LIB_SDz_AucLibrary "LIB_SDz_Auc"
TODO: add library description here
getLineStyle(style)
Parameters:
style (string)
Indicators and strategies
testLibLibrary "testLib"
TODO: add library description here
mySMA(x)
TODO: add function description here
Parameters:
x (int) : TODO: add parameter x description here
Returns: TODO: add what function returns
livremySMATestLibLibrary "livremySMATestLib"
TODO: add library description here
mySMA(x)
TODO: add function description here
Parameters:
x (int) : TODO: add parameter x description here
Returns: TODO: add what function returns
Material Color Palette Library█ OVERVIEW
Unlock a world of color in your Pine Script® projects with the Material Color Palette Library . This library provides a comprehensive and structured color system based on Google's Material Design palette, making it incredibly easy to create visually appealing and professional-looking indicators and strategies.
Forget about guessing hex codes. With this library, you have access to 19 distinct color families, each offering a wide range of shades. Every color can be fine-tuned with saturation, darkness, and opacity levels, giving you precise control over your script's appearance.
To make development even easier, the library includes a visual cheatsheet. Simply add the script to your chart to display a full table of all available colors and their corresponding parameters.
█ KEY FEATURES
Vast Spectrum: 19 distinct color families, from vibrant reds and blues to subtle greys and browns.
Fine-Tuned Control: Each color function accepts parameters for `saturationLevel` (1-13 or 1-9) and `darkLevel` (1-3) to select the perfect shade.
Opacity Parameter: Easily add transparency to any color for fills, backgrounds, or lines.
Quick Access Tones: A simple `tone()` function to grab base colors by name.
Visual Cheatsheet: An on-chart table displays the entire color palette, serving as a handy reference guide during development.
█ HOW TO USE
As a library, this script is meant to be imported into your own indicators or strategies.
1. Import the Library
Add the following line to the top of your script. Remember to replace `YourUsername` with your TradingView username.
import mastertop/ColorPalette/1 as colors
2. Call a Color Function
You can now use any of the exported functions to set colors for your plots, backgrounds, tables, and more.
The primary functions take three arguments: `functionName(saturationLevel, darkLevel, opacity)`
`saturationLevel`: An integer that controls the intensity of the color. Ranges from 1 (lightest) to 13 (most vibrant) for most colors, and 1-9 for `brown`, `grey`, and `blueGrey`.
`darkLevel`: An integer from 1 to 3 (1: light, 2: medium, 3: dark).
`opacity`: An integer from 0 (opaque) to 100 (invisible).
Example Usage:
Let's plot a moving average with a specific shade of teal.
// Import the library
import mastertop/ColorPalette/1 as colors
indicator("My Script with Custom Colors", overlay = true)
// Calculate a moving average
ma = ta.sma(close, 20)
// Plot the MA using a color from the library
// We'll use teal with saturation level 7, dark level 2, and 0% opacity
plot(ma, "MA", color = colors.teal(7, 2, 0), linewidth = 2)
3. Using the `tone()` Function
For quick access to a base color, you can use the `tone()` function.
// Set a red background with 85% transparency
bgcolor(colors.tone('red', 85))
█ VISUAL REFERENCE
To see all available colors at a glance, you can add this library script directly to your chart. It will display a comprehensive table showing every color variant. This makes it easy to pick the exact shade you need without guesswork.
This library is designed for fellow Pine Script® developers to streamline their workflow and enhance the visual quality of their scripts. Enjoy!
UTBotLibrary "UTBot"
is a powerful and flexible trading toolkit implemented in Pine Script. Based on the widely recognized UT Bot strategy originally developed by Yo_adriiiiaan with important enhancements by HPotter, this library provides users with customizable functions for dynamic trailing stop calculations using ATR (Average True Range), trend detection, and signal generation. It enables developers and traders to seamlessly integrate UT Bot logic into their own indicators and strategies without duplicating code.
Key features include:
Accurate ATR-based trailing stop and reversal detection
Multi-timeframe support for enhanced signal reliability
Clean and efficient API for easy integration and customization
Detailed documentation and examples for quick adoption
Open-source and community-friendly, encouraging collaboration and improvements
We sincerely thank Yo_adriiiiaan for the original UT Bot concept and HPotter for valuable improvements that have made this strategy even more robust. This library aims to honor their work by making the UT Bot methodology accessible to Pine Script developers worldwide.
This library is designed for Pine Script programmers looking to leverage the proven UT Bot methodology to build robust trading systems with minimal effort and maximum maintainability.
UTBot(h, l, c, multi, leng)
Parameters:
h (float) - high
l (float) - low
c (float)-close
multi (float)- multi for ATR
leng (int)-length for ATR
Returns:
xATRTS - ATR Based TrailingStop Value
pos - pos==1, long position, pos==-1, shot position
signal - 0 no signal, 1 buy, -1 sell
tclibLibrary "tclib"
super_smoother(data, smoothing_period)
Parameters:
data (float)
smoothing_period (int)
mt_elliott_coreLibrary "mt_elliott_core"
ewo(maFastLen, maSlowLen, smoothLen)
Parameters:
maFastLen (simple int)
maSlowLen (simple int)
smoothLen (simple int)
mt_phase_num(_len, _minGap)
Parameters:
_len (simple int)
_minGap (simple float)
mt_color_from_phase(_len, _minGap)
Parameters:
_len (simple int)
_minGap (simple float)
mt_phase_progress_pct(_len, _minGap)
Parameters:
_len (simple int)
_minGap (simple float)
anchor_p1_close(len, minGap)
Parameters:
len (simple int)
minGap (simple float)
anchor_p1_pivot(len, minGap)
Parameters:
len (simple int)
minGap (simple float)
row_group_from_ewo(ewoValue, atrValue, strongPct, neutralPct)
Parameters:
