SMA RIBBON10 SMA's arranged in a ribbon. Color coded depending on price close. Free to use, open source. As seen in some charts.
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10Y Bond Yield Spread (beta)10-Year Bond Yield Spread using Quandl data
See also:
- seekingalpha.com
- www.babypips.com
- www.forexfactory.com
10 Simple & 6 Exponential Moving Averages (w/ 18 day,week,month)* This is for the trader who wants tons of moving averages on their chart from one indicator
* Using the options, you should be able ot turn off some of them if the screen is too noisy for you
* You should also be able to change colors and thickness of the bars
* The thicker bars are for longer term averages
* This version is similar to my other script except it adds the 18 day, 18 week, and 18 Month SMa
* I added them after watching ira Epstein's YouTube videos
* Let me know if there are any bugs or things that need to be change
Multi ORB TrackerMulti ORB Tracker
Multi ORB Tracker plots the Opening Range Breakout (ORB) high/low for three timeframes—5m, 15m, 30m—anchored to the NY session open (09:30 America/New_York). It draws each ORB from the first 1-minute bar of the block so levels appear immediately at 09:30 and update live until that ORB bar closes.
What it draws
ORB High & Low lines for 5m, 15m, and/or 30m.
Compact labels near the anchor (“5m ORB”, “15m ORB”, “30m ORB”).
Lines extend for ~2 hours by default (auto-scaled to your chart timeframe).
Optional Extend Right: push all active ORB lines 10 bars beyond the last bar (useful for forward
reference).
Inputs
Show 5m ORB + color (default: purple)
Show 15m ORB + color (default: lime)
Show 30m ORB + color (default: orange)
Extend right (default: off)
How it behaves (important)
Uses lower-TF anchoring with HTF data so levels appear at 09:30, then evolve while the ORB bar is forming; after the ORB bar closes, the levels stop changing.
Lines reset each new day.
Timeframe gating: each ORB only draws when your chart timeframe ≤ ORB timeframe (e.g., 5m ORB shows on 1–5m charts).
Tips
Works best during US regular trading hours.
Combine with volume, VWAP, ADR/ATR, or your breakout rules.
If you trade non-US sessions or 24/7 markets (e.g., crypto), edit the session start to match your venue.
Disclaimer : For educational purposes only. Not financial advice. Performance varies by market conditions and execution.
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
ICT Killzones and Sessions W/ Silver Bullet + MacrosForex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
Usage:
To maximize your experience, minimize the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience.
Forex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
ICT Sessions and Kill Zones
What They Are:
ICT Sessions: These are specific times during the trading day when market activity is expected to be higher, such as the London Open, New York Open, and the Asian session.
Kill Zones: These are specific time windows within these sessions where the probability of significant price movements is higher. For example, the New York AM Kill Zone is typically from 8:30 AM to 11:00 AM EST.
How to Use Them:
Identify the Session: Determine which trading session you are in (London, New York, or Asian).
Focus on Kill Zones: Within that session, focus on the kill zones for potential trade setups. For instance, during the New York session, look for setups between 8:30 AM and 11:00 AM EST.
Silver Bullets
What They Are:
Silver Bullets: These are specific, high-probability trade setups that occur within the kill zones. They are designed to be "one shot, one kill" trades, meaning they aim for precise and effective entries and exits.
How to Use Them:
Time-Based Setup: Look for these setups within the designated kill zones. For example, between 10:00 AM and 11:00 AM for the New York AM session .
Chart Analysis: Start with higher time frames like the 15-minute chart and then refine down to 5-minute and 1-minute charts to identify imbalances or specific patterns .
Macros
What They Are:
Macros: These are broader market conditions and trends that influence your trading decisions. They include understanding the overall market direction, seasonal tendencies, and the Commitment of Traders (COT) reports.
How to Use Them:
Understand Market Conditions: Be aware of the macroeconomic factors and market conditions that could affect price movements.
Seasonal Tendencies: Know the seasonal patterns that might influence the market direction.
COT Reports: Use the Commitment of Traders reports to understand the positioning of large traders and commercial hedgers .
Putting It All Together
Preparation: Understand the macro conditions and review the COT reports.
Session and Kill Zone: Identify the trading session and focus on the kill zones.
Silver Bullet Setup: Look for high-probability setups within the kill zones using refined chart analysis.
Execution: Execute the trade with precision, aiming for a "one shot, one kill" outcome.
By following these steps, you can effectively use ICT sessions, kill zones, silver bullets, and macros to enhance your trading strategy.
Usage:
To maximize your experience, shrink the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience. All credit goes to itradesize for the SB + Macro boxes
Take Profit ModelThis Indicator allows you to define 9 Taking Profit levels between your floor price and a target price you define for 10 selectable Assets and tweak the levels to your preference. It does not do any fancy dynamic calculations, it just draws lines on the chart where you want them so that you have an easy reference for when to take profit (or not).
Example:
So, if your floor price for an asset is e.g. $10 and your target price is $110 (its up to you to define, who knows right, I do not have a crystal ball), You have a range of $100 where you can set your levels as follows
The first level is the Floor price you entered = $10
Formula: Level x (Target - Floor) + Floor = Take Profit level
Levels
0.1 x (110 - 10) + 10 = $20
0.2 x (110 - 10) + 10 = $30
0.3 x (110 - 10) + 10 = $40
0.4 x (110 - 10) + 10 = $50
0.5 x (110 - 10) + 10 = $60
0.6 x (110 - 10) + 10 = $70
0.7 x (110 - 10) + 10 = $80
0.8 x (110 - 10) + 10 = $90
0.9 x (110 - 10) + 10 = $100
And finally the last level is drawn for the target price
Target Price = $110
To change the settings, go to the cog icon of the Indicator, select the assets (Tickers) you have and next enter a value between 0 and 1 (as shown above) for each level, and if you want a different color. Instead of using 0.1-0.9 you e.g. can also use Fibonacci numbers like 0.235, 0.382, 0.618, 0.786 and disable (using the check mark) the rest of the levels. Experiment with this as you see fit.
Make sure that the chart you are looking at in TradingView is the same as you select in the indicator configuration e.g. COINBASE:BTCUSD should be selected as the chart as well as the Ticker in the configuration.
The Start date of the script is configurable (one date across all assets and levels)
The colors of the Levels is configurable (I am colorblind so go wild)
The standard values in the script are just examples, you need to determine the values that apply in your case and do your own research.
Your feedback is most welcome
Time-Based Fair Value Gaps (FVG) with Inversions (iFVG)Overview
The Time-Based Fair Value Gaps (FVG) with Inversions (iFVG) (ICT/SMT) indicator is a specialized tool designed for traders using Inner Circle Trader (ICT) methodologies. Inspired by LuxAlgo's Fair Value Gap indicator, this script introduces significant enhancements by integrating ICT principles, focusing on precise time-based FVG detection, inversion tracking, and retest signals tailored for institutional trading strategies. Unlike LuxAlgo’s general FVG approach, this indicator filters FVGs within customizable 10-minute windows aligned with ICT’s macro timeframes and incorporates ICT-specific concepts like mitigation, liquidity grabs, and session-based gap prioritization.
This tool is optimized for 1–5 minute charts, though probably best for 1 minute charts, identifying bullish and bearish FVGs, tracking their mitigation into inverted FVGs (iFVGs) as key support/resistance zones, and generating retest signals with customizable “Close” or “Wick” confirmation. Features like ATR-based filtering, optional FVG labels, mitigation removal, and session-specific FVG detection (e.g., first FVG in AM/PM sessions) make it a powerful tool for ICT traders.
