1:1 projection of the pre-breakout volatility. We see price action initially stalling near this level, confirming it as a zone of interest. T2 (Golden Ratio Extension): The second target is calculated as the initial distance multiplied by 1.618 (Fibonacci Golden Ratio). The chart shows the price rallying aggressively through T1 to tap the T2 zone, often considered an exhaustion or major take-profit level in harmonic extensions. Conclusion Gold has successfully invalidated the 4-hour bearish trendline. The confluence of a confirmed close above resistance (BC) and a structural shift (CHOCH) provided a high-probability long setup. The price has now fulfilled the T2 (1.618) extension, suggesting traders should watch for consolidation or a reaction at this key Fibonacci resistance level. Bearish Trendline Breakdown The image displays a Bearish Trendline Breakdown on the Gold (XAUUSD) 4-hour chart. The indicator is actually functioning in "Low" mode here (connecting swing lows to form support), which triggers the bearish logic found in the code. Here is the step-by-step breakdown: The Setup: Pivot Points & Trendline Visual: The Blue Labels "1" and "2" connected by a white diagonal line. Code Logic: These are the user-defined start and end points. Pivot Point 1 (startDate): The starting pivot of the trendline. Pivot Point 2 (endDate): The ending pivot. Trendline: The code draws a line between these two points and extends it to the right (extend.right). In this specific image, the line acts as a Support Trendline. The Trigger: Break Candle (BC) Visual: The Red Label "BC" appearing just below the white trendline. Code Logic: This is the execution signal. The code detects a "Down Break" (dnBreak) because the Price Source was likely set to "Low" and the candle's Close was lower than the Trendline Price at that specific bar (close < currLinePrice). This confirms the support level has been breached. The Projection: Targets (T1 & T2) Visual: The Green Labels "T1" and "T2" with dotted horizontal lines projected downward. Code Logic: These are profit targets based on a "Measured Move." Pivot Calculation: The script looks back for a recent "Pivot High" (the peak before the crash) to calculate the volatility/distance (dist) between that peak and the trendline. T1 (Conservative): The price is projected downward by 1x that distance (currLinePrice - dist). T2 (Extended): The price is projected downward by 1.618x that distance (Golden Ratio extension). Market Context: CHOCH Visual: The small Red/Orange "CHOCH" labels appearing above the price action. Code Logic: This is a secondary confirmation system running independently of the trendline. It detects a Change of Character (structural shift). The red labels indicate a "Bearish CHOCH," meaning the price broke below a significant prior swing low (last_swing_low). This supports the bearish bias of the trendline break. Disclaimer This tool is for educational and technical analysis purposes only. Breakouts can fail (fake-outs), and past geometric patterns do not guarantee future price action. Always manage risk and use this tool in conjunction with other forms of analysis.
Pine Script® indicator
by MarkitTick
2
Équilibre du Sentiment – Multi-Périodes (v6) English A unique and advanced sentiment indicator based on the harmonic mean of highs and lows over nested rolling windows. How it works: The neutral sentiment point is reached when positive sentiment equals negative sentiment, which corresponds to the situation where the percentage between the price and the minimum is equal to the percentage between the maximum and the price. For each chosen period N, the script calculates N different "neutral feeling" values: - One using the last 1 bar - One using the last 2 bars - … - One using the last N bars It then extracts the exact median of these N values using a sorted insertion method (no approximation). This produces an extremely smooth, non-repainting equilibrium line that represents the true "central sentiment" of the market over the selected lookback. Features: - Up to 3 independent periods (365, 52, 26 by default – fully customizable) - Optional background coloring (green/red) when price is above/below the main curve - Clean labels on the last bar showing the current value for each active period - Zero repainting – fully compatible with strategies and alerts - Highly responsive even with very long periods (up to 3500 bars) Great for: - Identifying long-term fair value / equilibrium zones - Building mean-reversion or breakout systems Pure Pine Script® v6 – no external libraries, no security calls, no repainting-free.