ewoValue (float)
atrValue (float)
strongPct (simple float)
neutralPct (simple float)
wave_event_pivot_aligned(ewoSeries, left, right, divTolPct, minBarsGap)
Parameters:
ewoSeries (float)
left (simple int)
right (simple int)
divTolPct (simple float)
minBarsGap (simple int)
DynLenLibLibrary "DynLenLib"
sum_dyn(src, len)
Parameters:
src (float)
len (int)
lag_dyn(src, len)
Parameters:
src (float)
len (int)
highest_dyn(src, len)
Parameters:
src (float)
len (int)
lowest_dyn(src, len)
Parameters:
src (float)
len (int)
var_dyn(src, len)
Parameters:
src (float)
len (int)
stdev_dyn(src, len)
Parameters:
src (float)
len (int)
hl2()
hlc3()
ohlc4()
sma_dyn(src, len)
Parameters:
src (float)
len (int)
ema_dyn(src, len)
Parameters:
src (float)
len (int)
rma_dyn(src, len)
Parameters:
src (float)
len (int)
smma_dyn(src, len)
Parameters:
src (float)
len (int)
wma_dyn(src, len)
Parameters:
src (float)
len (int)
vwma_dyn(price, vol, len)
Parameters:
price (float)
vol (float)
len (int)
hma_dyn(src, len)
Parameters:
src (float)
len (int)
dema_dyn(src, len)
Parameters:
src (float)
len (int)
tema_dyn(src, len)
Parameters:
src (float)
len (int)
kama_dyn(src, erLen, fastLen, slowLen)
Parameters:
src (float)
erLen (int)
fastLen (int)
slowLen (int)
mcginley_dyn(src, len)
Parameters:
src (float)
len (int)
median_price()
true_range()
atr_dyn(len)
Parameters:
len (int)
bbands_dyn(src, len, mult)
Parameters:
src (float)
len (int)
mult (float)
bb_percent_b(src, len, mult)
Parameters:
src (float)
len (int)
mult (float)
bb_bandwidth(src, len, mult)
Parameters:
src (float)
len (int)
mult (float)
keltner_dyn(src, lenEMA, lenATR, multATR)
Parameters:
src (float)
lenEMA (int)
lenATR (int)
multATR (float)
donchian_dyn(len)
Parameters:
len (int)
choppiness_index(len)
Parameters:
len (int)
vol_stop(lenATR, mult)
Parameters:
lenATR (int)
mult (float)
roc_dyn(src, len)
Parameters:
src (float)
len (int)
rsi_dyn(src, len)
Parameters:
src (float)
len (int)
stoch_dyn(kLen, dLen, smoothK)
Parameters:
kLen (int)
dLen (int)
smoothK (int)
stoch_rsi_dyn(rsiLen, stochLen, kSmooth, dLen)
Parameters:
rsiLen (int)
stochLen (int)
kSmooth (int)
dLen (int)
cci_dyn(src, len)
Parameters:
src (float)
len (int)
cmo_dyn(src, len)
Parameters:
src (float)
len (int)
trix_dyn(len)
Parameters:
len (int)
tsi_dyn(shortLen, longLen)
Parameters:
shortLen (int)
longLen (int)
ultimate_osc(len1, len2, len3)
Parameters:
len1 (int)
len2 (int)
len3 (int)
dpo_dyn(src, len)
Parameters:
src (float)
len (int)
willr_dyn(len)
Parameters:
len (int)
macd_dyn(src, fastLen, slowLen, sigLen)
Parameters:
src (float)
fastLen (int)
slowLen (int)
sigLen (int)
ppo_dyn(src, fastLen, slowLen, sigLen)
Parameters:
src (float)
fastLen (int)
slowLen (int)
sigLen (int)
aroon_dyn(len)
Parameters:
len (int)
dmi_adx_dyn(diLen, adxLen)
Parameters:
diLen (int)
adxLen (int)
vortex_dyn(len)
Parameters:
len (int)
coppock_dyn(rocLen1, rocLen2, wmaLen)
Parameters:
rocLen1 (int)
rocLen2 (int)
wmaLen (int)
rvi_dyn(len)
Parameters:
len (int)
price_osc_dyn(src, fastLen, slowLen)
Parameters:
src (float)
fastLen (int)
slowLen (int)
rci_dyn(src, len)
Parameters:
src (float)
len (int)
obv()
pvt()
cmf_dyn(len)
Parameters:
len (int)
adl()
chaikin_osc_dyn(fastLen, slowLen)
Parameters:
fastLen (int)
slowLen (int)
mfi_dyn(len)
Parameters:
len (int)
volume_osc_dyn(fastLen, slowLen)
Parameters:
fastLen (int)
slowLen (int)
up_down_volume()
cvd()
supertrend_dyn(atrLen, mult)
Parameters:
atrLen (int)
mult (float)
envelopes_dyn(src, len, pct)
Parameters:
src (float)
len (int)
pct (float)
linreg_line_slope(src, len)
Parameters:
src (float)
len (int)
lsma_dyn(src, len)
Parameters:
src (float)
len (int)
corrcoef_dyn(a, b, len)
Parameters:
a (float)
b (float)
len (int)
psar(step, maxStep)
Parameters:
step (float)
maxStep (float)
pivots_standard()
williams_alligator(src, jawLen, teethLen, lipsLen)
Parameters:
src (float)
jawLen (int)
teethLen (int)
lipsLen (int)
twap_dyn(src, len)
Parameters:
src (float)
len (int)
vwap_anchored(price, volume, reset)
Parameters:
price (float)
volume (float)
reset (bool)
performance_pct(len)
Parameters:
len (int)
AlgebraGeometryLabLibrary "AlgebraGeometryLab"
Algebra & 2D geometry utilities absent from Pine built-ins.
Rigorous, no-repaint, export-ready: vectors, robust roots, linear solvers, 2x2/3x3 det/inverse,
symmetric 2x2 eigensystem, orthogonal regression (TLS), affine transforms, intersections,
distances, projections, polygon metrics, point-in-polygon, convex hull (monotone chain),
Bezier/Catmull-Rom/Barycentric tools.
clamp(x, lo, hi)
clamp to
Parameters:
x (float)
lo (float)
hi (float)
near(a, b, atol, rtol)
approximately equal with relative+absolute tolerance
Parameters:
a (float)
b (float)
atol (float)
rtol (float)
sgn(x)
sign as {-1,0,1}
Parameters:
x (float)
hypot(x, y)
stable hypot (sqrt(x^2+y^2))
Parameters:
x (float)
y (float)
method length(v)
Namespace types: Vec2
Parameters:
v (Vec2)
method length2(v)
Namespace types: Vec2
Parameters:
v (Vec2)
method normalized(v)
Namespace types: Vec2
Parameters:
v (Vec2)
method add(a, b)
Namespace types: Vec2
Parameters:
a (Vec2)
b (Vec2)
method sub(a, b)
Namespace types: Vec2
Parameters:
a (Vec2)
b (Vec2)
method muls(v, s)
Namespace types: Vec2
Parameters:
v (Vec2)
s (float)
method dot(a, b)
Namespace types: Vec2
Parameters:
a (Vec2)
b (Vec2)
method crossz(a, b)
Namespace types: Vec2
Parameters:
a (Vec2)
b (Vec2)
method rotate(v, ang)
Namespace types: Vec2
Parameters:
v (Vec2)
ang (float)
method apply(v, T)
Namespace types: Vec2
Parameters:
v (Vec2)
T (Affine2)
affine_identity()
identity transform
affine_translate(tx, ty)
translation
Parameters:
tx (float)
ty (float)
affine_rotate(ang)
rotation about origin
Parameters:
ang (float)
affine_scale(sx, sy)
scaling about origin
Parameters:
sx (float)
sy (float)
affine_rotate_about(ang, px, py)
rotation about pivot (px,py)
Parameters:
ang (float)
px (float)
py (float)
affine_compose(T2, T1)
compose T2∘T1 (apply T1 then T2)
Parameters:
T2 (Affine2)
T1 (Affine2)
quadratic_roots(a, b, c)
Real roots of ax^2 + bx + c = 0 (numerically stable)
Parameters:
a (float)
b (float)
c (float)
Returns: with n∈{0,1,2}; r1<=r2 when n=2.