Originality and Improvements
While inspired by LuxAlgo’s FVG indicator (credit to LuxAlgo for their foundational work), this script significantly extends the original concept by:
1. Time-Based FVG Detection: Unlike LuxAlgo’s continuous FVG identification, this script filters FVGs within user-defined 10-minute windows each hour (:00–:10, :10–:20, etc.), aligning with ICT’s emphasis on specific periods of institutional activity, such as hourly opens/closes or kill zones (e.g., New York 7:00–11:00 AM EST). This ensures FVGs are relevant to high-probability ICT setups.
2. Session-Specific First FVG Option: A unique feature allows traders to display only the first FVG in ICT-defined AM (9:30–10:00 AM EST) or PM (1:30–2:00 PM EST) sessions, reflecting ICT’s focus on initial market imbalances during key liquidity events.
3. ICT-Driven Mitigation and Inversion Logic: The script tracks FVG mitigation (when price closes through a gap) and converts mitigated FVGs into iFVGs, which serve as ICT-style support/resistance zones. This aligns with ICT’s view that mitigated gaps become critical reversal points, unlike LuxAlgo’s simpler gap display.
4. Customizable Retest Signals: Retest signals for iFVGs are configurable for “Close” (conservative, requiring candle body confirmation) or “Wick” (faster, using highs/lows), catering to ICT traders’ need for precise entry timing during liquidity grabs or Judas swings.
5. ATR Filtering and Mitigation Removal: An optional ATR filter ensures only significant FVGs are displayed, reducing noise, while mitigation removal declutters the chart by removing filled gaps, aligning with ICT’s principle that mitigated gaps lose relevance unless inverted.
6. Timezone and Timeframe Safeguards: A timezone offset setting aligns FVG detection with EST for ICT’s New York-centric strategies, and a timeframe warning alerts users to avoid ≥1-hour charts, ensuring accuracy in time-based filtering.
These enhancements make the script a distinct tool that builds on LuxAlgo’s foundation while offering ICT traders a tailored, high-precision solution.
How It Works
FVG Detection
FVGs are identified when a candle’s low is higher than the high of two candles prior (bullish FVG) or a candle’s high is lower than the low of two candles prior (bearish FVG). Detection is restricted to:
• User-selected 10-minute windows (e.g., :00–:10, :50–:60) to capture ICT-relevant periods like hourly transitions.
• AM/PM session first FVGs (if enabled), focusing on 9:30–10:00 AM or 1:30–2:00 PM EST for key market opens.
An optional ATR filter (default: 0.25× ATR) ensures only gaps larger than the threshold are displayed, prioritizing significant imbalances.
Mitigation and Inversion
When price closes through an FVG (e.g., below a bullish FVG’s bottom), the FVG is mitigated and becomes an iFVG, plotted as a support/resistance zone. iFVGs are critical in ICT for identifying reversal points where institutional orders accumulate.
Retest Signals
The script generates signals when price retests an iFVG:
• Close: Triggers when the candle body confirms the retest (conservative, lower noise).
• Wick: Triggers when the candle’s high/low touches the iFVG (faster, higher sensitivity). Signals are visualized with triangular markers (▲ for bullish, ▼ for bearish) and can trigger alerts.
Visualization
• FVGs: Displayed as colored boxes (green for bullish, red for bearish) with optional “Bull FVG”/“Bear FVG” labels.
• iFVGs: Shown as extended boxes with dashed midlines, limited to the user-defined number of recent zones (default: 5).
• Mitigation Removal: Mitigated FVGs/iFVGs are removed (if enabled) to keep the chart clean.
How to Use
Recommended Settings
• Timeframe: Use 1–5 minute charts for precision, avoiding ≥1-hour timeframes (a warning label appears if misconfigured).
• Time Windows: Enable :00–:10 and :50–:60 for hourly open/close FVGs, or use the “Show only 1st presented FVG” option for AM/PM session focus.
• ATR Filter: Keep enabled (multiplier 0.25–0.5) for significant gaps; disable on 1-minute charts for more FVGs during volatility.
• Signal Preference: Use “Close” for conservative entries, “Wick” for aggressive setups.
• Timezone Offset: Set to -5 for EST (or -4 for EDT) to align with ICT’s New York session.
Trading Strategy
1. Macro Timeframes: Focus on New York (7:00–11:00 AM EST) or London (2:00–5:00 AM EST) kill zones for high institutional activity.
2. FVG Entries: Trade bullish FVGs as support in uptrends or bearish FVGs as resistance in downtrends, especially in :00–:10 or :50–:60 windows.
3. iFVG Retests: Enter on retest signals (▲/▼) during liquidity grabs or Judas swings, using “Close” for confirmation or “Wick” for speed.
4. Session FVGs: Use the “Show only 1st presented FVG” option to target the first gap in AM/PM sessions, often tied to ICT’s market maker algorithms.
5. Risk Management: Combine with ICT concepts like order blocks or breaker blocks for confluence, and set stops beyond FVG/iFVG boundaries.
Alerts
Set alerts for:
• “Bullish FVG Detected”/“Bearish FVG Detected”: New FVGs in selected windows.
• “Bullish Signal”/“Bearish Signal”: iFVG retest confirmations.
Settings Description
• Show Last (1–100, default: 5): Number of recent iFVGs to display. Lower values reduce clutter.
• Show only 1st presented FVG : Limits FVGs to the first in 9:30–10:00 AM or 1:30–2:00 PM EST sessions (overrides time window checkboxes).
• Time Window Checkboxes: Enable/disable FVG detection in 10-minute windows (:00–:10, :10–:20, etc.). All enabled by default.
• Signal Preference: “Close” (default) or “Wick” for iFVG retest signals.
• Use ATR Filter: Enables ATR-based size filtering (default: true).
• ATR Multiplier (0–∞, default: 0.25): Sets FVG size threshold (higher values = larger gaps).
• Remove Mitigated FVGs: Removes filled FVGs/iFVGs (default: true).
• Show FVG Labels: Displays “Bull FVG”/“Bear FVG” labels (default: true).
• Timezone Offset (-12 to 12, default: -5): Aligns time windows with EST.
• Colors: Customize bullish (green), bearish (red), and midline (gray) colors.
Why Use This Indicator?
This indicator empowers ICT traders with a tool that goes beyond generic FVG detection, offering precise, time-filtered gaps and inversion tracking aligned with institutional trading principles. By focusing on ICT’s macro timeframes, session-specific imbalances, and customizable signal logic, it provides a clear edge for scalping, swing trading, or reversal setups in high-liquidity markets.
Macros ICT KillZones [TradingFinder] Times & Price Trading Setup🔵 Introduction
ICT Macros, developed by Michael Huddleston, also known as ICT (Inner Circle Trader), is a powerful trading tool designed to help traders identify the best trading opportunities during key time intervals like the London and New York trading sessions.
For traders aiming to capitalize on market volatility, liquidity shifts, and Fair Value Gaps (FVG), understanding and using these critical time zones can significantly improve trading outcomes.
In today’s highly competitive financial markets, identifying the moments when the market is seeking buy-side or sell-side liquidity, or filling price imbalances, is essential for maximizing profitability.
The ICT Macros indicator is built on the renowned ICT time and price theory, which enables traders to track and leverage key market dynamics such as breaks of highs and lows, imbalances, and liquidity hunts.
This indicator automatically detects crucial market times and optimizes strategies for traders by highlighting the specific moments when price movements are most likely to occur. A standout feature of ICT Macros is its automatic adjustment for Daylight Saving Time (DST), ensuring that traders remain synced with the correct session times.
