Aurum DCX AVE Gold and Silver StrategySummary in one paragraph
Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter.
Scope and intent
• Markets. Gold and silver futures or spot, other liquid commodities, major indices
• Timeframes. Five minutes to one day. Defaults to 30min for swing pace
• Default demo used in this publication. TVC:GOLD on 30m
• Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias
• Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings
• Testability. Each component has a named input. Entry names L and S are visible in the list of trades
• Portable yardstick. Weekly ATR for stops and R multiples for targets
• Open source. Method and implementation are disclosed for community review
Method overview in plain language
You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope.
Base measures
• Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE
• Return basis. Not required
Components
• Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window
• Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat
• DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens
• Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band
Fusion rule
• All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled
Signal rule
• Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish
• Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish
• Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band
Inputs with guidance
Setup
• Symbol. Default TVC:GOLD (Correlation Asset for internal logic)
• Signal timeframe. Blank follows the chart
• Confirm timeframe. Default 1 day used by the bias block
Directional Convexity Index
• DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier
• DCX rise bars. Typical 3 to 6. Higher demands continuation
• DCX entry threshold. Typical 15 to 35. Higher avoids soft moves
• Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape
• Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence
Adaptive Volatility Envelope
• AVE window. Typical 24 to 48. Higher smooths more
• Midline type. ALMA or HMA or EMA per preference
• TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions
• Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR
• Base envelope mult. Typical 1.4 to 2.2. Width of bands
• Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands
Intermarket Bias
• Use DXY bias. Default ON
• DXY timeframe. Default 1 day
• DXY trend window. Typical 10 to 50
Risk
• Risk percent per trade. Reporting field. Keep live risk near one to two percent
• Weekly ATR. Default 14. Basis for stops
• Stop ATR weekly mult. Typical 1.5 to 3.0
• Take profit R multiple. Typical 1.5 to 3.0
• Trail with AVE band. Optional. OFF by default
Properties visible in this publication
• Initial capital. 20000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3% of the total capital available
• Pyramiding 0
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the expansion logic
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
Open source reuse and credits
• None
Mode
Public open source. Source is visible and free to reuse within TradingView House Rules
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Bands and Channels
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
ProbRSI Adaptive SPY and QQQ Swing One Hour Strategy Summary in one paragraph
A probabilistic RSI engine for large cap ETFs and index names on intraday and swing timeframes. It converts ATR scaled returns into a 0 to 100 probability line, adapts its smoothing from path efficiency, and gates flips with simple percent levels. It is original because it fuses three pieces that traders rarely combine in one signal line: ATR normalized return probability, curvature compression, and per bar adaptive EMA. Add it to a clean chart, keep the default one hour signal on QQQ, and read the entry and exit markers generated by the strategy. For conservative alerts select on bar close.
Scope and intent
• Markets. Major ETFs and large cap equities. Index futures. Liquid crypto. Major FX pairs
• Timeframes. One minute to daily. Defaults to one hour for swing pace
• Default demo used in this publication. SPY/QQQ on one hour
• Purpose. Reduce false flips by adapting to path efficiency and by gating long and short separately
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Logistic probability of ATR scaled returns with arcsine pre transform, optional curvature compression, and per bar adaptive EMA steered by an efficiency ratio
• Failure mode addressed. Fast whips in congestion and late entries after spikes
• Testability. Each component has a named input and can be tuned directly. Entry names Long and Short are visible in the list of trades
• Portable yardstick. ATR scaled return is a common unit across symbols and venues
• Protected rationale. The code stays protected to preserve implementation details of the adaptive engine and curvature assist while the method and usage are fully explained here for community review
Method overview in plain language
You convert raw returns into a probability scale, adapt the smoothing to the straightness of the path, and only allow flips when a simple gate is satisfied. The probability line crosses its own EMA to generate signals. When the cross happens below a short gate or above a long gate, the flip is allowed. Otherwise it is ignored.
Base measures
• Return basis. Close minus prior close normalized by ATR, then arcsine to damp large steps. ATR window is set by ATR length. Sensitivity is adjusted by an ATR scale input
• Probability map. A logistic function maps the normalized return to 0 to 1 which becomes 0 to 100 after scaling
Components
• Probability core. Logistic probability of ATR scaled returns. Higher values imply upside pressure. Smoothed by an adaptive EMA
• Curvature assist optional. A curvature proxy compresses extreme spikes toward neutral. Useful after news bars. Weight controls strength
• Efficiency ratio. A path efficiency score from 0 to 1 extends the smoothing length during noisy paths and shortens it during directional paths
• Signal line. An EMA of the probability line creates the reference for cross up and cross down
• Gates. Two simple percent levels define when long and short flips are allowed
Fusion rule
• The adaptive EMA length is computed as a linear map between a minimum and a maximum bound based on one minus efficiency
• If curvature assist is enabled the probability is adjusted by a small counter spike term
• Final probability is compared to its EMA
Signal rule
• Long. A long entry is suggested when probability crosses above the signal line and the current probability is above the Long gate level
• Short. A short entry is suggested when probability crosses below the signal line and the current probability is below the Short gate level
• Exit and flip. When an opposite entry condition appears the current position is closed and a new position opens in the opposite direction
What you will see on the chart
• Strategy markers on suggestion bars. Orders named Long and Short