cubic_roots(a, b, c, d)
Real roots of ax^3+bx^2+cx+d=0 (Cardano; returns up to 3 real roots)
Parameters:
a (float)
b (float)
c (float)
d (float)
Returns: (valid r2/r3 only if n>=2/n>=3)
det2(a, b, c, d)
det2 of
Parameters:
a (float)
b (float)
c (float)
d (float)
inv2(a, b, c, d)
inverse of 2x2; returns
Parameters:
a (float)
b (float)
c (float)
d (float)
solve2(a, b, c, d, e, f)
solve 2x2 * = via Cramer
Parameters:
a (float)
b (float)
c (float)
d (float)
e (float)
f (float)
det3(a11, a12, a13, a21, a22, a23, a31, a32, a33)
det3 of 3x3
Parameters:
a11 (float)
a12 (float)
a13 (float)
a21 (float)
a22 (float)
a23 (float)
a31 (float)
a32 (float)
a33 (float)
inv3(a11, a12, a13, a21, a22, a23, a31, a32, a33)
inverse 3x3; returns
Parameters:
a11 (float)
a12 (float)
a13 (float)
a21 (float)
a22 (float)
a23 (float)
a31 (float)
a32 (float)
a33 (float)
eig2_symmetric(a, b, d)
symmetric 2x2 eigensystem: [ , ]
Parameters:
a (float)
b (float)
d (float)
Returns: with unit eigenvectors
tls_line(xs, ys)
Orthogonal (total least squares) regression line through point cloud
Input arrays must be same length N>=2. Returns line in normal form n•x + c = 0
Parameters:
xs (array)
ys (array)
Returns: where (nx,ny) unit normal; (cx,cy) centroid.
orient(a, b, c)
orientation (signed area*2): >0 CCW, <0 CW, 0 collinear
Parameters:
a (Vec2)
b (Vec2)
c (Vec2)
project_point_line(p, a, d)
project point p onto infinite line through a with direction d
Parameters:
p (Vec2)
a (Vec2)
d (Vec2)
Returns: where proj = a + t*d
closest_point_segment(p, a, b)
closest point on segment to p
Parameters:
p (Vec2)
a (Vec2)
b (Vec2)
Returns: where t∈ on segment
dist_point_line(p, a, d)
distance from point to line (infinite)
Parameters:
p (Vec2)
a (Vec2)
d (Vec2)
dist_point_segment(p, a, b)
distance from point to segment
Parameters:
p (Vec2)
a (Vec2)
b (Vec2)
intersect_lines(p1, d1, p2, d2)
line-line intersection: L1: p1+d1*t, L2: p2+d2*u
Parameters:
p1 (Vec2)
d1 (Vec2)
p2 (Vec2)
d2 (Vec2)
Returns:
intersect_segments(s1, s2)
segment-segment intersection (closed segments)
Parameters:
s1 (Segment2)
s2 (Segment2)
Returns: where kind: 0=no, 1=proper point, 2=overlap (ix/iy=na)
circumcircle(a, b, c)
circle through 3 non-collinear points
Parameters:
a (Vec2)
b (Vec2)
c (Vec2)
intersect_circle_line(C, p, d)
intersections of circle and line (param p + d t)
Parameters:
C (Circle2)
p (Vec2)
d (Vec2)
Returns: with n∈{0,1,2}
intersect_circles(A, B)
circle-circle intersection
Parameters:
A (Circle2)
B (Circle2)
Returns: with n∈{0,1,2}
polygon_area(xs, ys)
signed area (shoelace). Positive if CCW.
Parameters:
xs (array)
ys (array)
polygon_centroid(xs, ys)
polygon centroid (for non-self-intersecting). Fallback to vertex mean if area≈0.
Parameters:
xs (array)
ys (array)
point_in_polygon(px, py, xs, ys)
point-in-polygon test (ray casting). Returns true if inside; boundary counts as inside.
Parameters:
px (float)
py (float)
xs (array)
ys (array)
convex_hull(xs, ys)
convex hull (monotone chain). Returns array of hull vertex indices in CCW order.
Uses array.sort_indices(xs) (ascending by x). Ties on x are handled; result is deterministic.
Parameters:
xs (array)
ys (array)
lerp(a, b, t)
linear interpolate between a and b
Parameters:
a (float)
b (float)
t (float)
bezier2(p0, p1, p2, t)
quadratic Bezier B(t) for points p0,p1,p2
Parameters:
p0 (Vec2)
p1 (Vec2)
p2 (Vec2)
t (float)
bezier3(p0, p1, p2, p3, t)
cubic Bezier B(t) for p0,p1,p2,p3
Parameters:
p0 (Vec2)
p1 (Vec2)
p2 (Vec2)
p3 (Vec2)
t (float)
catmull_rom(p0, p1, p2, p3, t, alpha)
Catmull-Rom interpolation (centripetal form when alpha=0.5)
t∈ , returns point between p1 and p2
Parameters:
p0 (Vec2)
p1 (Vec2)
p2 (Vec2)
p3 (Vec2)
t (float)
alpha (float)
barycentric(A, B, C, P)
barycentric coordinates of P wrt triangle ABC
Parameters:
A (Vec2)
B (Vec2)
C (Vec2)
P (Vec2)
Returns:
point_in_triangle(A, B, C, P)
point-in-triangle using barycentric (boundary included)
Parameters:
A (Vec2)
B (Vec2)
C (Vec2)
P (Vec2)
Vec2
Fields:
x (series float)
y (series float)
Line2
Fields:
p (Vec2)
d (Vec2)
Segment2
Fields:
a (Vec2)
b (Vec2)
Circle2
Fields:
c (Vec2)
r (series float)
Affine2
Fields:
a (series float)
b (series float)
c (series float)
d (series float)
tx (series float)
ty (series float)
ema 狀態機Library "ema_flow_lib"
ema_flow_state(e10, e20, e100, entanglePct, farPct, e10_prev, e20_prev)
Parameters:
e10 (float)
e20 (float)
e100 (float)
entanglePct (float)
farPct (float)
e10_prev (float)
e20_prev (float)
state_name(s)
Parameters:
s (int)
phx_liq_tlLibrary "phx_liq_tl"
new_state()
update(st, len, cup, cdn, space, proximity_pct, shs)
Parameters:
st (LTState)
len (int)
cup (color)
cdn (color)
space (float)
proximity_pct (float)
shs (bool)
LTState
Fields:
upln (array)
dnln (array)
upBroken (series bool)
dnBroken (series bool)
phx_kroLibrary "phx_kro"
compute(src, bandwidth, bbwidth, sdLook, sdMult, obos_mult)
Parameters:
src (float)
bandwidth (int)
bbwidth (float)
sdLook (int)
sdMult (float)
obos_mult (float)
start_flags(src, bandwidth, bbwidth)
Parameters:
src (float)
bandwidth (int)
bbwidth (float)
KROFeed
Fields:
Wave (series float)
is_green (series bool)
is_red (series bool)
band_width (series float)
band_width_sma (series float)
band_width_std (series float)
is_hyper_wide (series bool)
wave_sma (series float)
wave_std (series float)
wave_ob_threshold (series float)
wave_os_threshold (series float)
is_overbought (series bool)
is_oversold (series bool)
is_oversold_confirmed (series bool)
is_overbought_confirmed (series bool)
enhanced_os_confirmed (series bool)
enhanced_ob_confirmed (series bool)
triple_green_transition (series bool)
triple_red_transition (series bool)
startwave_bull (series bool)
startwave_bear (series bool)
phx_fvgfvg generator 4h and current time frame
library to import fvg from 4h with midle line and proximity support and resistance
JK_Traders_Reality_LibLibrary "JK_Traders_Reality_Lib"
This library contains common elements used in Traders Reality scripts
calcPvsra(pvsraVolume, pvsraHigh, pvsraLow, pvsraClose, pvsraOpen, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, darkGreyCandleColor, lightGrayCandleColor)
calculate the pvsra candle color and return the color as well as an alert if a vector candle has apperared.