Pine Script® indicator
by stochastoche
Fibonacci Degree System This Pine Script creates a sophisticated technical analysis tool that combines Fibonacci retracements with a degree-based cycle system. Here's a comprehensive breakdown: Core Concept The indicator maps price movements onto a 360-degree circular framework, treating market cycles like geometric angles. It creates a visual "mesh" where Fibonacci ratios intersect in both price (horizontal) and time (vertical) dimensions. How It Works 1. Finding Reference Points The script looks back over a specified period (default 100 bars) to identify: Highest High: The peak price point Lowest Low: The trough price point Time Locations: Exactly which bars these extremes occurred on These two points form the boundaries of your analysis window. 2. Creating the Fibonacci Grid Horizontal Lines (Price Levels): The script divides the price range between high and low into seven key Fibonacci ratios: 0% (Low) - Bottom boundary in red 23.6% - Minor retracement in orange 38.2% - Shallow retracement in yellow 50% - Midpoint in lime green 61.8% - Golden ratio in aqua (most significant) 78.6% - Deep retracement in blue 100% (High) - Top boundary in purple Each line represents a potential support/resistance level where price might react. Vertical Lines (Time Cycles): The same Fibonacci ratios are applied to the time dimension between the high and low bars. If your high and low are 50 bars apart, vertical lines appear at: Bar 0 (0%) Bar 12 (23.6%) Bar 19 (38.2%) Bar 25 (50%) Bar 31 (61.8%) Bar 39 (78.6%) Bar 50 (100%) These suggest when price might make significant moves. 3. The Degree Mapping System The innovative feature maps the time progression to degrees: 0° = Start point (0% time) 85° = 23.6% through the cycle 138° = 38.2% through the cycle 180° = Midpoint (50%) 222° = 61.8% through the cycle (golden angle) 283° = 78.6% through the cycle 360° = Complete cycle (100%) This treats market movements as circular patterns, similar to how planets orbit or pendulums swing. Visual Output When you apply this indicator, you'll see: A rectangular mesh extending beyond your high-low range (by 150% default) Color-coded horizontal lines showing price Fibonacci levels Matching vertical lines showing time Fibonacci intervals Price labels on the right showing percentage levels Degree labels at the bottom showing the angular position in the cycle Intersection points creating a grid of potentially significant price-time coordinates Trading Application Traders use this to identify: Support/Resistance Zones: Where horizontal and vertical lines intersect Time Targets: When price might reverse (at vertical Fibonacci times) Cycle Completion: When approaching 360°, a new cycle may begin Harmonic Patterns: Geometric relationships between price and time Customization Features The script offers extensive control: Lookback period: Adjust cycle length (10-500 bars) Mesh extension: How far to project the grid forward Visual toggles: Show/hide horizontal lines, vertical lines, labels Styling: Line thickness, style (solid/dashed/dotted), colors Label positioning: Fine-tune text placement for readability The intersection at 61.8% time and 61.8% price at 222° becomes a key target zone. This tool essentially converts the abstract concept of market cycles into a concrete, visual geometric framework that traders can analyze and act upon. DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. No guarantee of profits: Past performance and theoretical models do not guarantee future results. Trading and investing involve substantial risk of loss. Not a recommendation: This script illustration does not constitute a recommendation to buy, sell, or hold any financial instrument. Do your own research: Always conduct thorough independent research and consider consulting with a qualified financial advisor before making any trading decisions.
Pine Script® indicator
by kingshukghosh71
TraderDemircan Fibonacci + XABCD Formation v1.0This indicator automatically identifies the most recent significant swing low (Point X) and the subsequent swing high (Point A) to plot a comprehensive set of Fibonacci extension levels. Beyond a standard Fibonacci tool, this script also projects a potential harmonic XABCD pattern. It identifies a retracement level (Point B) and projects a "C" target based on the XA=BC price projection. This provides traders with a complete visual framework of key support/resistance levels and potential price targets based on the last significant impulse move. How It Works Swing Detection (X & A Points): The script scans the previous Lookback Bars (user-defined) to find the lowest low, which it labels as Point X. It then finds the highest high that occurred after Point X, labeling it as Point A. Fibonacci Levels: The price range between X and A (the "XA leg") is used as the basis (0.0 to 1.0) to draw 18 different Fibonacci levels, including key extensions (1.272, 1.618, 2.618, etc.) and retracements. XABCD Projection (B & C Points): Point B: The script dynamically identifies Point B at either the 0.382 or 0.5 retracement level of the XA leg, depending on the current price action. This shows the level that is currently acting as support. Point C (Target): A target (Point C) is projected by adding the price range of the XA leg to the B point. This creates a classic XA=BC (or AB=CD, where the first leg is XA) price projection, offering a potential target for the next upward move. Key Features Automatic Swing Detection: Automatically finds and plots the X and A points, adapting to the latest price action. Comprehensive Fibonacci Suite: Includes 18 toggleable Fibonacci levels (from 0.0 to 4.618) to cover all common retracement and extension targets. XABCD Pattern & Target: Visually plots the X-A, A-B, and the projected B-C legs, clearly highlighting the C target. Dynamic "B" Point: The B point label (0.382 or 0.5) updates to reflect which retracement level is currently in play. On-Screen Info Table: A clean table in the top-right corner displays the exact price values for X, A, B, and the C Target for quick reference. Full Customization: Users can control the visibility, color, width, and style of every Fibonacci level and pattern line. Label Options: Toggle price labels (on the right) and percentage/level labels (on the left) for a clean or detailed chart.