This means you can rely on accurate market timing without the need for manual updates, allowing you to focus on capturing profitable trades during critical timeframes.
🔵 How to Use
The ICT Macros indicator helps you capitalize on trading opportunities during key market moments, particularly when the market is breaking highs or lows, filling Fair Value Gaps (FVG), or addressing imbalances. This indicator is particularly beneficial for traders who seek to identify liquidity, market volatility, and price imbalances.
🟣 Sessions
London Sessions
London Macro 1 :
UTC Time : 06:33 to 07:00
New York Time : 02:33 to 03:00
London Macro 2 :
UTC Time : 08:03 to 08:30
New York Time : 04:03 to 04:30
New York Sessions
New York Macro AM 1 :
UTC Time : 12:50 to 13:10
New York Time : 08:50 to 09:10
New York Macro AM 2 :
UTC Time : 13:50 to 14:10
New York Time : 09:50 to 10:10
New York Macro AM 3 :
UTC Time : 14:50 to 15:10
New York Time : 10:50 to 11:10
New York Lunch Macro :
UTC Time : 15:50 to 16:10
New York Time : 11:50 to 12:10
New York PM Macro :
UTC Time : 17:10 to 17:40
New York Time : 13:10 to 13:40
New York Last Hour Macro :
UTC Time : 19:15 to 19:45
New York Time : 15:15 to 15:45
These time intervals adjust automatically based on Daylight Saving Time (DST), helping traders to enter or exit trades during key market moments when price volatility is high.
Below are the main applications of this tool and how to incorporate it into your trading strategies :
🟣 Combining ICT Macros with Trading Strategies
The ICT Macros indicator can easily be used in conjunction with various trading strategies. Two well-known strategies that can be combined with this indicator include:
ICT 2022 Trading Model : This model is designed based on identifying market liquidity, structural price changes, and Fair Value Gaps (FVG). By using ICT Macros, you can identify the key time intervals when the market is seeking liquidity, filling imbalances, or breaking through important highs and lows, allowing you to enter or exit trades at the right moment.
Silver Bullet Strategy : This strategy, which is built around liquidity hunting and rapid price movements, can work more accurately with the help of ICT Macros. The indicator pinpoints precise liquidity times, helping traders take advantage of market shifts caused by filling Fair Value Gaps or correcting imbalances.
🟣 Capitalizing on Price Volatility During Key Times
Large market algorithms often seek liquidity or fill Fair Value Gaps (FVG) during the intervals marked by ICT Macros. These periods are when price volatility increases, and traders can use these moments to enter or exit trades.
For example, if sell-side liquidity is drained and the market fills an imbalance, the price might move toward buy-side liquidity. By identifying these moments, which may also involve breaking a previous high or low, you can leverage rapid market fluctuations to your advantage.
🟣 Identifying Liquidity and Price Imbalances
One of the important uses of ICT Macros is identifying points where the market is seeking liquidity and correcting imbalances. You can determine high or low liquidity levels in the market before each ICT Macro, as well as Fair Value Gaps (FVG) and price imbalances that need to be filled, using them to adjust your trading strategy. This capability allows you to manage trades based on liquidity shifts or imbalance corrections without needing a bias toward a specific direction.
🔵 Settings
The ICT Macros indicator offers various customization options, allowing users to tailor it to their specific needs. Below are the main settings:
Time Zone Mode : You can select one of the following options to define how time is displayed:
UTC : For traders who need to work with Universal Time.
Session Local Time : The local time corresponding to the London or New York markets.
Your Time Zone : You can specify your own time zone (e.g., "UTC-4:00").
Your Time Zone : If you choose "Your Time Zone," you can set your specific time zone. By default, this is set to UTC-4:00.
Show Range Time : This option allows you to display the time range of each session on the chart. If enabled, the exact start and end times of each interval are shown.
Show or Hide Time Ranges : Toggle on/off for visual clarity depending on user preference.
Custom Colors : Set distinct colors for each session, allowing users to personalize their chart based on their trading style.These settings allow you to adjust the key time intervals of each trading session to your preference and customize the time format according to your own needs.
🔵 Conclusion
The ICT Macros indicator is a powerful tool for traders, helping them to identify key time intervals where the market seeks liquidity or fills Fair Value Gaps (FVG), corrects imbalances, and breaks highs or lows. This tool is especially valuable for traders using liquidity-based strategies such as ICT 2022 or Silver Bullet.
One of the key features of this indicator is its support for Daylight Saving Time (DST), ensuring you are always in sync with the correct trading session timings without manual adjustments. This is particularly beneficial for traders operating across different time zones.
With ICT Macros, you can capitalize on crucial market opportunities during sensitive times, take advantage of imbalances, and enhance your trading strategies based on market volatility, liquidity shifts, and Fair Value Gaps.
Adv EMA Cloud v6 (ADX, Alerts)Summary:
This indicator provides a multi-faceted view of market trends using Exponential Moving Averages (EMAs) arranged in visually intuitive clouds, enhanced with an optional ADX-based range filter and configurable alerts for key market conditions. It aims to help traders quickly gauge trend alignment across short, medium, and long timeframes while filtering signals during potentially choppy market conditions.
Key Features:
Multiple EMAs: Displays 10-period (Fast), 20-period (Mid), and 50-period (Slow) EMAs.
Long-Term Trend Filter: Includes a 200-period EMA to provide context for the overall dominant trend direction.
Dual EMA Clouds:
Fast/Mid Cloud (10/20 EMA): Fills the area between the 10 and 20 EMAs. Defaults to Green when 10 > 20 (bullish short-term momentum) and Red when 10 < 20 (bearish short-term momentum).
Mid/Slow Cloud (20/50 EMA): Fills the area between the 20 and 50 EMAs. Defaults to Aqua when 20 > 50 (bullish mid-term trend) and Fuchsia when 20 < 50 (bearish mid-term trend).
Optional ADX Range Filter: Uses the Average Directional Index (ADX) to identify potentially non-trending or choppy markets. When enabled and ADX falls below a user-defined threshold, the EMA clouds will turn grey, visually warning that trend-following signals may be less reliable.
Configurable Alerts: Provides several built-in alert conditions using Pine Script's alertcondition function:
Confluence Condition: Triggers when a 10/20 EMA crossover occurs while both EMA clouds show alignment (both bullish/green/aqua or both bearish/red/fuchsia) and price respects the 200 EMA filter and the ADX filter indicates a trend (if filters are enabled).
MA Filter Cross: Triggers when price crosses above or below the 200 EMA filter line.
Full Alignment Start: Triggers on the first bar where full bullish or bearish alignment occurs (both clouds aligned + MA filter respected + ADX trending, if filters are enabled).
How It Works:
EMA Calculation: Standard Exponential Moving Averages are calculated for the 10, 20, 50, and 200 periods based on the closing price.
Cloud Creation: The fill() function visually shades the area between the 10 & 20 EMAs and the 20 & 50 EMAs.
Cloud Coloring: The color of each cloud is determined by the relationship between the two EMAs that define it (e.g., if EMA 10 is above EMA 20, the first cloud is bullish-colored).
ADX Filter Logic: The script calculates the ADX value. If the "Use ADX Trend Filter?" input is checked and the calculated ADX is below the specified "ADX Trend Threshold", the script considers the market potentially ranging.
ADX Visual Effect: During detected ranging periods (if the ADX filter is active), the plotCloud12Color and plotCloud23Color variables are assigned a neutral grey color instead of their normal bullish/bearish colors before being passed to the fill() function.