• Exit marker when the opposite signal closes the open side
• No table by design. All tuning lives in Inputs for a clean chart
Inputs with guidance
Market TF
• Symbol. Series used for oscillator computation. Use the instrument you trade or a close proxy
• Signal timeframe. Timeframe where the oscillator is evaluated. Leave blank to follow the chart
Core
• Price source. Series used for returns. Typical choice close
• Base length. Fallback EMA length used when adaptation is off. Typical range 20 to 200. Larger smooths more
• ATR length. Window for ATR that scales returns. Typical range 10 to 30. Larger normalizes more and lowers sensitivity
• Logit sharpness. Steepness of the logistic link. Typical range 1 to 8. Raising it reacts more to the same input
• ATR scale. Extra divisor on ATR. Typical range 0.5 to 2. Smaller is more sensitive
• Signal length. EMA of the probability line. Typical range 5 to 20. Larger gives fewer flips
• Long gate. Allow long flips only above this level. Typical range 20 to 40
• Short gate. Allow short flips only below this level. Typical range 20 to 40
Adaptive
• Adaptive smoothing. If on, the efficiency ratio controls the per bar EMA length
• Min effective length. Lower bound of adaptive EMA. Typical range 5 to 50
• Max effective length. Upper bound of adaptive EMA. Typical range 50 to 300
• Efficiency window. Window for efficiency ratio. Typical range 30 to 100
Shape Assist
• Curvature influence. If on, extreme spikes are nudged toward neutral
• Curvature weight. Strength of compression. Typical range 0.1 to 0.3
Properties visible in this publication
• Initial capital. 25000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3 for realistic testing
• Pyramiding 0
• Process orders on close ON
• Bar magnifier OFF
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the curvature assist
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher gates or longer signal length
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
• Past results never guarantee future outcomes
Open source reuse and credits
• None
Mode
Public protected. Source is hidden while access is free. Implementation detail remains private. Method and use are fully disclosed here
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Gold GC Renko Strategy Futures MGC MicrosRENKO SET UP FOR GC (1 CONTRACT)
TRADITIONAL
BOX SIZE 1
CHART TIMEFRAME 1 MINUTE
__________________________
REGULAR CANDLE SETUP FOR MGC (2 MICROS)
15 MIN TIMEFRAME
__________________________
This strategy trades pullbacks within a trend, using two EMAs (fast/slow) to define uptrends and downtrends. It waits for a volatility “squeeze” , then looks for momentum ignition to go long, while shorts require a cross and optional band break/downtrend confirmation. Risk is handled with fixed dollar profit target and stop-loss values (converted to ticks), with exits placed immediately after entries and an automatic flat-at-session-close (New York time). Signals and risk lines are plotted.
TEMA 20/34/55 Strategie mit Buy & SellThis indicator uses three Triple Exponential Moving Averages (TEMA) with periods 20 (green), 34 (blue), and 55 (red) to identify trend direction.
A buy signal is generated when TEMA20 crosses above TEMA34 and TEMA34 crosses above TEMA55 (bullish trend start).
A sell signal is generated when TEMA20 crosses below TEMA34 and TEMA34 crosses below TEMA55 (bearish trend start).
The strategy enters long and short positions with configurable stop loss and take profit levels.
Ideal for trend following and suitable for intraday or swing trading.
ES cuhthis strategy uses laggard rsi to compute the best parameters to go long and tp at key levels. the overall trend strength within the rsi laggard indicator is what is used to automate the calculations within the script. enjoy and paramter optimize
Universal Regime Alpha Thermocline StrategyCurrents settings adapted for BTCUSD Daily timeframe
This description is written to comply with TradingView House Rules and Script Publishing Rules. It is self contained, in English first, free of advertising, and explains originality, method, use, defaults, and limitations. No external links are included. Nothing here is investment advice.
0. Publication mode and rationale
This script is published as Protected . Anyone can add and test it from the Public Library, yet the source code is not visible.
Why Protected
The engine combines three independent lenses into one regime score and then uses an adaptive centering layer and a thermo risk unit that share a common AAR measure. The exact mapping and interactions are the result of original research and extensive validation. Keeping the implementation protected preserves that work and avoids low effort clones that would fragment feedback and confuse users.
Protection supports a single maintained build for users. It reduces accidental misuse of internal functions outside their intended context which might lead to misleading results.
1. What the strategy does in one paragraph
Universal Regime Alpha Thermocline builds a single number between zero and one that answers a practical question for any market and timeframe. How aligned is current price action with a persistent directional regime right now. To answer this the script fuses three views of the tape. Directional entropy of up versus down closes to measure unanimity.
Convexity drift that rewards true geometric compounding and penalizes drag that comes from chop where arithmetic pace is high but growth is poor.
Tail imbalance that counts decisive bursts in one direction relative to typical bar amplitude. The three channels are blended, optionally confirmed by a higher timeframe, and then adaptively centered to remove local bias. Entries fire when the score clears an entry gate. Exits occur when the score mean reverts below an exit gate or when thermo stops remove risk. Position size can scale with the certainty of the signal.
2. Why it is original and useful
It mixes orthogonal evidence instead of leaning on a single family of tools. Many regime filters depend on moving averages or volatility compression. Here we add an information view from entropy, a growth view from geometric drift, and a structural view from tail imbalance.
The drift channel separates growth from speed. Arithmetic pace can look strong in whipsaw, yet geometric growth stays weak. The engine measures both and subtracts drag so that only sequences with compounding quality rise.
Tail counting is anchored to AAR which is the average absolute return of bars in the window. This makes the threshold self scaling and portable across symbols and timeframes without hand tuned constants.
Adaptive centering prevents the score from living above or below neutral for long stretches on assets with strong skew. It recovers neutrality while still allowing persistent regimes to dominate once evidence accumulates.
The same AAR unit used in the signal also sets stop distance and trail distance. Signal and risk speak the same language which makes the method portable and easier to reason about.