Pine Script® indicator
by TraderDemircan_
5
3D Cube Projection - √3 Diagonal3D Cube Projection - √3 Diagonal OVERVIEW This indicator implements Bradley F. Cowan's cube projection methodology from his "Four Dimensional Stock Market Structures & Cycles" work. It visualizes a 3D cube projected onto the 2D price-time chart, using the √3 (square root of 3) body diagonal as the primary analytical tool for identifying market structure and potential cycle termination points. METHODOLOGY The cube is constructed by selecting two pivot points (A and E) which form the body diagonal - the longest diagonal running through the cube's interior from one corner to the diagonally opposite corner. According to Cowan's geometric approach: - Point A = Starting pivot (low or high) - Point E = Ending pivot (opposite extreme) - Body Diagonal (A→E) = √3 × cube side length - Face Diagonal (A→C) = √2 × cube side length The script calculates the cube dimensions by: 1. Measuring the total price range from A to E 2. Dividing by √3 to determine the cube side length in price 3. Distributing the time component across three equal segments 4. Projecting the 3D structure onto the 2D chart plane FEATURES ✓ Interactive date selection for points A and E ✓ Automatic UPLEG/DOWNLEG detection ✓ All 8 cube vertices labeled (A-H) ✓ All 6 cube faces with independent color/opacity controls ✓ √3 body diagonal (red line by default) ✓ √2 face diagonal (orange line by default) ✓ Customizable cube lines, fills, and labels ✓ Information table showing key measurements VISUAL CUSTOMIZATION - Front & Back faces: Box fills for the two square faces - Side faces: Left and right vertical faces - Top & Bottom faces: Horizontal connecting faces - Each group has independent color and opacity settings - Label size and transparency fully adjustable - Cube line styles (solid, dashed, dotted) for depth perception IMPORTANT LIMITATIONS & DISCLOSURES This indicator works within the inherent constraints of projecting 3D geometry onto a 2D price-time chart: ⚠️ VISUAL APPROXIMATION: This is a visual projection tool, not a mathematically perfect 3D cube. True 3D geometry cannot be accurately represented on a 2D plane without distortion. ⚠️ TIME DISTRIBUTION: The script divides the time axis into three equal segments (total bars ÷ 3) for practical visualization. This is an approximation that prioritizes visual coherence over strict geometric accuracy. ⚠️ UNIT SCALING: Price and time use different units (dollars vs. bars), making true isometric projection impossible. The cube appears proportional on screen but the dimensions are not directly comparable. ⚠️ 2D CONSTRAINT: We only have X (time) and Y (price) axes available. The Z-axis (depth) is simulated through visual projection techniques (line styles, shading). INTENDED USE This tool is designed for traders and analysts who study Bradley Cowan's geometric market analysis methods. It helps visualize: - Market structure in geometric terms - Potential support/resistance zones at cube edges - Cycle timing relationships using √2 and √3 ratios - Harmonic price-time relationships The cube projection should be used as one component of a comprehensive analysis approach, combined with other technical tools and fundamental analysis. MATHEMATICAL FOUNDATION While the visual representation involves approximations, the core √3 relationship is mathematically sound: - For any cube, the body diagonal = √3 × side length - The face diagonal = √2 × side length - These ratios are preserved in the price dimension calculations HOW TO USE 1. Select your starting date (Point A) - typically a significant low or high 2. Select your ending date (Point E) - the opposite extreme pivot 3. The indicator automatically constructs the cube geometry 4. Analyze the cube edges, diagonals, and faces for market structure insights 5. Adjust colors and opacity to suit your chart aesthetic TECHNICAL NOTES - Works on all timeframes and instruments - Best viewed on charts with sufficient historical data - Cube updates in real-time as new bars form - Range selection is marked with vertical lines and shading - Calculator table shows Point A, Point E, side length, and bar measurements ACKNOWLEDGMENT This indicator is based on the geometric market analysis principles developed by Bradley F. Cowan. Users are encouraged to study Cowan's original works for deeper understanding of the theoretical framework. DISCLAIMER This indicator is for educational and analytical purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own research and risk management before making trading decisions.