Alert Logic: Boolean variables track the specific conditions (crossovers, cloud alignment, filter positions, ADX state). The alertcondition() function creates triggerable alerts based on these pre-defined conditions.
Potential Interpretation (Not Financial Advice):
Trend Alignment: When both clouds share the same directional color (e.g., both bullish - Green & Aqua) and price is on the corresponding side of the 200 EMA filter, it may suggest a stronger, more aligned trend. Conversely, conflicting cloud colors may indicate indecision or transition.
Dynamic Support/Resistance: The EMA lines themselves (especially the 20, 50, and 200) can sometimes act as dynamic levels where price might react.
Range Warning: Greyed-out clouds (when ADX filter is enabled) serve as a visual warning that trend-based strategies might face increased difficulty or whipsaws.
Confluence Alerts: The specific confluence alerts signal moments where multiple conditions align (crossover + cloud agreement + filters), which some traders might view as higher-probability setups.
Customization:
All EMA lengths (10, 20, 50, 200) are adjustable via the Inputs menu.
The ADX length and threshold are configurable.
The MA Trend Filter and ADX Trend Filter can be independently enabled or disabled.
Disclaimer:
This indicator is provided for informational and educational purposes only. Trading financial markets involves significant risk. Past performance is not indicative of future results. Always conduct your own thorough analysis and consider your risk tolerance before making any trading decisions. This indicator should be used in conjunction with other analysis methods and tools. Do not trade based solely on the signals or visuals provided by this indicator.
Pulse of Cycle Oscillator"Pulse of Cycle" Oscillator: Logic and Usage
What Is It and How Does It Work?
The "Pulse of Cycle" is an oscillator that measures the cycles of price rises and falls, helping you spot overbought and oversold conditions. Unlike classic indicators, it doesn’t focus on how much the price moves but tracks its direction (up or down) like a "pulse." Here’s the logic:
Price Movement:
If the price rises compared to the previous bar, it adds +1.
If the price falls, it subtracts -1.
If the price stays the same, it adds 0.
Decay Factor: Each step, the previous value is multiplied by a factor (e.g., 0.9) to shrink it slightly. This keeps the oscillator from growing too big and focuses it on recent price action.
Signals: The oscillator moves around zero. When it crosses certain levels (e.g., 5 and 10), it warns you about overbought or oversold zones:
Weak Signal: Above ±5, the market might be stretching a bit.
Strong Signal: Above ±10, a reversal is more likely.
In short, it tracks the "rhythm" of price streaks (consecutive ups or downs) and signals when things might be getting extreme.
How It Looks on the Chart
Line: The oscillator moves around a zero line.
Colors:
Blue: Normal zone (between -5 and +5).
Orange: Weak overbought (+5 and up) or oversold (-5 and down).
Red: Strong overbought (+10 and up).
Lime: Strong oversold (-10 and down).
Threshold Lines: You’ll see lines at 0, ±5, and ±10 on the chart to show where you are.
How to Use It?
Here’s how to trade with this oscillator:
Buy Opportunity (Long Position):
When?: The oscillator drops below -5 (weak) or -10 (strong), then starts moving back toward zero. This suggests the price has hit a bottom and might rise.
Example: It falls to -12 (lime), then rises to -8. You could buy, expecting a bounce.
Tip: Wait for a green candle to confirm if you want to be safer.
Sell Opportunity (Short Position):
When?: The oscillator rises above +5 (weak) or +10 (strong), then starts dropping back toward zero. This indicates the price might have peaked and could fall.
Example: It hits +11 (red), then drops to +7. You could sell, expecting a decline.
Tip: Look for a red candle to confirm the turn.
Neutral Zone: If it’s between -5 and +5, the market is balanced. You can wait for a clearer signal.
Practical Steps to Use
Add to TradingView:
Paste the code into Pine Editor and click “Add to Chart.”
Adjust Settings (Optional):
Decay (0.9): Lower to 0.7 for faster response, raise to 0.95 for smoother movement.
Thresholds (5 and 10): Change them (e.g., 4 and 8) based on your market.
Watch Signals:
Follow the color changes and threshold crossings.
Set Alerts:
Right-click the oscillator > “Add Alert” to get notified on overbought/oversold signals.
Things to Watch Out For
Confirmation: Pair it with support/resistance levels or candlestick patterns for stronger signals.
Market Type: Works best in range-bound (sideways) markets. In strong trends (all up or down), signals might mislead.
Risk: Always use a stop loss—below the last low for buys, above the last high for sells.
Summary
The "Pulse of Cycle" is a simple yet powerful tool that tracks price movement streaks. Use it to catch reversals at strong signals (-10/+10) or get early warnings at weak signals (±5). The colors and lines on the chart make it easy to see when to act.
Checklist By TradeINskiChecklist By TradeINski
First Things First
This indicator is a supporting tool for trading momentum burst that is 2 Lynch setup by stock bee aka Pradeep Bonde.
Disclaimer: This indicator will not give any buy or sell signal. This is just a supporting tool to improve efficiency in my trading.
Apply Indicators and then open indicator settings and read the following simultaneously to understand better.
Default color settings are best suited for light themes. Which is also my personal preference.
Users can change most of the default options in settings according to their personal preference in settings.
When we open settings we can see 3 tabs that are {Inputs tab} {Style tab} {Visibility tab} each tab have its own options, Understand and use it accordingly.
Indicator will be only visible in the Daily time frame as its primary TF is daily. In the lower time frame nothing is plotted.
An indicator is plotted on an existing plane and overlaid on the existing plane.
Contents
My Checklist Lynch
Table Header Settings
Position
Size
Text Color
Background Color
“ON/OFF” Header “Text Box” “Info”
Table Content
Text Color
Background Color
“ON/OFF” R (1 - 10) “Text Box” T (1 - 10) “Text Box”
My Checklist - 2Lynch
This is the checklist I use while placing the trade just to make use of not missing anything based on predefined rules of the setup I trade.
2 - The stock should not be Up more than 2 days in a row, Minor movement can be acceptable.
L - The stock price movement should be linear, validation of established momentum
Y - Young trend in preference 1 - 3rd breakout from base
N - Narrow Range or -ve day before breakout
C - Consolidation should be narrow, linear and low volume. No more than one 4% breakdown.
H - The candle should close near high or at least 20% within when entered.
Table Headers Settings
Position - “Drop Down” with 9 different options which are self explanatory. Users can change the position of the table as per their preference.
Size - “Drop Down” with 6 different options which are self explanatory. Users can change the size of all the text printed in the table as per their preference.
Text Color - “Default Color is White” This setting is specifically only for header text. And users can change the text color of the header as per their preference.
Background Color - “Default Color is Blue” This setting is specifically only for header
background color. Users can change the background color of the header as per their preference.
“ON/OFF” Header “Text Box” “Info”
“Check Mark” - To show or hide the header that is “ON/OFF”.
“Header” - Heading of the table.
“Text Box” - Users can input as per their preference.
“Info” - Info symbol that shows short form and important note that is (Max 50 characteristics for all text boxes) .
Table Content
Text Color - “Default Color is White” This setting is specifically for table texts. And users can change the text color of the all content table texts as per their preference.
Background Color - “Default Color is black” This setting is specifically for content table texts background color. Users can change the background color of the header as per their preference.
“ON/OFF” R (1 - 10) “Text Box” T (1 - 10) “Text Box”
“Check Mark” - To show or hide the complete Row. Users have options and can change as per their preferences.
R (1-10) - “R” stands for Row and (1-10) is Number of rows available for users to enter text. Users have 10 different options.