Situation "Climax"
Bars with volume >= 200% of the average volume of the 10 previous chart TFs, or bars
where the product of candle spread x candle volume is >= the highest for the 10 previous
chart time TFs.
Default Colors: Bull bars are green and bear bars are red.
Situation "Volume Rising Above Average"
Bars with volume >= 150% of the average volume of the 10 previous chart TFs.
Default Colors: Bull bars are blue and bear are violet.
Parameters:
pvsraVolume (float) : the instrument volume series (obtained from request.sequrity)
pvsraHigh (float) : the instrument high series (obtained from request.sequrity)
pvsraLow (float) : the instrument low series (obtained from request.sequrity)
pvsraClose (float) : the instrument close series (obtained from request.sequrity)
pvsraOpen (float) : the instrument open series (obtained from request.sequrity)
redVectorColor (simple color) : red vector candle color
greenVectorColor (simple color) : green vector candle color
violetVectorColor (simple color) : violet/pink vector candle color
blueVectorColor (simple color) : blue vector candle color
darkGreyCandleColor (simple color) : regular volume candle down candle color - not a vector
lightGrayCandleColor (simple color) : regular volume candle up candle color - not a vector
@return
adr(length, barsBack)
Parameters:
length (simple int) : how many elements of the series to calculate on
barsBack (simple int) : starting possition for the length calculation - current bar or some other value eg last bar
@return adr the adr for the specified lenght
adrHigh(adr, fromDo)
Calculate the ADR high given an ADR
Parameters:
adr (float) : the adr
fromDo (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adrHigh the position of the adr high in price
adrLow(adr, fromDo)
Parameters:
adr (float) : the adr
fromDo (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adrLow the position of the adr low in price
splitSessionString(sessXTime)
given a session in the format 0000-0100:23456 split out the hours and minutes
Parameters:
sessXTime (simple string) : the session time string usually in the format 0000-0100:23456
@return
calcSessionStartEnd(sessXTime, gmt)
calculate the start and end timestamps of the session
Parameters:
sessXTime (simple string) : the session time string usually in the format 0000-0100:23456
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
@return
drawOpenRange(sessXTime, sessXcol, showOrX, gmt)
draw open range for a session
Parameters:
sessXTime (simple string) : session string in the format 0000-0100:23456
sessXcol (simple color) : the color to be used for the opening range box shading
showOrX (simple bool) : boolean flag to toggle displaying the opening range
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
@return void
drawSessionHiLo(sessXTime, showRectangleX, showLabelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle)
Parameters:
sessXTime (simple string) : session string in the format 0000-0100:23456
showRectangleX (simple bool)
showLabelX (simple bool)
sessXcolLabel (simple color) : the color to be used for the hi/low lines and label
sessXLabel (simple string) : the session label text
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
sessionLineStyle (simple string) : the line stile for the session high low lines
@return void
calcDst()
calculate market session dst on/off flags
@return indicating if DST is on or off for a particular region
timestampPreviousDayOfWeek(previousDayOfWeek, hourOfDay, gmtOffset, oneWeekMillis)
Timestamp any of the 6 previous days in the week (such as last Wednesday at 21 hours GMT)
Parameters:
previousDayOfWeek (simple string) : Monday or Satruday
hourOfDay (simple int) : the hour of the day when psy calc is to start
gmtOffset (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
oneWeekMillis (simple int) : the amount if time for a week in milliseconds
@return the timestamp of the psy level calculation start time
getdayOpen()
get the daily open - basically exchange midnight
@return the daily open value which is float price
newBar(res)
new_bar: check if we're on a new bar within the session in a given resolution
Parameters:
res (simple string) : the desired resolution
@return true/false is a new bar for the session has started
toPips(val)
to_pips Convert value to pips
Parameters:
val (float) : the value to convert to pips
@return the value in pips
rLabel(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series during the current bar
Parameters:
ry (float) : series float the y coordinate of the lable
rtext (simple string) : the text of the label
rstyle (simple string) : the style for the lable
rcolor (simple color) : the color for the label
valid (simple bool) : a boolean flag that allows for turning on or off a lable
labelXOffset (int) : how much to offset the label from the current position
rLabelOffset(ry, rtext, rstyle, rcolor, valid, labelOffset)
a function that draws a right aligned lable for a series during the current bar
Parameters:
ry (float) : series float the y coordinate of the lable
rtext (string) : the text of the label
rstyle (simple string) : the style for the lable
rcolor (simple color) : the color for the label
valid (simple bool) : a boolean flag that allows for turning on or off a lable
labelOffset (int)
rLabelLastBar(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series only on the last bar
Parameters:
ry (float) : series float the y coordinate of the lable
rtext (string) : the text of the label
rstyle (simple string) : the style for the lable
rcolor (simple color) : the color for the label
valid (simple bool) : a boolean flag that allows for turning on or off a lable
labelXOffset (int) : how much to offset the label from the current position
drawLine(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, xLabelOffset, validTimeFrame)
a function that draws a line and a label for a series
Parameters:
xSeries (float) : series float the y coordinate of the line/label
res (simple string) : the desired resolution controlling when a new line will start
tag (simple string) : the text for the lable
xColor (simple color) : the color for the label
xStyle (simple string) : the style for the line
xWidth (simple int) : the width of the line
xExtend (simple string) : extend the line
isLabelValid (simple bool) : a boolean flag that allows for turning on or off a label
xLabelOffset (int)
validTimeFrame (simple bool) : a boolean flag that allows for turning on or off a line drawn
drawLineDO(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, xLabelOffset, validTimeFrame)
a function that draws a line and a label for the daily open series
Parameters:
xSeries (float) : series float the y coordinate of the line/label
res (simple string) : the desired resolution controlling when a new line will start
tag (simple string) : the text for the lable
xColor (simple color) : the color for the label
xStyle (simple string) : the style for the line
xWidth (simple int) : the width of the line
xExtend (simple string) : extend the line
isLabelValid (simple bool) : a boolean flag that allows for turning on or off a label
xLabelOffset (int)
validTimeFrame (simple bool) : a boolean flag that allows for turning on or off a line drawn
drawPivot(pivotLevel, res, tag, pivotColor, pivotLabelColor, pivotStyle, pivotWidth, pivotExtend, isLabelValid, validTimeFrame, levelStart, pivotLabelXOffset)
draw a pivot line - the line starts one day into the past
Parameters:
pivotLevel (float) : series of the pivot point
res (simple string) : the desired resolution
tag (simple string) : the text to appear
pivotColor (simple color) : the color of the line