Pine Script® indicator
by geneclash
NEURAL FLOW INDEX — Core Energy • Momentum Stream • Pulse SyncNeural Flow Index (NFI) — Advanced Triple-Layer Reversal Framework The Neural Flow Index (NFI) is a next-generation market oscillator designed to reveal the hidden synchronization between trend energy, cyclical momentum, and internal pulse dynamics. It merges three powerful analytical layers into a single, normalized view: Core Energy Curve (based on RSO logic) — captures structural trend bias and volatility expansion. Momentum Stream (WaveTrend algorithm) — visualizes cyclical motion of price waves. Pulse Sync (Stochastic RSI adaptation) — measures short-term momentum rhythm and overextension. Each layer feeds into a unified flow model that adapts to both trend-following and reversal conditions. The goal is not to chase every fluctuation, but to sense where momentum, direction, and volatility converge into true inflection points. Conceptual Mechanics The oscillator translates complex market behavior into an elegant, multi-phase signal system: Core Energy Curve (RSO foundation): A smoothed dynamic field representing the overall strength and direction of market pressure. Green energy indicates expansion (bullish dominance); red energy reflects contraction (bearish decay). Momentum Stream (WaveTrend): The teal line functions like an electro-wave, oscillating through phases of expansion and exhaustion. It provides the heartbeat of the market — smooth, rhythmic, and beautifully cyclic. Pulse Sync (Stochastic RSI): The purple line acts as the market’s nervous pulse, reacting to micro-momentum changes before the larger trend adjusts. It identifies micro-tops and micro-bottoms that precede major trend shifts. When these three forces align, they create high-probability reversal zones known as Neural Nodes — regions where energy, momentum, and rhythm converge. Trading Logic Potential Entry Zones: When the purple Pulse Sync line crosses the green Momentum Stream near the lower or upper bounds of the oscillator, a potential turning point forms. Yet, these crossovers are only validated when the Core Energy histogram (RSO) simultaneously supports the same direction — confirming that energy and rhythm are synchronized. Histogram Confirmation: The histogram is the “voice” of the oscillator. Rising green volume within the histogram during a Pulse-Momentum crossover suggests a legitimate upward reversal. Conversely, expanding red energy during an upper-band cross indicates momentum exhaustion and an early short-side opportunity. Neutral Zones: When all three layers flatten near the zero line, the market enters an equilibrium phase — no clear trend dominance, ideal for patience and re-entry planning. | Layer | Representation | Color | Function | | --------------------- | ------------------- | ----------------- | ------------------------------ | | **Core Energy Curve** | Area / Histogram | Lime-Red gradient | Trend bias & volatility energy | | **Momentum Stream** | WaveTrend line | Teal | Cyclical flow of price | | **Pulse Sync** | Stochastic RSI line | Purple | Short-term momentum rhythm | Interpretation Summary Converging Waves: Trend, momentum, and pulse move together → strong continuation. Diverging Waves: Pulse or Momentum decouple from Core Energy → early reversal warnings. Histogram Expansion: Confirms direction and strength of the new wave. Crossovers at Extremes: Potential entries, especially when confirmed by energy alignment. 🪶 Philosophy Behind NFI The Neural Flow Index is not just a technical indicator — it’s a behavioral visualization system. Instead of focusing on lagging confirmations, it captures the neural pattern of price motion: how liquidity flows, contracts, and expands through time. It bridges the gap between pure mathematics and market intuition — giving traders a cinematic, harmonic view of energy transition inside price structure.
Pine Script® indicator
by ozgurzari
PubLibPivotLibrary "PubLibPivot" Pivot detection library for harmonic pattern analysis - Fractal and ZigZag methods with validation and utility functions fractalPivotHigh(depth)   Fractal pivot high condition   Parameters:      depth (int)   Returns: bool fractalPivotLow(depth)   Fractal pivot low condition   Parameters:      depth (int)   Returns: bool fractalPivotHighPrice(depth, occurrence)   Get fractal pivot high price   Parameters:      depth (int)      occurrence (simple int)   Returns: float fractalPivotLowPrice(depth, occurrence)   Get fractal pivot low price   Parameters:      depth (int)      occurrence (simple int)   Returns: float fractalPivotHighBarIndex(depth, occurrence)   Get fractal pivot high bar index   Parameters:      depth (int)      occurrence (simple int)   Returns: int fractalPivotLowBarIndex(depth, occurrence)   Get fractal pivot low bar index   Parameters:      depth (int)      occurrence (simple int)   Returns: int zigzagPivotHigh(deviation, backstep, useATR, atrLength)   ZigZag pivot high condition   Parameters:      deviation (float)      backstep (int)      useATR (bool)      atrLength (simple int)   Returns: bool zigzagPivotLow(deviation, backstep, useATR, atrLength)   ZigZag pivot low condition   Parameters:      deviation (float)      backstep (int)      useATR (bool)      atrLength (simple int)   Returns: bool zigzagPivotHighPrice(deviation, backstep, useATR, atrLength, occurrence)   Get ZigZag pivot high price   Parameters:      deviation (float)      backstep (int)      useATR (bool)      atrLength (simple int)      occurrence (simple int)   Returns: float zigzagPivotLowPrice(deviation, backstep, useATR, atrLength, occurrence)   Get ZigZag pivot low price   Parameters:      deviation (float)      backstep (int)      useATR (bool)      atrLength (simple int)      occurrence (simple int)   Returns: float zigzagPivotHighBarIndex(deviation, backstep, useATR, atrLength, occurrence)   Get ZigZag pivot high bar index   Parameters:      deviation (float)      backstep (int)      useATR (bool)      atrLength (simple int)      occurrence (simple int)   Returns: int zigzagPivotLowBarIndex(deviation, backstep, useATR, atrLength, occurrence)   Get ZigZag pivot low bar index   Parameters:      deviation (float)      backstep (int)      useATR (bool)      atrLength (simple int)      occurrence (simple int)   Returns: int isValidPivotVolume(pivotPrice, pivotBarIndex, minVolumeRatio, volumeLength)   Validate pivot quality based on volume   Parameters:      pivotPrice (float)      pivotBarIndex (int)      minVolumeRatio (float)      volumeLength (int)   Returns: bool isValidPivotATR(pivotPrice, lastPivotPrice, minATRMultiplier, atrLength)   Validate pivot based on minimum ATR movement   Parameters:      pivotPrice (float)      lastPivotPrice (float)      minATRMultiplier (float)      atrLength (simple int)   Returns: bool isValidPivotTime(pivotBarIndex, lastPivotBarIndex, minBars)   Validate pivot based on minimum time between pivots   Parameters:      pivotBarIndex (int)      lastPivotBarIndex (int)      minBars (int)   Returns: bool isPivotConfirmed(pivotBarIndex, depth)   Check if pivot is not repainting (confirmed)   Parameters:      pivotBarIndex (int)      depth (int)   Returns: bool addPivotToArray(pivotArray, barArray, pivotPrice, pivotBarIndex, maxSize)   Add pivot to array with validation   Parameters:      pivotArray (array)      barArray (array)      pivotPrice (float)      pivotBarIndex (int)      maxSize (int)   Returns: array - updated pivot array getPivotFromArray(pivotArray, barArray, index)   Get pivot from array by index   Parameters:      pivotArray (array)      barArray (array)      index (int)   Returns: tuple - (price, bar_index) getPivotsInRange(pivotArray, barArray, startIndex, count)   Get all pivots in range   Parameters:      pivotArray (array)      barArray (array)      startIndex (int)      count (int)   Returns: tuple, array> - (prices, bar_indices) pivotDistance(barIndex1, barIndex2)   Calculate distance between two pivots in bars   Parameters:      barIndex1 (int)      barIndex2 (int)   Returns: int - distance in bars pivotPriceRatio(price1, price2)   Calculate price ratio between two pivots   Parameters:      price1 (float)      price2 (float)   Returns: float - price ratio pivotRetracementRatio(startPrice, endPrice, currentPrice)   Calculate retracement ratio   Parameters:      startPrice (float)      endPrice (float)      currentPrice (float)   Returns: float - retracement ratio (0-1) pivotExtensionRatio(startPrice, endPrice, currentPrice)   Calculate extension ratio   Parameters:      startPrice (float)      endPrice (float)      currentPrice (float)   Returns: float - extension ratio (>1 for extension) isInFibZone(startPrice, endPrice, currentPrice, fibLevel, tolerance)   Check if price is in Fibonacci retracement zone   Parameters:      startPrice (float)      endPrice (float)      currentPrice (float)      fibLevel (float)      tolerance (float)   Returns: bool - true if in zone getPivotType(pivotPrice, pivotBarIndex, lookback)   Get pivot type (high/low) based on surrounding prices   Parameters:      pivotPrice (float)      pivotBarIndex (int)      lookback (int)   Returns: string - "high", "low", or "unknown" calculatePivotStrength(pivotPrice, pivotBarIndex, lookback)   Calculate pivot strength based on volume and price action   Parameters:      pivotPrice (float)      pivotBarIndex (int)      lookback (int)   Returns: float - strength score (0-100)
Pine Script® library
by asawicki
Advanced Pattern Detection System [50+ Patterns]【Advanced Pattern Detection System - Auto-detects 50+ Chart Patterns】 Introducing the most powerful pattern detection indicator for TradingView! ◆ What is this? An automated tool that finds and displays over 50 chart patterns on your charts. It detects all the patterns professional traders use - Double Tops, Triangles, Head & Shoulders, and more - all in ONE indicator. ◆ Main Features ・Detects 50+ patterns in real-time ・Shows visual explanation of WHY each pattern was identified ・Automatically calculates theoretical target prices ・Displays confidence levels in % (60-95%) ・Choose panel position from 9 locations ・Works on all timeframes (1min to Monthly) ◆ Detectable Patterns 1. Classic Patterns (Double Top/Bottom, Head & Shoulders, etc.) 2. Triangle Patterns (Ascending, Descending, Symmetrical, Expanding) 3. Continuation Patterns (Flags, Pennants, Wedges, etc.) 4. Harmonic Patterns (Gartley, Butterfly, Bat, etc.) 5. Price Action (Pin Bar, Engulfing, Hammer, etc.) 6. Special Patterns (Cup & Handle, V-formations, etc.) ◆ What Makes It Different ・Not just detection - shows the reasoning behind it ・Auto-draws pivot points and necklines ・Displays target prices with % gain/loss from current price ・Detects multiple patterns simultaneously, sorted by confidence ・Available in both Japanese and English versions ◆ Perfect For ✓ Anyone tired of using multiple indicators ✓ Beginners wanting to learn pattern trading ✓ Traders who don't want to miss entry points ✓ Those looking to improve discretionary trading accuracy ◆ How to Use (Easy 3 Steps) 1. Open TradingView and paste code in Pine Editor 2. Click "Add to Chart" 3. Enable only the patterns you need in settings ◆ Color Meanings Green → Bullish potential (Buy signal) Red → Bearish potential (Sell signal) Yellow → Neutral direction (Wait and see) ◆ Recommended Settings Scalping: Detection period 20, Sensitivity 0.0025 Day Trading: Detection period 50, Sensitivity 0.002 Swing Trading: Detection period 100, Sensitivity 0.0015 ◆ Real Trading Example "Detects Double Bottom → 85% confidence → Enter on neckline break → Take profit at displayed target price" This is how you can use it in practice. ◆ Important Notes ・This is an analysis tool, not investment advice ・Always combine with other indicators ・Always set stop losses ・Practice on demo account before live trading ◆ Performance If running slow, turn OFF unused pattern categories. Reducing max display count to 3 also helps. ◆ Summary This single tool provides functionality that would normally require multiple paid indicators (worth $100-200 total). It's the ultimate pattern detection system recommended for all traders, from beginners to professionals. Give it a try if interested! Feel free to ask questions in the comments.
Pine Script® indicator
by Hunk77
8
Reversal Point Dynamics⇋ Reversal Point Dynamics (RPD) This is not an indicator; it is a complete system for deconstructing the mechanics of a market reversal. Reversal Point Dynamics (RPD) moves far beyond simplistic pattern recognition, venturing into a deep analysis of the underlying forces that cause trends to exhaust, pause, and turn. It is engineered from the ground up to identify high-probability reversal points by quantifying the confluence of market dynamics in real-time. Where other tools provide a static signal, RPD delivers a dynamic probability. It understands that a true market turning point is not a single event, but a cascade of failing momentum, structural breakdown, and a shift in market order. RPD's core engine meticulously analyzes each of these dynamic components—the market's underlying state, its velocity and acceleration, its degree of chaos (entropy), and its structural framework. These forces are synthesized into a single, unified Probability Score, offering you an unprecedented, transparent view into the conviction behind every potential reversal. This is not a "black box" system. It is an open-architecture engine designed to empower the discerning trader. Featuring real-time signal projection, an integrated Fibonacci R2R Target Engine, and a comprehensive dashboard that acts as your Dynamics Control Center , RPD gives you a complete, holistic view of the market's state. The Theoretical Core: Deconstructing Market Dynamics RPD's analytical power is born from the intelligent synthesis of multiple, distinct theoretical models. Each pillar of the engine analyzes a different facet of market behavior. The convergence of these analyses—the "Singularity" event referenced in the dashboard—is what generates the final, high-conviction probability score. 1. Pillar One: Quantum State Analysis (QSA) This is the foundational analysis of the market's current state within its recent context. Instead of treating price as a random walk, QSA quantizes it into a finite number of discrete "states." Formulaic Concept: The engine establishes a price range using the highest high and lowest low over the Adaptive Analysis Period. This range is then divided into a user-defined number of Analysis Levels. The current price is mapped to one of these states (e.g., in a 9-level system, State 0 is the absolute low, and State 8 is the absolute high). Analytical Edge: This acts as a powerful foundational filter. The engine will only begin searching for reversal signals when the market has reached a statistically stretched, extreme state (e.g., State 0 or 8). The Edge Sensitivity input allows you to control exactly how close to this extreme edge the price must be, ensuring you are trading from points of maximum potential exhaustion. 2. Pillar Two: Price State Roc (PSR) - The Dynamics of Momentum This pillar analyzes the kinetic forces of the market: its velocity and acceleration. It understands that it’s not just where the price is, but how it got there that matters. Formulaic Concept: The psr function calculates two derivatives of price. Velocity: (price - price ). This measures the speed and direction of the current move. Acceleration: (velocity - velocity ). This measures the rate of change in that speed. A negative acceleration (deceleration) during a strong rally is a critical pre-reversal warning, indicating momentum is fading even as price may be pushing higher. Analytical Edge: The engine specifically hunts for exhaustion patterns where momentum is clearly decelerating as price reaches an extreme state. This is the mechanical signature of a weakening trend. 