3. Plain language overview of the math
Log returns . The base series is r equal to the natural log of close divided by the previous close. Log return allows clean aggregation and makes growth comparisons natural.
Directional entropy . Inside the lookback we compute the proportion p of bars where r is positive. Binary entropy of p is high when the mix of up and down closes is balanced and low when one direction dominates. Intensity is one minus entropy. Directional sign is two times p minus one. The trend channel is zero point five plus one half times sign times intensity. It lives between zero and one and grows stronger as unanimity increases.
Convexity drift with drag . Arithmetic mean of r measures pace. Geometric mean of the price ratio over the window measures compounding. Drag is the positive part of arithmetic minus geometric. Drift raw equals geometric minus drag multiplier times drag. We then map drift through an arctangent normalizer scaled by AAR and a nonlinearity parameter so the result is stable and remains between zero and one.
Tail imbalance . AAR equals the average of the absolute value of r in the window. We count up tails where r is greater than aar_mult times AAR and down tails where r is less than minus aar_mult times AAR. The imbalance is their difference over their total, mapped to zero to one. This detects directional impulse flow.
Fusion and centering . A weighted average of the three channels yields the raw score. If a higher timeframe is requested, the same function is executed on that timeframe with lookahead off and blended with a weight. Finally we subtract a fraction of the rolling mean of the score to recover neutrality. The result is clipped to the zero to one band.
4. Entries, exits, and position sizing
Enter long when score is strictly greater than the entry gate. Enter short when score is strictly less than one minus the entry gate unless direction is restricted in inputs.
Exit a long when score falls below the exit gate. Exit a short when score rises above one minus the exit gate.
Thermo stops are expressed in AAR units. A long uses the maximum of an initial stop sized by the entry price and AAR and a trail stop that references the running high since entry with a separate multiple. Shorts mirror this with the running low. If the trail is disabled the initial stop is active.
Cooldown is a simple bar counter that begins when the position returns to flat. It prevents immediate re entry in churn.
Dynamic position size is optional. When enabled the order percent of equity scales between a floor and a cap as the score rises above the gate for longs or below the symmetric gate for shorts.
5. Inputs quick guide with recommended ranges
Every input has a tooltip in the script. The same guidance appears here for fast reading.
Core window . Shared lookback for entropy, drift, and tails. Start near 80 on daily charts. Try 60 to 120 on intraday and 80 to 200 for swing.
Entry threshold . Typical range 0.55 to 0.65 for trend following. Faster entries 0.50 to 0.55.
Exit threshold . Typical range 0.35 to 0.50. Lower holds longer yet gives back more.
Weight directional entropy . Starting value 0.40. Raise on markets with clean persistence.
Weight convexity drift . Starting value 0.40. Raise when compounding quality is critical.
Weight tail imbalance . Starting value 0.20. Raise on breakout prone markets.
Tail threshold vs AAR . Typical range 1.0 to 1.5 to count decisive bursts.
Drag penalty . Typical range 0.25 to 0.75. Higher punishes chop more.
Nonlinearity scale . Typical range 0.8 to 2.0. Larger compresses extremes.
AAR floor in percent . Typical range 0.0005 to 0.002 for liquid instruments. This stabilizes the math during quiet regimes.
Adaptive centering . Keep on for most symbols. Center strength 0.40 to 0.70.
Confirm timeframe optional . Leave empty to disable. If used, try a multiple between three and five of the chart timeframe with a blend weight near 0.20.
Dynamic position size . Enable if you want size to reflect certainty. Floor and cap define the percent of equity band. A practical band for many accounts is 0.5 to 2.
Cooldown bars after exit . Start at 3 on daily or slightly higher on shorter charts.
Thermo stop multiple . Start between 1.5 and 3.0 on daily. Adjust to your tolerance and symbol behavior.
Thermo trailing stop and Trail multiple . Trail on locks gains earlier. A trail multiple near 1.0 to 2.0 is common. You can keep trail off and let the exit gate handle exits.
Background heat opacity . Cosmetic. Set to taste. Zero disables it.
6. Properties used on the published chart
The example publication uses BTCUSD on the daily timeframe. The following Properties and inputs are used so everyone can reproduce the same results.
Initial capital 100000
Base currency USD
Order size 2 percent of equity coming from our risk management inputs.
Pyramiding 0
Commission 0.05 percent
Slippage 10 ticks in the publication for clarity. Users should introduce slippage in their own research.
Recalculate after order is filled off. On every tick off.
Using bar magnifier on. On bar close on.
Risk inputs on the published chart. Dynamic position size on. Size floor percent 2. Size cap percent 2. Cooldown bars after exit 3. Thermo stop multiple 2.5. Thermo trailing stop off. Trail multiple 1.
7. Visual elements and alerts
The score is painted as a subtle dot rail near the bottom. A background heat map runs from red to green to convey regime strength at a glance. A compact HUD at the top right shows current score, the three component channels, the active AAR, and the remaining cooldown. Four alerts are included. Long Setup and Short Setup on entry gates. Exit Long by Score and Exit Short by Score on exit gates. You can disable trading and use alerts only if you want the score as a risk switch inside a discretionary plan.
8. How to reproduce the example
Open a BTCUSD daily chart with regular candles.
Add the strategy and load the defaults that match the values above.
Set Properties as listed in section 6.(they are set by default) Confirm that bar magnifier is on and process on bar close is on.
Run the Strategy Tester. Confirm that the trade count is reasonable for the sample. If the count is too low, slightly lower the entry threshold or extend history. If the count is excessively high, raise the threshold or add a small cooldown.