pivotLabelColor (simple color) : the color of the label
pivotStyle (simple string) : the line style
pivotWidth (simple int) : the line width
pivotExtend (simple string) : extend the line
isLabelValid (simple bool) : boolean param allows to turn label on and off
validTimeFrame (simple bool) : only draw the line and label at a valid timeframe
levelStart (int) : basically when to start drawing the levels
pivotLabelXOffset (int) : how much to offset the label from its current postion
@return the pivot line series
getPvsraFlagByColor(pvsraColor, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, lightGrayCandleColor)
convert the pvsra color to an internal code
Parameters:
pvsraColor (color) : the calculated pvsra color
redVectorColor (simple color) : the user defined red vector color
greenVectorColor (simple color) : the user defined green vector color
violetVectorColor (simple color) : the user defined violet vector color
blueVectorColor (simple color) : the user defined blue vector color
lightGrayCandleColor (simple color) : the user defined regular up candle color
@return pvsra internal code
updateZones(pvsra, direction, boxArr, maxlevels, pvsraHigh, pvsraLow, pvsraOpen, pvsraClose, transperancy, zoneupdatetype, zonecolor, zonetype, borderwidth, coloroverride, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor)
a function that draws the unrecovered vector candle zones
Parameters:
pvsra (int) : internal code
direction (simple int) : above or below the current pa
boxArr (array) : the array containing the boxes that need to be updated
maxlevels (simple int) : the maximum number of boxes to draw
pvsraHigh (float) : the pvsra high value series
pvsraLow (float) : the pvsra low value series
pvsraOpen (float) : the pvsra open value series
pvsraClose (float) : the pvsra close value series
transperancy (simple int) : the transparencfy of the vecor candle zones
zoneupdatetype (simple string) : the zone update type
zonecolor (simple color) : the zone color if overriden
zonetype (simple string) : the zone type
borderwidth (simple int) : the width of the border
coloroverride (simple bool) : if the color overriden
redVectorColor (simple color) : the user defined red vector color
greenVectorColor (simple color) : the user defined green vector color
violetVectorColor (simple color) : the user defined violet vector color
blueVectorColor (simple color) : the user defined blue vector color
cleanarr(arr)
clean an array from na values
Parameters:
arr (array) : the array to clean
@return if the array was cleaned
calcPsyLevels(oneWeekMillis, showPsylevels, psyType, sydDST)
calculate the psy levels
4 hour res based on how mt4 does it
mt4 code
int Li_4 = iBarShift(NULL, PERIOD_H4, iTime(NULL, PERIOD_W1, Li_0)) - 2 - Offset;
ObjectCreate("PsychHi", OBJ_TREND, 0, Time , iHigh(NULL, PERIOD_H4, iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)), iTime(NULL, PERIOD_W1, 0), iHigh(NULL, PERIOD_H4,
iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)));
so basically because the session is 8 hours and we are looking at a 4 hour resolution we only need to take the highest high an lowest low of 2 bars
we use the gmt offset to adjust the 0000-0800 session to Sydney open which is at 2100 during dst and at 2200 otherwize. (dst - spring foward, fall back)
keep in mind sydney is in the souther hemisphere so dst is oposite of when london and new york go into dst
Parameters:
oneWeekMillis (simple int) : a constant value
showPsylevels (simple bool) : should psy levels be calculated
psyType (simple string) : the type of Psylevels - crypto or forex
sydDST (bool) : is Sydney in DST
@return
adrHiLo(length, barsBack, fromDO)
Parameters:
length (simple int) : how many elements of the series to calculate on
barsBack (simple int) : starting possition for the length calculation - current bar or some other value eg last bar
fromDO (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adr, adrLow and adrHigh - the adr, the position of the adr High and adr Low with respect to price
drawSessionHiloLite(sessXTime, showRectangleX, showLabelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle, sessXcol)
Parameters:
sessXTime (simple string) : session string in the format 0000-0100:23456
showRectangleX (simple bool)
showLabelX (simple bool)
sessXcolLabel (simple color) : the color to be used for the hi/low lines and label
sessXLabel (simple string) : the session label text
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
sessionLineStyle (simple string) : the line stile for the session high low lines
sessXcol (simple color) : - the color for the box color that will color the session
@return void
msToHmsString(ms)
converts milliseconds into an hh:mm string. For example, 61000 ms to '0:01:01'
Parameters:
ms (int) : - the milliseconds to convert to hh:mm
@return string - the converted hh:mm string
countdownString(openToday, closeToday, showMarketsWeekends, oneDay)
that calculates how much time is left until the next session taking the session start and end times into account. Note this function does not work on intraday sessions.
Parameters:
openToday (int) : - timestamps of when the session opens in general - note its a series because the timestamp was created using the dst flag which is a series itself thus producing a timestamp series
closeToday (int) : - timestamp of when the session closes in general - note its a series because the timestamp was created using the dst flag which is a series itself thus producing a timestamp series
@return a countdown of when next the session opens or 'Open' if the session is open now
showMarketsWeekends (simple bool)
oneDay (simple int)
countdownStringSyd(sydOpenToday, sydCloseToday, showMarketsWeekends, oneDay)
that calculates how much time is left until the next session taking the session start and end times into account. special case of intraday sessions like sydney
Parameters:
sydOpenToday (int)
sydCloseToday (int)
showMarketsWeekends (simple bool)
oneDay (simple int)
Market Structure Report Library [TradingFinder]🔵 Introduction
Market Structure is one of the most fundamental concepts in Price Action and Smart Money theory. In simple terms, it represents how price moves between highs and lows and reveals which phase of the market cycle we are currently in uptrend, downtrend, or transition.
Each structure in the market is formed by a combination of Breaks of Structure (BoS) and Changes of Character (CHoCH) :
BoS occurs when the market breaks a previous high or low, confirming the continuation of the current trend.
CHoCH occurs when price breaks in the opposite direction for the first time, signaling a potential trend reversal.
Since price movement is inherently fractal, market structure can be analyzed on two distinct levels :
Major / External Structure: represents the dominant macro trend.
Minor / Internal Structure: represents corrective or smaller-scale movements within the larger trend.
🔵 Library Purpose
The “Market Structure Report Library” is designed to automatically detect the current market structure type in real time.
Without drawing or displaying any visuals, it analyzes raw price data and returns a series of logical and textual outputs (Return Values) that describe the current structural state of the market.
It provides the following information :
Trend Type :
External Trend (Major): Up Trend, Down Trend, No Trend
Internal Trend (Minor): Up Trend, Down Trend, No Trend
Structure Type :
BoS : Confirms trend continuation
CHoCH : Indicates a potential trend reversal
Consecutive BoS Counter : Measures trend strength on both Major and Minor levels.