3. Pillar Three: Market Entropy Analysis - The Dynamics of Order & Chaos This is RPD's chaos filter, a concept borrowed from information theory. Entropy measures the degree of randomness or disorder in the market's price action. Formulaic Concept: The calculateEntropy function analyzes recent price changes. A market moving directionally and smoothly has low entropy (high order). A market chopping back and forth without direction has high entropy (high chaos). The value is normalized between 0 and 1. Analytical Edge: The most reliable trades occur in low-entropy, ordered environments. RPD uses the Entropy Threshold to disqualify signals that attempt to form in chaotic, unpredictable conditions, providing a powerful shield against whipsaw markets. 4. Pillar Four: The Synthesis Engine & Probability Calculation This is where all the dynamic forces converge. The final probability score is a weighted calculation that heavily rewards confluence. Formulaic Concept: The calculateProbability function intelligently assembles the final score: A Base Score is established from trend strength and entropy. An Entropy Score adds points for low entropy (order) and subtracts for high entropy (chaos). A significant Divergence Bonus is awarded for a classic momentum divergence. RSI & Volume Bonuses are added if momentum oscillators are in extreme territory or a volume spike confirms institutional interest. MTF & Adaptive Bonuses add further weight for alignment with higher timeframe structure. Analytical Edge: A signal backed by multiple dynamic forces (e.g., extreme state + decelerating momentum + low entropy + volume spike) will receive an exponentially higher probability score. This is the very essence of analyzing reversal point dynamics. The Command Center: Mastering the Inputs Every input is a precise lever of control, allowing you to fine-tune the RPD engine to your exact trading style, market, and timeframe. 🧠 Core Algorithm Predictive Mode (Early Detection): What It Is: Enables the engine to search for potential reversals on the current, unclosed bar. How It Works: Analyzes intra-bar acceleration and state to identify developing exhaustion. These signals are marked with a ' ? ' and are tentative. How To Use It: Enable for scalping or very aggressive day trading to get the earliest possible indication. Disable for swing trading or a more conservative approach that waits for full bar confirmation. Live Signal Mode (Current Bar): What It Is: A highly aggressive mode that plots tentative signals with a ' ! ' on the live bar based on projected price and momentum. These signals repaint intra-bar. How It Works: Uses a linear regression projection of the close to anticipate a reversal. How To Use It: For advanced users who use intra-bar dynamics for execution and understand the nature of repainting signals. Adaptive Analysis Period: What It Is: The main lookback period for the QSA, PSR, and Entropy calculations. This is the engine's "memory." How It Works: A shorter period makes the engine highly sensitive to local price swings. A longer period makes it focus only on major, significant market structure. How To Use It: Scalping (1-5m): 15-25. Day Trading (15m-1H): 25-40. Swing Trading (4H+): 40-60. Fractal Strength (Bars): What It Is: Defines the strength of the pivot detection used for confirming reversal events. How It Works: A value of '2' requires a candle's high/low to be more extreme than the two bars to its left and right. How To Use It: '2' is a robust standard. Increase to '3' for an even stricter definition of a structural pivot, which will result in fewer signals. MTF Multiplier: What It Is: Integrates pivot data from a higher timeframe for confluence. How It Works: A multiplier of '4' on a 15-minute chart will pull pivot data from the 1-hour chart (15 * 4 = 60m). How To Use It: Set to a multiple that corresponds to your preferred higher timeframe for contextual analysis. 🎯 Signal Settings Min Probability %: What It Is: Your master quality filter. A signal is only plotted if its score exceeds this threshold. How It Works: Directly filters the output of the final probability calculation. How To Use It: High-Quality (80-95): For A+ setups only. Balanced (65-75): For day trading. Aggressive (50-60): For scalping. Min Signal Distance (Bars): What It Is: A noise filter that prevents signals from clustering in choppy conditions. How It Works: Enforces a "cooldown" period of N bars after a signal. How To Use It: Increase in ranging markets to focus on major swings. Decrease on lower timeframes. Entropy Threshold: What It Is: Your "chaos shield." Sets the maximum allowable market randomness for a signal. How It Works: If calculated entropy is above this value, the signal is invalidated. How To Use It: Lower values (0.1-0.5): Extremely strict. Higher values (0.7-1.0): More lenient. 