9. Practical tuning recipes
Trend following focus . Raise the entry threshold toward 0.60. Raise the trend weight to 0.50 and reduce tail weight to 0.15. Keep drift near 0.35 to retain the growth filter. Consider leaving the trail off and let the exit threshold manage positions.
Breakout focus . Keep entry near 0.55. Raise tail weight to 0.35. Keep aar_mult near 1.3 so only decisive bursts count. A modest cooldown near 5 can reduce immediate false flips after the first burst bar.
Chop defense . Raise drag multiplier to 0.70. Raise exit threshold toward 0.48 to recycle capital earlier. Consider a higher cooldown, for example 8 to 12 on intraday.
Higher timeframe blend . On a daily chart try a weekly confirm with a blend near 0.20. On a five minute chart try a fifteen minute confirm. This moderates transitions.
Sizing discipline . If you want constant position size, set floor equal to cap. If you want certainty scaling, set a band like 0.5 to 2 and monitor drawdown behavior before widening it.
10. Strengths and limitations
Strengths
Self scaling unit through AAR makes the tool portable across markets and timeframes.
Blends evidence that target different failure modes. Unanimity, growth quality, and impulse flow rarely agree by chance which raises confidence when they align.
Adaptive centering reduces structural bias at the score level which helps during regime flips.
Limitations
In very quiet regimes AAR becomes small even with a floor. If your symbol is thin or gap prone, raise the floor a little to keep stops and drift mapping stable.
Adaptive centering can delay early breakout acceptance. If you miss starts, lower center strength or temporarily disable centering while you evaluate.
Tail counting uses a fixed multiple of AAR. If a market alternates between very calm and very violent weeks, a single aar_mult may not capture both extremes. Sweep this parameter in research.
The engine reacts to realized structure. It does not anticipate scheduled news or liquidity shocks. Use event awareness if you trade around releases.
11. Realism and responsible publication
No promises or projections of performance are made. Past results never guarantee future outcomes.
Commission is set to 0.05 percent per round which is realistic for many crypto venues. Adjust to your own broker or exchange.
Slippage is set at 10 in the publication . Introduce slippage in your own tests or use a percent model.
Position size should respect sustainable risk envelopes. Risking more than five to ten percent per trade is rarely viable. The example uses a fixed two percent position size.
Security calls use lookahead off. Standard candles only. Non standard chart types like Heikin Ashi or Renko are not supported for strategies that submit orders.
12. Suggested research workflow
Begin with the balanced defaults. Confirm that the trade count is sensible for your timeframe and symbol. As a rough guide, aim for at least one hundred trades across a wide sample for statistical comfort. If your timeframe cannot produce that count, complement with multiple symbols or run longer history.
Sweep entry and exit thresholds on a small grid and observe stability. Stability across windows matters more than the single best value.
Try one higher timeframe blend with a modest weight. Large weights can drown the signal.
Vary aar_mult and drag_mult together. This tunes the aggression of breakouts versus defense in chop.
Evaluate whether dynamic size improves risk adjusted results for your style. If not, set floor equal to cap for constancy.
Walk forward through disjoint segments and inspect results by regime. Bootstrapping or segmented evaluation can reveal sensitivity to specific periods.
13. How to read the HUD and heat map
The HUD presents a compact view. Score is the current fused value. Trend is the directional entropy channel. Drift is the compounding quality channel. Tail is the burst flow channel. AAR is the current unit that scales stops and the drift map. CD is the cooldown counter. The background heat is a visual aid only. It can be disabled in inputs. Green zones near the upper band show alignment among the channels. Muted colors near the mid band show uncertainty.
14. Frequently asked questions
Can I use this as a pure indicator . Yes. Disable entries by restricting direction to one side you will not trade and use the alerts as a regime switch.
Will it work on intraday charts . Yes. The AAR unit scales with bar size. You will likely reduce the core window and increase cooldown slightly.
Should I enable the adaptive trail . If you wish to lock gains sooner and accept more exits, enable it. If you prefer to let the exit gate do the heavy lifting, keep it off.
Why do I sometimes see a green background without a position . Heat expresses the score. A position also depends on threshold comparisons, direction mode, and cooldown.
Why is Order size set to one hundred percent if dynamic size is on . The script passes an explicit quantity percent on each entry. That explicit quantity overrides the property. The property is kept at one hundred percent to avoid confusion when users later disable dynamic sizing.
Can I combine this with other tools on my chart . You can, yet for publication the chart is kept clean so users and moderators can see the output clearly. In your private workspace feel free to add other context.
15. Concepts glossary
AAR . Average absolute return across the lookback. Serves as a unit for tails, drift scaling, and stops.
Directional entropy . A measure of uncertainty of up versus down closes. Low entropy paired with a directional sign signals unanimity.
Geometric mean growth . Rate that preserves the effect of compounding over many bars.
Drag . The positive difference between arithmetic pace and geometric growth. Larger drag often signals churn that looks active but fails to compound.
Thermo stops . Stops expressed in the same AAR unit as the signal. They adapt with volatility and keep risk and signal on a common scale.
Adaptive centering . A bias correction that recenters the fused score around neutral so the meter does not drift due to persistent skew.
16. Educational notice and risk statement
Markets involve risk. This publication is for education and research. It does not provide financial advice and it is not a recommendation to buy or sell any instrument. Use realistic costs. Validate ideas with out of sample testing and with conservative position sizing. Past performance never guarantees future results.