Candle Type : Returns the current candle’s condition(Bullish, Bearish, Doji)
This library is specifically designed for use in Smart Money–based screeners, indicators, and algorithmic strategies.
It can analyze multiple symbols and timeframes simultaneously and return the exact structure type (BoS or CHoCH) and trend direction for each.
🔵 Function Outputs
The function MS() processes the price data and returns seven key outputs,
each representing a distinct structural state of the market. These values can be used in indicators, strategies, or multi-symbol screeners.
🟣 ExternalTrend
Type : string
Description : Represents the direction of the Major (External) market structure.
Possible values :
Up Trend
Down Trend
No Trend
This is determined based on the behavior of Major Pivots (swing highs/lows).
🟣 InternalTrend
Type : string
Description : Represents the direction of the Minor (Internal) market structure.
Possible values :
Up Trend
Down Trend
No Trend
🟣 M_State
Type : string
Description : Specifies the type of the latest Major Structure event.
Possible values :
BoS
CHoCH
🟣 m_State
Type : string
Description : Specifies the type of the latest Minor Structure event.
Possible values :
BoS
CHoCH
🟣 MBoS_Counter
Type : integer
Description : Counts the number of consecutive structural breaks (BoS) in the Major structure.
Useful for evaluating trend strength :
Increasing count: indicates trend continuation.
Reset to zero: typically occurs after a CHoCH.
🟣 mBoS_Counter
Type : integer
Description : Counts the number of consecutive structural breaks in the Minor structure.
Helps analyze the micro structure of the market on lower timeframes.
Higher value : strong internal trend.
Reset : indicates a minor pullback or reversal.
🟣 Candle_Type
Type : string
Description : Represents the type of the current candle.
Possible values :
Bullish
Bearish
Doji
import TFlab/Market_Structure_Report_Library_TradingFinder/1 as MSS
PP = input.int (5 , 'Market Structure Pivot Period' , group = 'Symbol 1' )
= MSS.MS(PP)
SequencerLibraryLibrary "SequencerLibrary"
SequencerLibrary v1 is a Pine Script™ library for identifying, tracking, and visualizing
sequential bullish and bearish patterns on price charts.
It provides a complete framework for building sequence-based trading systems, including:
• Automatic detection and counting of setup and countdown phases.
• Real-time tracking of completion states, perfected setups, and exhaustion signals.
• Dynamic support and resistance thresholds derived from recent price structure.
• Customizable visual highlighting for both setup and countdown sequences.
method doSequence(s, src, config, condition)
Updates the sequence state based on the source value, and user configuration.
Namespace types: Sequence
Parameters:
s (Sequence) : The sequence object containing bullish and bearish setups.
src (float) : The source value (e.g., close price) used for evaluating sequence conditions.
config (SequenceInputs) : The user-defined settings for sequence analysis.
condition (bool) : When true, executes the sequence logic.
Returns:
highlight(s, css, condition)
Highlights the bullish and bearish sequence setups and countdowns on the chart.
Parameters:
s (Sequence) : The sequence object containing bullish and bearish sequence states.
css (SequenceCSS) : The styling configuration for customizing label appearances.
condition (bool) : When true, the function creates and displays labels for setups and countdowns.
Returns:
SequenceState
A type representing the configuration and state of a sequence setup.
Fields:
setup (series int) : Current count of the setup phase (e.g., how many bars have met the setup criteria).
countdown (series int) : Current count of the countdown phase (e.g., bars meeting countdown criteria).
threshold (series float) : The price threshold level used as support/resistance for the sequence.
priceWhenCompleted (series float) : The closing price when the setup or countdown phase is completed.
indicatorWhenCompleted (series float) : The indicator value when the setup or countdown phase is completed.
setupCompleted (series bool) : Indicates if the setup phase has been completed (i.e., reached the required count).
countdownCompleted (series bool) : Indicates if the countdown phase has been completed (i.e., reached exhaustion).
perfected (series bool) : Indicates if the setup meets the "perfected" condition (e.g., aligns with strict criteria).
highlightSetup (series bool) : Determines whether the setup phase should be visually highlighted on the chart.
highlightCountdown (series bool) : Determines whether the countdown phase should be visually highlighted on the chart.
Sequence
A type containing bullish and bearish sequence setups.
Fields:
bullish (SequenceState) : Configuration and state for bullish sequences.
bearish (SequenceState) : Configuration and state for bearish sequences.
SequenceInputs
A type for user-configurable input settings for sequence-based analysis.
Fields:
showSetup (series bool) : Enables or disables the display of setup sequences.
showCountdown (series bool) : Enables or disables the display of countdown sequences.
setupFilter (series string) : A comma‐separated string containing setup sequence counts to be highlighted (e.g., "1,2,3,4,5,6,7,8,9").
countdownFilter (series string) : A comma‐separated string containing countdown sequence counts to be highlighted (e.g., "1,2,3,4,5,6,7,8,9,10,11,12,13").
lookbackSetup (series int) : Defines the lookback period for evaluating setup conditions (default: 4 bars).
lookbackCountdown (series int) : Defines the lookback period for evaluating countdown conditions (default: 2 bars).
lookbackSetupPerfected (series int) : Defines the lookback period to determine a perfected setup condition (default: 6 bars).
maxSetup (series int) : The maximum count required to complete a setup phase (default: 9).
maxCountdown (series int) : The maximum count required to complete a countdown phase (default: 13).
SequenceCSS
A type defining the visual styling options for sequence labels.
Fields:
bullish (series color) : Color used for bullish sequence labels.
bearish (series color) : Color used for bearish sequence labels.
imperfect (series color) : Color used for labels representing imperfect sequences.
GBB_lib_utilsLibrary "GBB_lib_utils"
gbb_moving_average_source(_source, _length, _ma_type)
gbb_moving_average_source
@description Calculates the moving average of a source series.
Parameters:
_source (float) : (series float)
_length (simple int) : (int)
_ma_type (string) : (string)
Returns: (series) Moving average series
gbb_tf_to_display(tf_minutes, tf_string)
gbb_tf_to_display
@description Converts minutes and TF string into a short standard label.
Parameters:
tf_minutes (float) : (float)
tf_string (string) : (string)
Returns: (string) Timeframe label (M1,H1,D1,...)
gbb_convert_bars(_bars)
gbb_convert_bars
@description Formats a number of bars into a duration (days, hours, minutes + bar count).
Parameters:
_bars (int) : (int)
Returns: (string)
gbb_goldorak_init(_tf5Levels_input)
gbb_goldorak_init
@description Builds a contextual message about the current timeframe and optional 5-level TF.
Parameters:
_tf5Levels_input (string) : (string) Alternative timeframe ("" = current timeframe).