“Text Box” - Place to enter text that users want to print on column 1 of the table.
T (1-10) - “T” stands for table and (1-10) is Number of text boxes available for users to enter text. Users have 10 different options.
“Text Box” - Place to enter text that users want to print on column 2 of the table.
Realtime FootprintThe purpose of this script is to gain a better understanding of the order flow by the footprint. To that end, i have added unusual features in addition to the standard features.
I use "Real Time 5D Profile by LucF" main engine to create basic footprint(profile type) and added some popular features and my favorites.
This script can only be used in realtime, because tradingview doesn't provide historical Bid/Ask date.
Bid/Ask date used this script are up/down ticks.
This script can only be used by time based chart (1m, 5m , 60m and daily etc)
This script use many labels and these are limited max 500, so you can't display many bars.
If you want to display foot print bars longer, turn off the unused sub-display function.
Default setting is footprint is 25 labels, IB count is 1, COT high and Ratio high is 1, COT low and Ratio low is 1 and Delta Box Ratio Volume is 1 , total 29.
plus UA , IB stripes , ladder fading mark use several labels.
///////// General Setting ///////////
Resets on Volume / Range bar
: If you want to use simple time based Resets on, please set Total Volume is 0.
Your timeframe is always the first condition. So if you set Total Volume is 1000, both conditions(Volume >= 1000 and your timeframe start next bar) must be met. (that is, new footprint bar doesn't start at when total volume = exactly 1000).
Ticks per row and Maximum row of Bar
: 1 is minimum size(tick). "Maximum row of Bar" decide the number of rows used in one footprint. 1 row is created from 1 label, so you need to reduce this number to display many footprints (Max label is 500).
Volume Filter and For Calculation and Display
: "Volume Filter" decide minimum size of using volume for this script.
"For Calculation and Display" is used to convert volume to an integer.
This script only use integer to make profile look better (I contained Bid number and Ask number in one row( one label) to saving labels. This require to make no difference in width by the number of digits and this script corresponds integers from 0 to 3 digits).
ex) Symbol average volume size is from 0.0001 to 0.001. You decide only use Volume >= 0.0005 by "Volume Filter".
Next, you convert volume to integer, by setting "For Calculation and Display" is 1000 (0.0005 * 1000 = 5).
If 0.00052 → 5.2 → 5, 0.00058 → 5.8 → 6 (Decimal numbers are rounded off)
This integer is used to all calculation in this script.
//////// Main Display ///////
Footprint, Total, Row Delta, Diagonal Delta and Profile
: "Footprint" display Ask and Bid per row. "Total" display Ask + Bid per row.
"Row Delta" display Ask - Bid per row. "Diagonal Delta" display Ask(row N) - Bid(row N -1) per row.
Profile display Total Volume(Ask + Bid) per row by using Block. Profile Block coloring are decided by Row Delta value(default: positive Row Delta (Ask > Bid) is greenish colors and negative Row Delta (Ask < Bid) is reddish colors.)
Volume per Profile Block, Row Imbalance Ratio and Delta Bull/Bear/Neutral Colors
: "Volume per Profile Block" decide one block contain how many total volume.
ex) When you set 20, Total volume 70 display 3 block.
The maximum number of blocks that can be used per low is 20.
So if you set 20, Total volume 400 is 20 blocks. total volume 800 is 20 blocks too.
"Row Imbalance Ratio" decide block coloring. The row imbalance is that the difference between Ask and Bid (row delta) is large.
default is x3, x2 and x1. The larger the difference, the brighter the color.
ex) Ask 30 Bid 10 is light green. Ask 20 Bid 10 is green. Ask 11 Bid 10 is dark green.
Ask 0 Bid 1 is light red. Ask 1 Bid 2 is red. ask 30 Bid 59 is dark green.
Ask 10 Bid 10 is neutral color(gray)
profile coloring is reflected same row's other elements(Ask, Bid, Total and Delta) too.
It's because one label can only use one text color.
/////// Sub Display ///////
Delta, total and Commitment of Traders
: "Delta" is total Ask - total Bid in one footprint bar. Total is total Ask + total Bid in one footprint bar.
"Commitment of traders" is variation of "Delta". COT High is reset to 0 when current highest is touched. COT Low is opposite.
Basic concept of Delta is to compare price with Delta. Ordinary, when price move up, delta is positive. Price move down is negative delta.
This is because market orders move price and market orders are counted by Delta (although this description is not exactly correct).
But, sometimes prices do not move even though many market orders are putting pressure on price , or conversely, price move strongly without many market orders.
This is key point. Big player absorb market orders by iceberg order(Subdivide large orders and pretend to be small limit orders.
Small limit orders look weak in the order book, but they are added each time you fill, so they are more powerful than they look.), so price don't move.
On the other hand, when the price is moving easily, smart players may be aiming to attract and counterattack to a better price for them.
It's more of a sport than science, and there's always no right response. Pay attention to the relationship between price, volume and delta.
ex) If COT Low is large negative value, it means many sell market orders is coming, but iceberg order is absorbing their attack at limit order.
you should not do buy entry, only this clue. but this is one of the hints.
"Delta, Box Ratio and Total texts is contained same label and its color are "Delta" coloring. Positive Delta is Delta Bull color(green),Negative Delta is Delta Bear Color
and Delta = 0 is Neutral Color(gray). When Delta direction and price direction are opposite is Delta Divergence Color(yellow).
I didn't add the cumulative volume delta because I prefer to display the CVD line on the price chart rather than the number.
Box Ratio , Box Ratio Divisor and Heavy Box Ratio Ratio
: This is not ordinary footprint features, but I like this concept so I added.
Box Ratio by Richard W. Arms is simple but useful tool. calculation is "total volume (one bar) divided by Bar range (highest - lowest)."
When Bull and bear are fighting fiercely this number become large, and then important price move happen.
I made average BR from something like 5 SMA and if current BR exceeds average BR x (Heavy Box Ratio Ratio), BR box mark will be filled.
Box Ratio Divisor is used to good looking display(BR multiplied by Box Ratio Divisor is rounded off and displayed as an integer)
Diagonal Imbalance Count , D IB Mark and D IB Stripes
: Diagonal Imbalance is defined by "Diagonal Imbalance Ratio".
ex) You set 2. When Ask(row N) 30 Bid(row N -1)10, it's 30 > 10*2, so positive Diagonal Imbalance.
When Ask(row N) 4 Bid(row N -1)9, it's 4*2 < 9, so negative Diagonal Imbalance.
This calculation does not use equals to avoid Ask(row N) 0 Bid(row N -1)0 became Diagonal Imbalance.
Ask(row N) 0 Bid(row N -1)0, it's 0 = 0*2, not Diagonal Imbalance. Ask(row N) 10 Bid(row N -1)5, it's 10 = 5*2, not Diagonal Imbalance.
"D IB Mark" emphasize Ask or Bid number which is dominant side(Winner of Diagonal Imbalance calculation), by under line.
"Diagonal Imbalance Count" compare Ask side D IB Mark to Bid side D IB Mark in one footprint.
Coloring depend on which is more aggressive side (it has many IB Mark) and When Aggressive direction and price direction are opposite is Delta Divergence Color(yellow).
"D IB Stripes" is a function that further emphasizes with an arrow Mark, when a DIB mark is added on the same side for three consecutive row. Three consecutive arrow is added at third row.
Unfinished Auction, Ratio Bounds and Ladder fading Mark
: "Unfinished Auction" emphasize highest or lowest row which has both Ask and Bid, by Delta Divergence Color(yellow) XXXXXX mark.