17. Final notes for readers and moderators
The goal of this strategy is clarity and portability. Clarity comes from a single score that reflects three independent features of the tape. Portability comes from self scaling units that respect structure across assets and timeframes. The publication keeps the chart clean, explains the math plainly, lists defaults and Properties used, and includes warnings where care is required. The code is protected so the implementation remains consistent for the community while the description remains complete enough for users to understand its purpose and for moderators to evaluate originality and usefulness. If you explore variants, keep them self contained, explain exactly what they contribute, publish in English first, and treat others with respect in the comments.
Load the strategy on BTCUSD daily with the defaults listed above and study how the score transitions across regimes. Then adjust one lever at a time. Observe how the trend channel, the drift channel, and the tail channel interact during starts, pauses, and reversals. Use the alerts as a risk switch inside your own process or let the built in entries and exits run if you prefer an automated study. The intent is not to promise outcomes. The intent is to give you a robust meter for regime strength that travels well across markets and helps you structure decisions with more confidence.
Thank you for your time to read all of this
Fury by Tetrad Fury by Tetrad
What it is:
A rules-based Bollinger+RSI strategy that fades extremes: it looks for price stretching beyond Bollinger Bands while RSI confirms exhaustion, enters countertrend, then exits at predefined profit multipliers or optional stoploss. “Ultra Glow” visuals are purely cosmetic.
How it works — logic at a glance
Framework: Classic Bollinger Bands (SMA basis; configurable length & multiplier) + RSI (configurable length).
Long entries:
Price closes below the lower band and RSI < Long RSI threshold (default 28.3) → open LONG (subject to your “Market Direction” setting).
Short entries:
Price closes above the upper band and RSI > Short RSI threshold (default 88.4) → open SHORT.
Profit exits (price targets):
Uses simple multipliers of the strategy’s average entry price:
Long exit = `entry × Long Exit Multiplier` (default 1.14).
Short exit = `entry × Short Exit Multiplier` (default 0.915).
Risk controls:
Optional pricebased stoploss (disabled by default) via:
Long stop = `entry × Long Stop Factor` (default 0.73).
Short stop = `entry × Short Stop Factor` (default 1.05).
Directional filter:
“Market Direction” input lets you constrain entries to Market Neutral, Long Only, or Short Only.
Visuals:
“Ultra Glow” draws thin layered bands around upper/basis/lower; these do not affect signals.
> Note: Inputs exist for a timebased stop tracker in code, but this version exits via targets and (optional) price stop only.
Why it’s different / original
Explicit extreme + momentum pairing: Entries require simultaneous band breach and RSI exhaustion, aiming to avoid entries on gardenvariety volatility pokes.
Deterministic exits: Multiplier-based targets keep results auditable and reproducible across datasets and assets.
Minimal, unobtrusive visuals: Thin, layered glow preserves chart readability while communicating regime around the Bollinger structure.
Inputs you can tune
Bollinger: Length (default 205), Multiplier (default 2.2).
RSI: Length (default 23), Long/Short thresholds (28.3 / 88.4).
Targets: Long Exit Mult (1.14), Short Exit Mult (0.915).
Stops (optional): Enable/disable; Long/Short Stop Factors (0.73 / 1.05).
Market Direction: Market Neutral / Long Only / Short Only.
Visuals: Ultra Glow on/off, light bar tint, trade labels on/off.
How to use it
1. Timeframe & assets: Works on any symbol/timeframe; start with liquid majors and 60m–1D to establish baseline behavior, then adapt.
2. Calibrate thresholds:
Narrow/meanreverting markets often tolerate tighter RSI thresholds.
Fast/volatile markets may need wider RSI thresholds and stronger stop factors.
3. Pick realistic targets: The default multipliers are illustrative; tune them to reflect typical mean reversion distance for your instrument/timeframe (e.g., ATRinformed profiling).
4. Risk: If enabling stops, size positions so risk per trade ≤ 1–2% of equity (max 5–10% is a commonly cited upper bound).
5. Mode: Use Long Only or Short Only when your discretionary bias or higher timeframe model favors one side; otherwise Market Neutral.
Recommended publication properties (for backtests that don’t mislead)
When you publish, set your strategy’s Properties to realistic values and keep them consistent with this description:
Initial capital: 10,000 (typical retail baseline).
Commission: ≥ 0.05% (adjust for your venue).
Slippage: ≥ 2–3 ticks (or a conservative pertrade value).
Position sizing: Avoid risking > 5–10% equity per trade; fixedfractional sizing ≤ 10% or fixedcash sizing is recommended.
Dataset / sample size: Prefer symbols/timeframes yielding 100+ trades over the tested period for statistical relevance. If you deviate, say why.
> If you choose different defaults (e.g., capital, commission, slippage, sizing), explain and justify them here, and use the same settings in your publication.
Interpreting results & limitations
This is a countertrend approach; it can struggle in strong trends where band breaches compound.
Parameter sensitivity is real: thresholds and multipliers materially change trade frequency and expectancy.
No predictive claims: Past performance is not indicative of future results. The future is unknowable; treat outputs as decision support, not guarantees.
Suggested validation workflow
Try different assets. (TSLA, AAPL, BTC, SOL, XRP)
Run a walkforward across multiple years and market regimes.
Test several timeframes and multiple instruments. (30m Suggested)
Compare different commission/slippage assumptions.
Inspect distribution of returns, max drawdown, win/loss expectancy, and exposure.
Confirm behavior during trend vs. range segments.
Alerts & automation
This release focuses on chart execution and visualization. If you plan to automate, create alerts at your entry/exit conditions and ensure your broker/venue fills reflect your slippage/fees assumptions.