Returns: (string, string, float)
CarolTradeLibLibrary "CarolTradeLib"
f_generateSignalID(strategyName)
Parameters:
strategyName (string)
f_buildJSON(orderType, action, symbol, price, strategyName, apiKey, additionalFields, indicatorJSON)
Parameters:
orderType (string)
action (string)
symbol (string)
price (float)
strategyName (string)
apiKey (string)
additionalFields (string)
indicatorJSON (string)
sendSignal(action, symbol, price, strategyName, apiKey, indicatorJSON)
Parameters:
action (string)
symbol (string)
price (float)
strategyName (string)
apiKey (string)
indicatorJSON (string)
marketOrder(action, symbol, price, strategyName, apiKey, stopLoss, takeProfit, rrRatio, size, indicatorJSON)
Parameters:
action (string)
symbol (string)
price (float)
strategyName (string)
apiKey (string)
stopLoss (float)
takeProfit (float)
rrRatio (float)
size (float)
indicatorJSON (string)
limitOrder(action, symbol, price, strategyName, apiKey, limitPrice, size, indicatorJSON)
Parameters:
action (string)
symbol (string)
price (float)
strategyName (string)
apiKey (string)
limitPrice (float)
size (float)
indicatorJSON (string)
stopLimitOrder(action, symbol, price, strategyName, apiKey, stopPrice, limitPrice, size, indicatorJSON)
Parameters:
action (string)
symbol (string)
price (float)
strategyName (string)
apiKey (string)
stopPrice (float)
limitPrice (float)
size (float)
indicatorJSON (string)
TrailingStopLossLibrary "TrailingStopLoss"
简易追踪止损； 未充分测试，欢迎提交issue
drawdown_percent(entry_bar_index, direction_long)
drawdown_percent: 回撤百分比
Parameters:
entry_bar_index (int)
direction_long (bool)
Returns: percentage: 回撤百分比 > 0
closure_needed(entry_bar_index, initial_sl_price, percentage_ts, num_bars_tolerance, extra_drawdown_distance)
closure_needed: 是否满足平仓条件
Parameters:
entry_bar_index (int)
initial_sl_price (float)
percentage_ts (float)
num_bars_tolerance (int)
extra_drawdown_distance (float)
Returns: do_closure: bool 是否平仓
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)
AlertSenderLibrary_TradingFinderLibrary "AlertSenderLibrary_TradingFinder"
TODO: add library description here
AlertSender(Condition, Alert, AlertName, AlertType, DetectionType, SetupData, Frequncy, UTC, MoreInfo, Message, o, h, l, c, Entry, TP, SL, Distal, Proximal)
Parameters:
Condition (bool)
Alert (string)
AlertName (string)
AlertType (string)
DetectionType (string)
SetupData (string)
Frequncy (string)
UTC (string)
MoreInfo (string)
Message (string)
o (float)
h (float)
l (float)
c (float)
Entry (float)
TP (float)
SL (float)
Distal (float)
Proximal (float)
TA█ TA Library
📊 OVERVIEW
TA is a Pine Script technical analysis library. This library provides 25+ moving averages and smoothing filters , from classic SMA/EMA to Kalman Filters and adaptive algorithms, implemented based on academic research.
🎯 Core Features
Academic Based - Algorithms follow original papers and formulas
Performance Optimized - Pre-calculated constants for faster response
Unified Interface - Consistent function design
Research Based - Integrates technical analysis research
🎯 CONCEPTS
Library Design Philosophy
This technical analysis library focuses on providing:
Academic Foundation
Algorithms based on published research papers and academic standards
Implementations that follow original mathematical formulations
Clear documentation with research references
Developer Experience
Unified interface design for consistent usage patterns
Pre-calculated constants for optimal performance
Comprehensive function collection to reduce development time
Single import statement for immediate access to all functions
Each indicator encapsulated as a simple function call - one line of code simplifies complexity
Technical Excellence
25+ carefully implemented moving averages and filters
Support for advanced algorithms like Kalman Filter and MAMA/FAMA
Optimized code structure for maintainability and reliability
Regular updates incorporating latest research developments
🚀 USING THIS LIBRARY
Import Library
//@version=6
import DCAUT/TA/1 as dta
indicator("Advanced Technical Analysis", overlay=true)
Basic Usage Example
// Classic moving average combination
ema20 = ta.ema(close, 20)
kama20 = dta.kama(close, 20)
plot(ema20, "EMA20", color.red, 2)
plot(kama20, "KAMA20", color.green, 2)
Advanced Trading System
// Adaptive moving average system
kama = dta.kama(close, 20, 2, 30)
= dta.mamaFama(close, 0.5, 0.05)
// Trend confirmation and entry signals
bullTrend = kama > kama and mamaValue > famaValue
bearTrend = kama < kama and mamaValue < famaValue
longSignal = ta.crossover(close, kama) and bullTrend
shortSignal = ta.crossunder(close, kama) and bearTrend
plot(kama, "KAMA", color.blue, 3)
plot(mamaValue, "MAMA", color.orange, 2)
plot(famaValue, "FAMA", color.purple, 2)
plotshape(longSignal, "Buy", shape.triangleup, location.belowbar, color.green)
plotshape(shortSignal, "Sell", shape.triangledown, location.abovebar, color.red)
📋 FUNCTIONS REFERENCE
ewma(source, alpha)
Calculates the Exponentially Weighted Moving Average with dynamic alpha parameter.
Parameters:
source (series float) : Series of values to process.
alpha (series float) : The smoothing parameter of the filter.
Returns: (float) The exponentially weighted moving average value.
dema(source, length)
Calculates the Double Exponential Moving Average (DEMA) of a given data series.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Double Exponential Moving Average value.
tema(source, length)
Calculates the Triple Exponential Moving Average (TEMA) of a given data series.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Triple Exponential Moving Average value.
zlema(source, length)
Calculates the Zero-Lag Exponential Moving Average (ZLEMA) of a given data series. This indicator attempts to eliminate the lag inherent in all moving averages.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Zero-Lag Exponential Moving Average value.
tma(source, length)
Calculates the Triangular Moving Average (TMA) of a given data series. TMA is a double-smoothed simple moving average that reduces noise.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Triangular Moving Average value.
frama(source, length)
Calculates the Fractal Adaptive Moving Average (FRAMA) of a given data series. FRAMA adapts its smoothing factor based on fractal geometry to reduce lag. Developed by John Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Fractal Adaptive Moving Average value.
kama(source, length, fastLength, slowLength)
Calculates Kaufman's Adaptive Moving Average (KAMA) of a given data series. KAMA adjusts its smoothing based on market efficiency ratio. Developed by Perry J. Kaufman.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the efficiency calculation.
fastLength (simple int) : Fast EMA length for smoothing calculation. Optional. Default is 2.
slowLength (simple int) : Slow EMA length for smoothing calculation. Optional. Default is 30.
Returns: (float) The calculated Kaufman's Adaptive Moving Average value.
t3(source, length, volumeFactor)
Calculates the Tilson Moving Average (T3) of a given data series. T3 is a triple-smoothed exponential moving average with improved lag characteristics. Developed by Tim Tillson.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
volumeFactor (simple float) : Volume factor affecting responsiveness. Optional. Default is 0.7.