0.85 is a good balance. Adaptive Entropy & Aggressive Mode: What It Is: Toggles for dynamically adjusting the engine's core parameters. How It Works: Adaptive Entropy can slightly lower the required probability in strong trends. Aggressive Mode uses more lenient settings across the board. How To Use It: Keep Adaptive on. Use Aggressive Mode sparingly, primarily for scalping highly volatile assets. 📊 State Analysis Analysis Levels: What It Is: The number of discrete "states" for the QSA. How It Works: More levels create a finer-grained analysis of price location. How To Use It: 6-7 levels are ideal. Increasing to 9 can provide more precision on very volatile assets. Edge Sensitivity: What It Is: Defines how close to the absolute top/bottom of the range price must be. How It Works: '0' means price must be in the absolute highest/lowest state. '3' allows a signal within the top/bottom 3 states. How To Use It: '3' provides a good balance. Lower it to '1' or '0' if you only want to trade extreme exhaustion. The Dashboard: Your Dynamics Control Center The dashboard provides a transparent, real-time view into the engine's brain. Use it to understand the context behind every signal and to gauge the current market environment at a glance. 🎯 UNIFIED PROB SCORE TOTAL SCORE: The highest probability score (either Peak or Valley) the engine is currently calculating. This is your main at-a-glance conviction metric. The "Singularity" header refers to the event where market dynamics align—the event RPD is built to detect. Quality: A human-readable interpretation of the Total Score. "EXCEPTIONAL" (🌟) is a rare, A+ confluence event. "STRONG" (💪) is a high-quality, tradable setup. 📊 ORDER FLOW & COMPONENT ANALYSIS Volume Spike: Shows if the current volume is significantly higher than average (YES/NO). A 'YES' adds major confirmation. Peak/Valley Conf: This breaks down the probability score into its directional components, showing you the separate confidence levels for a potential top (Peak) versus a bottom (Valley). 🌌 MARKET STRUCTURE HTF Trend: Shows the direction of the underlying trend based on a Supertrend calculation. Entropy: The current market chaos reading. "🔥 LOW" is an ideal, ordered state for trading. "😴 HIGH" is a warning of choppy, unpredictable conditions. 🔮 FIB & R2R ZONE (Large Dashboard) This section gives you the status of the Fibonacci Target Engine. It shows if an Active Channel (entry zone) or Stop Zone (invalidation zone) is active and displays the precise price levels for the static entry, target, and stop calculated at the time of the signal. 🛡️ FILTERS & PREDICTIVES (Large Dashboard) This panel provides a status check on all the bonus filters. It shows the current RSI Status, whether a Divergence is present, and if a Live Pending signal is forming. The Visual Interface: A Symphony of Data Every visual element is designed for instant, intuitive interpretation of market dynamics. Signal Markers: These are the primary outputs of the engine. ▼/▲ b: A fully confirmed signal that has passed all filters. ? b: A tentative signal generated in Predictive Mode, indicating developing dynamics. ◈ b: This diamond icon replaces the standard triangle when the signal is confirmed by a strong momentum divergence, highlighting it as a superior setup where dynamics are misaligned with price. Harmonic Wave: The flowing, colored wave around the price. What It Represents: The market's "flow dynamic" and volatility. How to Interpret It: Expanding waves show increasing volatility. The color is tied to the "Quantum Color" in your theme, representing the underlying energy field of the market. Entropy Particles: The small dots appearing above/below price. What They Represent: A direct visualization of the "order dynamic." How to Interpret Them: Their presence signifies a low-entropy, ordered state ideal for trading. Their color indicates the direction of momentum (PSR velocity). Their absence means the market is too chaotic (high entropy). The Fibonacci Target Engine: The dynamic R2R system appearing post-signal. Static Fib Levels: Colored horizontal lines representing the market's "structural dynamic." The Green "Active Channel" Box: Your zone of consideration. An area to manage a potential entry. Development Philosophy Reversal Point Dynamics was engineered to answer a fundamental question: can we objectively measure the forces behind a market turn? It is a synthesis of concepts from market microstructure, statistics, and information theory. The objective was never to create a "perfect" system, but to build a robust decision-support tool that provides a measurable, statistical edge by focusing on the principle of confluence. By demanding that multiple, independent market dynamics align simultaneously, RPD filters out the vast majority of market noise. It is designed for the trader who thinks in terms of probability and risk management, not in terms of certainties. It is a tool to help you discount the obvious and bet on the unexpected alignment of market forces. "Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected." — George Soros Trade with insight. Trade with anticipation. — Dskyz, for DAFE Trading Systems
Pine Script® indicator
by DskyzInvestments
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