Disclaimer
This script is provided for educational and research purposes. It is not investment advice. Trading involves risk, including the possible loss of principal. © Tetrad Protocol.
ALMASTO – Pro Trend & Momentum (v1.1)ALMASTO — Pro Trend & Momentum Strategy
Description:
This strategy is designed for precision trading in both Forex (FX) and Crypto markets.
It combines multi-timeframe trend confirmation (EMA200), momentum filters (RSI, MACD, ADX), and ATR-based dynamic risk management.
ALMASTO — Pro Trend & Momentum Strategy automatically manages take-profit levels, stop-loss, and breakeven adjustments once TP1 is reached — providing a structured and emotion-free trading approach.
Optimal Use
Works best on lower timeframes (5m–15m) with strong liquidity sessions.
Optimized for pairs like EURUSD, XAUUSD, and BTCUSDT.
Built for trend-following setups and momentum reversals with high volatility confirmation.
Recommended Settings
🔹 Forex – 5m
EMA Fast = 34, EMA Slow = 200, HTF = 1H
RSI (14): Long ≥ 55 / Short ≤ 45
MACD (8 / 21 / 5), ADX Len 10 / Min 27
ATR Len 7, Stop Loss = ATR × 2.1
TP1 = 1.1 RR, TP2 = 2.3 RR
Session = 07:00–11:00 & 12:30–16:00 (Exchange Time)
Risk = 0.8% per trade
🔹 Forex – 15m
EMA Fast = 50, EMA Slow = 200, HTF = 4H
RSI (14): Long ≥ 53 / Short ≤ 47
MACD (12 / 26 / 9), ADX Min 24
ATR Len 10, SL = ATR × 1.9
TP1 = 1.2 RR, TP2 = 2.6 RR
Risk = 1.0% per trade
🔹 Crypto – 5m (BTC/USDT)
EMA Fast = 34, EMA Slow = 200, HTF = 4H
RSI (14): Long ≥ 56 / Short ≤ 44
MACD (8 / 21 / 5), ADX Min 30
ATR Len 7, SL = ATR × 2.2
TP1 = 1.0 RR, TP2 = 2.5 RR
Session = 00:00–06:00 & 12:00–22:00 (UTC)
Risk = 0.5% per trade
Core Features
✅ Auto breakeven after TP1
✅ Dual take-profit system (1:1 & 1:2 RR)
✅ ATR-based stop & trailing logic
✅ Filters for session time, volume, and volatility
✅ Candle-body vs ATR size filter to avoid noise
✅ Optional cooldown between trades
Important Notes
Use bar close confirmation only (barstate.isconfirmed) to avoid repainting on lower timeframes.
Adjust commission (0.01–0.03%) and slippage (1–2 ticks) in Strategy Tester for realistic results.
Avoid low-liquidity hours (after 21:00 UTC for FX / after midnight for crypto).
Backtest using realistic broker data (e.g., BlackBull Markets / Bybit / Binance Futures).
Best results occur during London & New York sessions with moderate volatility.
⚠️ Disclaimer
This script is for educational and research purposes only.
It does not constitute financial advice.
Use proper risk management and test thoroughly before using on live accounts.
Developed by KING FX Labs
Built and optimized by Yousef Almasto — combining advanced price-action logic, multi-timeframe EMA structure, and volatility-adaptive ATR management.
Tested across Forex, Gold, and Crypto markets to ensure consistent performance and minimal drawdown.
📈 “Precision Trading. Zero Emotion. Pure Momentum.”
SAN_Price Action BOS Strategy Price Action strategy with Break of structure including 20-30EMA crossover with perfect BUY/SELL alert is a beauty of this one
AI Combo Strategy: Heat + Reversal + Momentum (v3)✅ Three indicators (Heat Meter, Reversal, Momentum Nexus),
✅ Separate LookBack for SL and TP,
✅ A full-fledged HTF filter,
✅ Enable/Disable checkboxes for each block,
✅ The ability to enable Long/Short separately.
SabinaCounter-trend strategy working only in long.
Principle of Operation
The strategy is based on market extremes, which serve as both the signals for opening a position and for closing it. These extremes possess data such as Open, High, Low, Close, and others. The length and the shift (positive or negative) of the extremes are also configurable.
The extreme Ext is used for closing the position, and the extreme Ent is used for opening the position.
Base Order
A dedicated percentage of the deposit is specified. If the price crosses the Ent extreme, a long position is opened.
Take Profit and Stop Loss
The Take Profit level is calculated from the average price. A trailing stop order is present by default, which is set by the Ext extreme. When the price crosses this extreme, the position will be closed if the Take Profit has not yet been reached.
Grid of Orders (Averaging)
This section allows for enabling or disabling the grid of orders.
In the order grid, you can specify the percentage below the base order at which the grid's limit orders should be placed. The grid step is also configurable. The leverage for all orders, including the base order, is set here.
The order grid consists of 10 orders, and each order can be assigned its own percentage of the deposit. This gives the strategy greater flexibility compared to a standard DCA (Dollar-Cost Averaging) grid.
Information Panel
A table displays the historical price drop at a given moment, providing some insight into the potential liquidation level based on the selected leverage. The table also shows the deposit utilization (how much of the deposit is currently tied up).
Camarilla Pivots + 20 EMA StrategyThis is an intraday volatility and trend-following system for commodities like Natural Gas, combining dynamic pivot levels (Camarilla) with a trend filter (20-period EMA) to improve risk-reward and reduce false breakouts.
Core Components
1. Camarilla Pivots:
These are special support and resistance levels (H3, H4, L3, L4) calculated each day based on the previous day's high, low, and close.