Returns: (float) The calculated Tilson Moving Average value.
ultimateSmoother(source, length)
Calculates the Ultimate Smoother of a given data series. Uses advanced filtering techniques to reduce noise while maintaining responsiveness. Based on digital signal processing principles by John Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the smoothing calculation.
Returns: (float) The calculated Ultimate Smoother value.
kalmanFilter(source, processNoise, measurementNoise)
Calculates the Kalman Filter of a given data series. Optimal estimation algorithm that estimates true value from noisy observations. Based on the Kalman Filter algorithm developed by Rudolf Kalman (1960).
Parameters:
source (series float) : Series of values to process.
processNoise (simple float) : Process noise variance (Q). Controls adaptation speed. Optional. Default is 0.05.
measurementNoise (simple float) : Measurement noise variance (R). Controls smoothing. Optional. Default is 1.0.
Returns: (float) The calculated Kalman Filter value.
mcginleyDynamic(source, length)
Calculates the McGinley Dynamic of a given data series. McGinley Dynamic is an adaptive moving average that adjusts to market speed changes. Developed by John R. McGinley Jr.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the dynamic calculation.
Returns: (float) The calculated McGinley Dynamic value.
mama(source, fastLimit, slowLimit)
Calculates the Mesa Adaptive Moving Average (MAMA) of a given data series. MAMA uses Hilbert Transform Discriminator to adapt to market cycles dynamically. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: (float) The calculated Mesa Adaptive Moving Average value.
fama(source, fastLimit, slowLimit)
Calculates the Following Adaptive Moving Average (FAMA) of a given data series. FAMA follows MAMA with reduced responsiveness for crossover signals. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: (float) The calculated Following Adaptive Moving Average value.
mamaFama(source, fastLimit, slowLimit)
Calculates Mesa Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA).
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: ( ) Tuple containing values.
laguerreFilter(source, length, gamma, order)
Calculates the standard N-order Laguerre Filter of a given data series. Standard Laguerre Filter uses uniform weighting across all polynomial terms. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Length for UltimateSmoother preprocessing.
gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.8.
order (simple int) : The order of the Laguerre filter (1-10). Higher order increases lag. Optional. Default is 8.
Returns: (float) The calculated standard Laguerre Filter value.
laguerreBinomialFilter(source, length, gamma)
Calculates the Laguerre Binomial Filter of a given data series. Uses 6-pole feedback with binomial weighting coefficients. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Length for UltimateSmoother preprocessing.
gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.5.
Returns: (float) The calculated Laguerre Binomial Filter value.
superSmoother(source, length)
Calculates the Super Smoother of a given data series. SuperSmoother is a second-order Butterworth filter from aerospace technology. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Period for the filter calculation.
Returns: (float) The calculated Super Smoother value.
rangeFilter(source, length, multiplier)
Calculates the Range Filter of a given data series. Range Filter reduces noise by filtering price movements within a dynamic range.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the average range calculation.
multiplier (simple float) : Multiplier for the smooth range. Higher values increase filtering. Optional. Default is 2.618.
Returns: ( ) Tuple containing filtered value, trend direction, upper band, and lower band.
qqe(source, rsiLength, rsiSmooth, qqeFactor)
Calculates the Quantitative Qualitative Estimation (QQE) of a given data series. QQE is an improved RSI that reduces noise and provides smoother signals. Developed by Igor Livshin.
Parameters:
source (series float) : Series of values to process.
rsiLength (simple int) : Number of bars for the RSI calculation. Optional. Default is 14.
rsiSmooth (simple int) : Number of bars for smoothing the RSI. Optional. Default is 5.
qqeFactor (simple float) : QQE factor for volatility band width. Optional. Default is 4.236.
Returns: ( ) Tuple containing smoothed RSI and QQE trend line.
sslChannel(source, length)
Calculates the Semaphore Signal Level (SSL) Channel of a given data series. SSL Channel provides clear trend signals using moving averages of high and low prices.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: ( ) Tuple containing SSL Up and SSL Down lines.
ma(source, length, maType)
Calculates a Moving Average based on the specified type. Universal interface supporting all moving average algorithms.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
maType (simple MaType) : Type of moving average to calculate. Optional. Default is SMA.
Returns: (float) The calculated moving average value based on the specified type.
atr(length, maType)
Calculates the Average True Range (ATR) using the specified moving average type. Developed by J. Welles Wilder Jr.
Parameters:
length (simple int) : Number of bars for the ATR calculation.
maType (simple MaType) : Type of moving average to use for smoothing. Optional. Default is RMA.
Returns: (float) The calculated Average True Range value.
macd(source, fastLength, slowLength, signalLength, maType, signalMaType)
Calculates the Moving Average Convergence Divergence (MACD) with customizable MA types. Developed by Gerald Appel.
Parameters:
source (series float) : Series of values to process.
fastLength (simple int) : Period for the fast moving average.
slowLength (simple int) : Period for the slow moving average.
signalLength (simple int) : Period for the signal line moving average.
maType (simple MaType) : Type of moving average for main MACD calculation. Optional. Default is EMA.
signalMaType (simple MaType) : Type of moving average for signal line calculation. Optional. Default is EMA.
Returns: ( ) Tuple containing MACD line, signal line, and histogram values.
dmao(source, fastLength, slowLength, maType)
Calculates the Dual Moving Average Oscillator (DMAO) of a given data series. Uses the same algorithm as the Percentage Price Oscillator (PPO), but can be applied to any data series.
Parameters:
source (series float) : Series of values to process.
fastLength (simple int) : Period for the fast moving average.
slowLength (simple int) : Period for the slow moving average.
maType (simple MaType) : Type of moving average to use for both calculations. Optional. Default is EMA.
Returns: (float) The calculated Dual Moving Average Oscillator value as a percentage.
continuationIndex(source, length, gamma, order)
Calculates the Continuation Index of a given data series. The index represents the Inverse Fisher Transform of the normalized difference between an UltimateSmoother and an N-order Laguerre filter. Developed by John F. Ehlers, published in TASC 2025.09.
Parameters:
source (series float) : Series of values to process.
length (simple int) : The calculation length.
gamma (simple float) : Controls the phase response of the Laguerre filter. Optional. Default is 0.8.
order (simple int) : The order of the Laguerre filter (1-10). Optional. Default is 8.
Returns: (float) The calculated Continuation Index value.
📚 RELEASE NOTES
v1.0 (2025.09.24)
✅ 25+ technical analysis functions
✅ Complete adaptive moving average series (KAMA, FRAMA, MAMA/FAMA)
✅ Advanced signal processing filters (Kalman, Laguerre, SuperSmoother, UltimateSmoother)
✅ Performance optimized with pre-calculated constants and efficient algorithms
✅ Unified function interface design following TradingView best practices
✅ Comprehensive moving average collection (DEMA, TEMA, ZLEMA, T3, etc.)
✅ Volatility and trend detection tools (QQE, SSL Channel, Range Filter)
✅ Continuation Index - Latest research from TASC 2025.09
✅ MACD and ATR calculations supporting multiple moving average types
✅ Dual Moving Average Oscillator (DMAO) for arbitrary data series analysis