Unfinished Auction sometimes has magnet effect, price may touch and breakout at UA side in the future.
This concept is famous as profit taking target than entry decision.
But, I'm interested in the case that Big player make fake breakout at UA side and trapped retail traders, and then do reversal with retail traders stop-loss hunt.
Anyway, it's not stand alone signal.
"Ratio Bounds" gauge decrease of pressure at extreme price. Ratio Bounds High is number which second highest ask is divided by highest ask.
Ratio Bounds Low is number which second lowest bid is divided by lowest bid. The larger the number, the less momentum the price has.
ex)first footprint bar has Ratio Bounds Low 2, second footprint bar has RBL 4, third footprint bar has RBL 20.
This indicates that the bear's power is gradually diminishing.
"Ladder fading mark" emphasizes the decrease of the value in 3 consecutive row at extreme price. I added two type Marks.
Ask/Bid type(triangle Mark) is Ask/Bid values are decreasing of three consecutive row at extreme price.
Row Imbalance type(Diamond Mark) are row Imbalance values are decreasing of three consecutive row at extreme price.
ex)Third lowest Bid 40, second lowest Bid 10 and lowest Bid 5 have triangle up Mark. That is bear's power is gradually diminishing.
(This Mark only check Bid value at lowest price and Ask value at highest price).
Third highest row delta + 60, second highest row delta + 5, highest delta - 20 have diamond Mark. That is Bull's power is gradually diminishing.
Sub display use Delta colors at bottom of Sub display section.
////// Candle & POC /////////
candle and POC
: Ordinary, "POC" Point of Control is row of largest total volume, but this script'POC is volume weighted average.
This is because the regular POC was visually displayed by the profile ,and I was influenced LucF's ideas.
POC coloring is decided in relation to the previous POC. When current POC is higher than previous POC, color is UP Bar Color(green).
In the opposite case, Down Bar color is used.
POC Divergence Color is used when Current POC is up but current bar close is lower than open (Down price Bar),or in the opposite case.
POC coloring has option also highlight background by Delta Divergence Color(yellow). but bg color is displayed at your time frame current price bar not current footprint bar.
The basic explanation is over.
I add some image to promote understanding basic ideas.
EAOBS by MIGVersion 1
1. Strategy Overview Objective: Capitalize on breakout movements in Ethereum (ETH) price after the Asian open pre-market session (7:00 PM–7:59 PM EST) by identifying high and low prices during the session and trading breakouts above the high or below the low.
Timeframe: Any (script is timeframe-agnostic, but align with session timing).
Session: Pre-market session (7:00 PM–7:59 PM EST, adjustable for other time zones, e.g., 12:00 AM–12:59 AM GMT).
Risk-Reward Ratios (R:R): Targets range from 1.2:1 to 5.2:1, with a fixed stop loss.
Instrument: Ethereum (ETH/USD or ETH-based pairs).
2. Market Setup Session Monitoring: Monitor ETH price action during the pre-market session (7:00 PM–7:59 PM EST), which aligns with the Asian market open (e.g., 9:00 AM–9:59 AM JST).
The script tracks the highest high and lowest low during this session.
Breakout Triggers: Buy Signal: Price breaks above the session’s high after the session ends (7:59 PM EST).
Sell Signal: Price breaks below the session’s low after the session ends.
Visualization: The session is highlighted on the chart with a white background.
Horizontal lines are drawn at the session’s high and low, extended for 30 bars, along with take-profit (TP) and stop-loss (SL) levels.
3. Entry Rules Long (Buy) Entry: Enter a long position when the price breaks above the session’s high price after 7:59 PM EST.
Entry price: Just above the session high (e.g., add a small buffer, like 0.1–0.5%, to avoid false breakouts, depending on volatility).
Short (Sell) Entry: Enter a short position when the price breaks below the session’s low price after 7:59 PM EST.
Entry price: Just below the session low (e.g., subtract a small buffer, like 0.1–0.5%).
Confirmation: Use a candlestick close above/below the breakout level to confirm the entry.
Optionally, add volume confirmation or a momentum indicator (e.g., RSI or MACD) to filter out weak breakouts.
Position Size: Calculate position size based on risk tolerance (e.g., 1–2% of account per trade).
Risk is determined by the stop-loss distance (10 points, as defined in the script).
4. Exit Rules Take-Profit Levels (in points, based on script inputs):TP1: 12 points (1.2:1 R:R).
TP2: 22 points (2.2:1 R:R).
TP3: 32 points (3.2:1 R:R).
TP4: 42 points (4.2:1 R:R).
TP5: 52 points (5.2:1 R:R).
Example for Long: If session high is 3000, TP levels are 3012, 3022, 3032, 3042, 3052.
Example for Short: If session low is 2950, TP levels are 2938, 2928, 2918, 2908, 2898.
Strategy: Scale out of the position (e.g., close 20% at TP1, 20% at TP2, etc.) or take full profit at a preferred TP level based on market conditions.
Stop-Loss: Fixed at 10 points from the entry.
Long SL: Session high - 10 points (e.g., entry at 3000, SL at 2990).
Short SL: Session low + 10 points (e.g., entry at 2950, SL at 2960).
Trailing Stop (Optional):After reaching TP2 or TP3, consider trailing the stop to lock in profits (e.g., trail by 10–15 points below the current price).
5. Risk Management per Trade: Limit risk to 1–2% of your trading account per trade.
Calculate position size: Account Size × Risk % ÷ (Stop-Loss Distance × ETH Price per Point).
Example: $10,000 account, 1% risk = $100. If SL = 10 points and 1 point = $1, position size = $100 ÷ 10 = 0.1 ETH.
Daily Risk Limit: Cap daily losses at 3–5% of the account to avoid overtrading.
Maximum Exposure: Avoid taking both long and short positions simultaneously unless using separate accounts or strategies.
Volatility Consideration: Adjust position size during high-volatility periods (e.g., major news events like Ethereum upgrades or macroeconomic announcements).
6. Trade Management Monitoring :Watch for breakouts after 7:59 PM EST.
Monitor price action near TP and SL levels using alerts or manual checks.
Trade Duration: Breakout lines extend for 30 bars (script parameter). Close trades if no TP or SL is hit within this period, or reassess based on market conditions.
Adjustments: If the market shows strong momentum, consider holding beyond TP5 with a trailing stop.
If the breakout fails (e.g., price reverses before TP1), exit early to minimize losses.
7. Additional Considerations Market Conditions: The 7:00 PM–7:59 PM EST session aligns with the Asian market open (e.g., Tokyo Stock Exchange open at 9:00 AM JST), which may introduce higher volatility due to Asian trading activity.
Avoid trading during low-liquidity periods or extreme volatility (e.g., major crypto news).
Check for upcoming events (e.g., Ethereum network upgrades, ETF decisions) that could impact price.
Backtesting: Test the strategy on historical ETH data using the session high/low breakouts for the 7:00 PM–7:59 PM EST window to validate performance.
Adjust TP/SL levels based on backtest results if needed.
Broker and Fees: Use a low-fee crypto exchange (e.g., Binance, Kraken, Coinbase Pro) to maximize R:R.
Account for trading fees and slippage in your position sizing.
Time zone Adjustment: Adjust session time input for your time zone (e.g., "0000-0059" for GMT).
Ensure your trading platform’s clock aligns with the script’s time zone (default: America/New_York).
8. Example Trade Scenario: Session (7:00 PM–7:59 PM EST) records a high of 3050 and a low of 3000.
Long Trade: Entry: Price breaks above 3050 (e.g., enter at 3051).