The pivots adapt to daily volatility, giving more relevant breakout and bounce zones than static lines.
H4: Aggressive resistance (used for breakout LONG entry)
H3: Moderate resistance/support (used for bounce or stoploss)
L4: Aggressive support (used for breakout SHORT entry)
L3: Moderate support/resistance (used for bounce or stoploss)
2. 20 EMA (Exponential Moving Average):
Plotted on the 30-minute chart, this acts as a trend filter.
If the price is above 20 EMA: Only look for long trades (bullish bias).
If below 20 EMA: Only look for short trades (bearish bias).
How the Strategy Works
Setup (30-Min Chart):
Camarilla pivots for the day are drawn on the chart.
20 EMA is also plotted.
Trade Filter:
Bullish: Trade ONLY if price is above 20 EMA.
Bearish: Trade ONLY if price is below 20 EMA.
Entry:
LONG: Enter when price breaks and closes above the H4 pivot AND is above 20 EMA.
SHORT: Enter when price breaks and closes below the L4 pivot AND is below 20 EMA.
Stop Loss:
LONG: Place stoploss at H3 (the next lower Camarilla resistance).
SHORT: Place stoploss at L3 (the next higher Camarilla support).
Target:
Always set a profit target at 2x the distance (risk) between entry and stoploss (strict R:R 2).
For example, if your entry is at H4 and stoploss at H3, your target is entry + 2*(entry - stoploss).
Alerts & Visuals:
The strategy plots entry arrows, stoploss and target lines for immediate visual reference.
Alerts trigger on breakout signals so you never miss a trade.
Why This Works Well for Natural Gas
Adapts to volatility: The pivots change daily, handling wide-ranging and choppy price moves better than fixed breakouts.
Trend filter: EMA prevents counter-trend whipsaws, only trades with market momentum.
Risk control: Every trade must meet strict risk-reward criteria, so losses are contained and winners can outweigh losers.
Eyas's EyeTry it and see!!
# 🦅 EYAS'S EYE - Multi-Confluence Trend Strategy
A systematic trading strategy combining multiple technical indicators with advanced risk management for high-probability trades in trending markets.
## 📊 OVERVIEW
**Trading Style:** Swing/Position Trading
**Direction:** Long & Short
**Best Timeframes:** 4H, Daily
**Markets:** Crypto, Forex, Indices
## 🎯 METHODOLOGY
**Multi-Indicator Confluence System:**
- Trend analysis for market direction
- Momentum indicators for timing
- Volatility-based entry zones
- Dynamic ATR-based risk management
**Entry Requirements:**
- Multiple confirming signals required
- Strong trend filtering
- Minimum bars between trades
- Balanced long/short exposure
**Exit Strategy:**
- Volatility-adjusted stop losses
- High risk-reward targets (6:1)
- Trailing stops to capture trends
- Signal-based exits
- Minimum hold time to let winners run
## ✨ KEY FEATURES
✅ Realistic execution model (no look-ahead bias)
✅ Dynamic risk management
✅ Customizable parameters
✅ Clear visual signals
✅ Real-time performance metrics
## 📈 PERFORMANCE
Backtested on ETH/USD (12 months):
- Win Rate: 88-93%
- 500+ closed trades
- Strong profit factor
- Consistent monthly returns
**Best in:** Trending markets with medium-high volatility
**Challenges:** Choppy sideways markets
## 🔒 ACCESS
**This is a PROTECTED script**
To request access, send me a private message or comment below.
## ⚠️ DISCLAIMER
Trading involves substantial risk. Past performance does not guarantee future results. This is not financial advice. Always test with paper trading first and never risk more than you can afford to lose.
---
**Strategy Philosophy:** Quality over quantity. The name "Eyas's Eye" represents the sharp vision of a young eagle - patience in waiting for the right moment and the ability to spot opportunities others miss.
🦅 **Trade with vision. Trade with Eyas's Eye.**
Trend Catcher and Mean ReversionPlease DM if you want to use this strategy.
it took long time to make this code profitable using 3 parameters only!
it allow you to:
1- Pyramid as you see fit.
2- allow option to use trend catching strategy ( while keeping mean reversion strategy)
3- Time filter to limit trading and exit at your preferred time.
4- it works for long, short or both positions.
5- has trailing tp as an option as well while keeping initial sl as hard stop
6- tp multiple (of stop loss) is optional
ongoing working for alerts and automation. More on that for subscribers only.
i will charge the minimum fee to utilize this code as we don't need your money but we need people to support our vision.
Natural Gas Intraday Strategy [15m] with Partial Profit & TrailBuy when:
1. Close > EMA 100 and EMA 20 > EMA 100
2. MACD (8,21,5) > Signal and histogram rising
3. RSI > 60
4. ATR > threshold (avoid flat market)
Sell when:
1. Close < EMA 100 and EMA 20 < EMA 100
2. MACD (8,21,5) < Signal and histogram falling
3. RSI < 40
4. ATR > threshold
Exit:
• SL = recent swing ± 0.5 ATR
• TP1 = 1 ATR, trail rest with EMA 20
三均線中頻策略 v3.0 - R=2.5 + 進場點點標記📌 Core Strategy Concept
This is a medium-frequency trend-following model that utilizes three Simple Moving Averages to determine bullish or bearish alignment. It then enters trades in the direction of the trend when price confirms a breakout and applies a fixed risk-to-reward ratio (R). Stop loss and take profit levels are dynamically calculated based on moving averages, ensuring clear risk control and systematic execution.