TP Levels: 3063 (TP1), 3073 (TP2), 3083 (TP3), 3093 (TP4), 3103 (TP5).
SL: 3040 (3050 - 10).
Position Size: For a $10,000 account, 1% risk = $100. SL = 11 points ($11). Size = $100 ÷ 11 = ~0.09 ETH.
Short Trade: Entry: Price breaks below 3000 (e.g., enter at 2999).
TP Levels: 2987 (TP1), 2977 (TP2), 2967 (TP3), 2957 (TP4), 2947 (TP5).
SL: 3010 (3000 + 10).
Position Size: Same as above, ~0.09 ETH.
Execution: Set alerts for breakouts, enter with limit orders, and monitor TPs/SL.
9. Tools and Setup Platform: Use TradingView to implement the Pine Script and visualize breakout levels.
Alerts: Set price alerts for breakouts above the session high or below the session low after 7:59 PM EST.
Set alerts for TP and SL levels.
Chart Settings: Use a 1-minute or 5-minute chart for precise session tracking.
Overlay the script to see high/low lines, TP levels, and SL levels.
Optional Indicators: Add RSI (e.g., avoid overbought/oversold breakouts) or volume to confirm breakouts.
10. Risk Warnings Crypto Volatility: ETH is highly volatile; unexpected news can cause rapid price swings.
False Breakouts: Breakouts may fail, especially in low-volume sessions. Use confirmation signals.
Leverage: Avoid high leverage (e.g., >5x) to prevent liquidation during volatile moves.
Session Accuracy: Ensure correct session timing for your time zone to avoid misaligned entries.
11. Performance Tracking Journaling :Record each trade’s entry, exit, R:R, and outcome.
Note market conditions (e.g., trending, ranging, news-driven).
Review: Weekly: Assess win rate, average R:R, and adherence to the plan.
Monthly: Adjust TP/SL or session timing based on performance.
Institutional Volume Profile# Institutional Volume Profile (IVP) - Advanced Volume Analysis Indicator
## Overview
The Institutional Volume Profile (IVP) is a sophisticated technical analysis tool that combines traditional volume profile analysis with institutional volume detection algorithms. This indicator helps traders identify key price levels where significant institutional activity has occurred, providing insights into market structure and potential support/resistance zones.
## Key Features
### 🎯 Volume Profile Analysis
- **Point of Control (POC)**: Identifies the price level with the highest volume activity
- **Value Area**: Highlights the price range containing a specified percentage (default 70%) of total volume
- **Multi-Row Distribution**: Displays volume distribution across 10-50 price levels for detailed analysis
- **Customizable Period**: Analyze volume profiles over 10-500 bars
### 🏛️ Institutional Volume Detection
- **Pocket Pivot Volume (PPV)**: Detects bullish institutional buying when up-volume exceeds recent down-volume peaks
- **Pivot Negative Volume (PNV)**: Identifies bearish institutional selling when down-volume exceeds recent up-volume peaks
- **Accumulation Detection**: Spots potential accumulation phases with high volume and narrow price ranges
- **Distribution Analysis**: Identifies distribution patterns with high volume but minimal price movement
### 🎨 Visual Customization Options
- **Multiple Color Schemes**: Heat Map, Institutional, Monochrome, and Rainbow themes
- **Bar Styles**: Solid, Gradient, Outlined, and 3D Effect rendering
- **Volume Intensity Display**: Visual intensity based on volume magnitude
- **Flexible Positioning**: Left or right side profile placement
- **Current Price Highlighting**: Real-time price level indication
### 📊 Advanced Visual Features
- **Volume Labels**: Display volume amounts at key price levels
- **Gradient Effects**: Multi-step gradient rendering for enhanced visibility
- **3D Styling**: Shadow effects for professional appearance
- **Opacity Control**: Adjustable transparency (10-100%)
- **Border Customization**: Configurable border width and styling
## How It Works
### Volume Distribution Algorithm
The indicator analyzes each bar within the specified period and distributes its volume proportionally across the price levels it touches. This creates an accurate representation of where trading activity has been concentrated.
### Institutional Detection Logic
- **PPV Trigger**: Current up-bar volume > highest down-volume in lookback period + above volume MA
- **PNV Trigger**: Current down-bar volume > highest up-volume in lookback period + above volume MA
- **Accumulation**: High volume + narrow range + bullish close
- **Distribution**: Very high volume + minimal price movement
### Value Area Calculation
Starting from the POC, the algorithm expands both upward and downward, adding volume until reaching the specified percentage of total volume (default 70%).
## Configuration Parameters
### Profile Settings
- **Profile Period**: 10-500 bars (default: 50)
- **Number of Rows**: 10-50 levels (default: 24)
- **Profile Width**: 10-100% of screen (default: 30%)
- **Value Area %**: 50-90% (default: 70%)
### Institutional Analysis
- **PPV Lookback Days**: 5-20 periods (default: 10)
- **Volume MA Length**: 10-200 periods (default: 50)
- **Institutional Threshold**: 1.0-2.0x multiplier (default: 1.2)
### Visual Controls
- **Bar Style**: Solid, Gradient, Outlined, 3D Effect
- **Color Scheme**: Heat Map, Institutional, Monochrome, Rainbow
- **Profile Position**: Left or Right side
- **Opacity**: 10-100%
- **Show Labels**: Volume amount display toggle
## Interpretation Guide
### Volume Profile Elements
- **Thick Horizontal Bars**: High volume nodes (strong support/resistance)
- **Thin Horizontal Bars**: Low volume nodes (weak levels)
- **White Line (POC)**: Strongest support/resistance level
- **Blue Highlighted Area**: Value Area (fair value zone)
### Institutional Signals
- **Blue Triangles (PPV)**: Bullish institutional buying detected
- **Orange Triangles (PNV)**: Bearish institutional selling detected
- **Color-Coded Bars**: Different colors indicate institutional activity types
### Color Scheme Meanings
- **Heat Map**: Red (high volume) → Orange → Yellow → Gray (low volume)
- **Institutional**: Blue (PPV), Orange (PNV), Aqua (Accumulation), Yellow (Distribution)
- **Monochrome**: Grayscale intensity based on volume
- **Rainbow**: Color-coded by price level position
## Trading Applications
### Support and Resistance
- POC acts as dynamic support/resistance
- High volume nodes indicate strong price levels
- Low volume areas suggest potential breakout zones
### Institutional Activity
- PPV above Value Area: Strong bullish signal
- PNV below Value Area: Strong bearish signal
- Accumulation patterns: Potential upward breakouts
- Distribution patterns: Potential downward pressure
### Market Structure Analysis
- Value Area defines fair value range
- Profile shape indicates market sentiment
- Volume gaps suggest potential price targets
## Alert Conditions
- PPV Detection at current price level
- PNV Detection at current price level
- PPV above Value Area (strong bullish)
- PNV below Value Area (strong bearish)
## Best Practices
1. Use multiple timeframes for confirmation
2. Combine with price action analysis
3. Pay attention to volume context (above/below average)
4. Monitor institutional signals near key levels
5. Consider overall market conditions
## Technical Notes
- Maximum 500 boxes and 100 labels for optimal performance
- Real-time calculations update on each bar close
- Historical analysis uses complete bar data
- Compatible with all TradingView chart types and timeframes
---
*This indicator is designed for educational and informational purposes. Always combine with other analysis methods and risk management strategies.*
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
random_values█ OVERVIEW
This library provides helper functions for generating random values of various types, including numbers, letters, words, booleans, and arrays. It simplifies the creation of random data within Pine Script™ for testing, simulations, or other applications.