✅ Strategy Advantages
📏 Clear Rules Trade conditions based on triple SMA alignment and price breakout; easy to replicate.
🛡 Defined Risk Stop loss and take profit are calculated based on moving averages with a fixed R ratio, ensuring disciplined risk management.
⚖️ Balanced Frequency Medium trade frequency avoids overtrading while still capturing sufficient opportunities.
👁 Visual Markers Entry points are visually marked on the chart for easy backtesting and live tracking.
Investorjordann - Script I have developed a script for the BTC pair. I'm currently trialing this...it is using multiple indicators and timeframes to trigger a trade. So far it seems very profitable across many timeframes, but I am still trailing.
Elliott Wave Auto + Fib Targets + Scalper Strategy (Fixed)// Elliott Wave Auto + Fib Targets + Scalper Strategy
//
// Fixed by expert trader:
// - Replaced table with label-based visualization to avoid 'Column 2 is out of table bounds' error.
// - Uses label.new to display buy/sell signal counts in top-right corner, mimicking table layout.
// - Fixed array.sum() error: Replaced invalid range-based array.sum() with custom sum_array_range() function.
// - Removed barstate usage to fix 'Undeclared identifier barstate' error.
// - Replaced barstate.isconfirmed with true (process every bar).
// - Replaced barstate.isfirstconfirmed with bar_index == 0 (first bar).
// - Replaced strategy.alert with label.new for long/short entry signals (buy/sell markers).
// - Fixed array index out-of-bounds: Protected array.get() calls with size checks.
// - Fixed pyramiding: Set constant pyramiding=4 (max 5 entries); use allow_pyramiding to limit entries.
// - Fixed default_qty_value: Set constant default_qty_value=100.0; use entry_size_pct to scale qty.
// - Replaced alertcondition with labels for Elliott Wave patterns.
// - Fixed partial exits: 50% at TP1 with fixed SL, 50% at TP2 with fixed SL or trailing.
// - Fixed Elliott Wave pivot indexing for alternating H/L check.
// - Ensured proper position sizing and exit logic.
BOCS Channel Scalper Strategy - Automated Mean Reversion System# BOCS Channel Scalper Strategy - Automated Mean Reversion System
## WHAT THIS STRATEGY DOES:
This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Version**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Trading enabled
- If ATR < threshold: No signals fire
This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement.
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge.
### Stop Loss Placement:
Stop losses are placed just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits.
### Trade Execution Logic:
When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position):
1. Calculate entry price at zone boundary
2. Calculate TP and SL based on selected method
3. Execute strategy.entry() with calculated position size
4. Place strategy.exit() with TP limit and SL stop orders
5. Update info table with active trade details
The strategy enforces one position at a time by checking strategy.position_size == 0 before entry.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
### Position Sizing System:
Three methods calculate position size:
**Fixed Contracts**:
- Uses exact contract quantity specified in settings
- Best for futures traders (e.g., "trade 2 NQ contracts")
**Percentage of Equity**:
- position_size = (strategy.equity × equity_pct / 100) / close
- Dynamically scales with account growth
**Cash Amount**:
- position_size = cash_amount / close
- Maintains consistent dollar exposure regardless of price
## INPUT PARAMETERS:
### Position Sizing:
- **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount
- **Number of Contracts**: Fixed quantity per trade (1-1000)
- **% of Equity**: Percentage of account to allocate (1-100%)
- **Cash Amount**: Dollar value per position ($100+)
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long entries on/off
- **Enable Short Scalps**: Toggle short entries on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time strategy status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Color Settings**: Customize long/short/TP/SL colors
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short entries
- **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status
## HOW TO USE:
### For 1-3 Minute Scalping (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars
- Position Size: 1-2 contracts
### For 5-15 Minute Day Trading:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- Position Size: Fixed contracts or 5-10% equity
### For 30-60 Minute Swing Scalping:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- Position Size: % of equity recommended
## BACKTEST CONSIDERATIONS:
- Strategy performs best in ranging, mean-reverting markets
- Strong trending markets produce more stop losses as price breaks channels
- ATR filter significantly reduces trade count but improves quality during low volatility
- Cooldown period trades signal quantity for signal quality
- Commission and slippage materially impact sub-5-minute timeframe performance
- Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions
- % of Channel TP adapts better to varying channel sizes than fixed points
- Fixed contract sizing recommended for consistent risk per trade in futures
**Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability.
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality.
## KNOWN LIMITATIONS:
- Immediate touch entry can fire multiple times in choppy zones without adequate cooldown
- Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size
- ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation)
- Mean reversion logic fails in strong breakout scenarios leading to stop loss hits
- Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price
- No partial closing capability - full position exits at TP or SL only
- Strategy does not account for gap openings or overnight holds
## RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively.
## ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.
AI - Gaussian Channel Strategy AI – Gaussian Channel Strategy is a long-only swing trading strategy designed for Bitcoin and other assets on daily charts. It combines an adaptive Gaussian Channel with Supertrend and Stochastic RSI filters to identify potential bullish breakouts or pullback entries. The channel defines trend direction and volatility, while the Stochastic RSI provides momentum confirmation. Positions are opened only when the price closes above the channel’s upper band under favorable momentum conditions, and are closed when the price crosses back below the band.
This script is intended for educational and research purposes. Parameters such as poles, period length, ATR factor, and RSI settings can be adjusted to fit different markets and timeframes.
Disclaimer: This script does not guarantee profits and should not be considered financial advice. Past performance is not indicative of future results. Trading involves risk, and you are solely responsible for your own decisions and outcomes.






