█ HOW TO USE
Import the library into your script:
import kaigouthro/random_values/1 as rv
Then, use the functions provided:
// Get a random integer between 5 and 15
int randInt = rv.intVal(5, 15)
// Generate a random word with 8 characters
string randWord = rv.word(8)
// Create a boolean array with 5 elements
array randBoolArray = rv.boolArray(5)
// And other options! See below for details.
█ FEATURES
• num(float min, float max) : Returns a random float between *min* and *max*. (Internal helper function, not exported).
• letter() : Returns a random lowercase letter (a-z).
• word(int size = 0) : Returns a random word. *size* specifies the length (default: random length between 3 and 10).
• words(int size = 20) : Returns a string of random words separated by spaces, where *size* specifies the number of words.
• boolVal() : Returns a random boolean (true or false).
• floatVal(float min = 0, float max = 100, int precision = 2) : Returns a random float with specified *min*, *max*, and *precision*.
• intVal(int min = 1, int max = 100) : Returns a random integer between *min* and *max*.
• stringArray(int size = 0) : Returns an array of random words. *size* specifies the array length (default: random between 3 and 10).
• floatArray(int size = 0, float min = 0, float max = 100, int precision = 2) : Returns an array of random floats with specified parameters. *size* determines the array length.
• intArray(int size = 0, int min = 1, int max = 100) : Returns an array of random integers with specified parameters. *size* determines the array length.
• boolArray(int size = 0) : Returns an array of random booleans. *size* specifies the array length (default: random between 3 and 10).
█ NOTES
* This library uses the `kaigouthro/into/2` library for type conversions. Make sure it's available.
* Default values are provided for most function parameters, offering flexibility in usage.
█ LICENSE
This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
```
**Changes and Rationale:**
* **OVERVIEW:** Clearly states the library's purpose.
* **HOW TO USE:** Provides essential import and usage instructions with Pine Script™ examples.
* **FEATURES:** Details each function with its parameters, types, and descriptions. Emphasizes *size*, *min*, *max*, and *precision* as common input parameters using italics. Uses custom bulleted lists.
* **NOTES:** Includes important information about dependencies and defaults.
* **LICENSE:** Directly links to the license URL using the proper ` ` tag.
* **Formatting:** Uses full block and em space for section titles, consistent bolding, and improved spacing for readability. Removes unnecessary blank lines.
This format improves clarity, making the library documentation easy to understand for TradingView users. Remember to test the rendering on TradingView to catch any formatting issues.
Library "random_values"
A library containing Random value generating helper functions.
letter()
Random letter generator.
Returns: (string) A random lowercase letter.
word(size)
Random word generator.
Parameters:
size (int) : (int) The desired length of the word. If 0 or not provided, a random length between 3 and 10 is used.
Returns: (string) A random word.
words(size)
Random words generator.
Parameters:
size (int) : (int) The number of words to generate. If 0 or not provided, a random number between 3 and 10 is used.
Returns: (string) A string of random words separated by spaces.
boolVal()
Random boolean generator.
Returns: (bool) A random boolean value (true or false).
floatVal(min, max, precision)
Random float number generator.
Parameters:
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (float) A random float number.
intVal(min, max)
Random integer number generator.
Parameters:
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (int) A random integer number.
stringArray(size)
Random string array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random words.
floatArray(size, min, max, precision)
Random float array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (array) An array of random float numbers.
intArray(size, min, max)
Random integer array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (array) An array of random integer numbers.
boolArray(size)
Random boolean array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random boolean values.
Financials Score All Description of the "Financials Score All" Script
This Pine Script calculates a financial score for a specific stock, based on various financial metrics. The purpose is to provide a comprehensive numerical score that reflects the financial health of the stock. The score is calculated using multiple financial indicators, including profitability, valuation, debt management, and liquidity. Here’s a breakdown of what each part of the script does:
period = input.string('FQ', 'Period', options= )
FQ refers to Quarterly financial data.
FY refers to Fiscal Year financial data.
Financial Metrics:
The script uses various financial metrics to calculate the score. These are obtained via request.financial, which retrieves financial data for the stock from TradingView's database. Below are the metrics used:
opmar (Operating Margin): Measures the company's profitability as a percentage of revenue.
eps (Earnings Per Share): Represents the portion of a company's profit allocated to each outstanding share.
eps_ttm (Earnings Per Share – Trailing Twelve Months): EPS over the most recent 12 months.
pe_ratio (Price-to-Earnings Ratio): A measure of the price investors are willing to pay for a stock relative to its earnings.
pb_ratio (Price-to-Book Ratio): A valuation ratio comparing a company’s market value to its book value.
de_ratio (Debt-to-Equity Ratio): A measure of the company’s financial leverage, showing how much debt it has compared to shareholders' equity.
roe_pb (Return on Equity Adjusted to Book): Measures the company's profitability relative to its book value.
fcf_per_share (Free Cash Flow per Share): Represents the free cash flow available for dividends, debt reduction, or reinvestment, per share.
pfcf_ratio (Price-to-Free-Cash-Flow Ratio): A measure comparing a company’s market value to its free cash flow.
current_ratio (Current Ratio): A liquidity ratio that measures a company's ability to pay short-term obligations with its current assets.
RSI Calculation:
The script calculates the Relative Strength Index (RSI) for the stock using an 8-period lookback:
rsi = ta.rsi(close, 8)
Score Calculation:
The script calculates a total score by adding points based on the values of the financial metrics. Each metric is checked against a condition, and if the condition is met, the score is incremented:
If the Operating Margin (opmar) is greater than 20, the score is incremented by 20 points.
If Earnings Per Share (EPS) is positive, 10 points are added.
If the P/E ratio is between 0 and 20, 10 points are added.
If the P/B ratio is less than 3, 10 points are added.
If the Debt-to-Equity ratio is less than 0.8, 10 points are added.
If the Return on Equity Adjusted to Book is greater than 10, 10 points are added.
If the P/FCF ratio is between 0 and 15, 10 points are added.
If the Current Ratio is greater than 1.61, 10 points are added.
If the RSI is less than 35, 10 points are added.
The score is accumulated based on these conditions and stored in the total_score variable.
Displaying the Total Score:
Finally, the total score is plotted on the chart:
Summary of How It Works:
This script calculates a financial score for a stock using a variety of financial indicators. Each metric has a threshold, and when the stock meets certain criteria (for example, a good operating margin, a healthy debt-to-equity ratio, or a low P/E ratio), points are added to the overall score. The result is a single numerical value that reflects the financial health of the stock.
This score can help traders or investors identify companies with strong financials, or serve as a comparison tool between different stocks based on their financial health.
Generally >60 is the best stocks for med and long term trades
ICT Macros [LuxAlgo]The ICT Macros indicator aims to highlight & classify ICT Macros, which are time intervals where algorithmic trading takes place to interact with existing liquidity or to create new liquidity.
🔶 SETTINGS
🔹 Macros
Macro Time options (such as '09:50 AM 10:10'): Enable specific macro display.
Top Line , Mid Line , Bottom Line and Extending Lines options: Controls the lines for the specific macro.
🔹 Macro Classification
Length : A length to detect Market Structure Brakes and classify macro type based on detection.
Swing Area : Swing or Liquidity Area selection, highest/lowest of the wick or the candle bodies.
Accumulation , Manipulation and Expansion color options for the classified macros.
🔹 Others
Macro Texts : Controls both the size and the visibility of the macro text.
Alert Macro Times in Advance (Minutes) : This option will plot a vertical line presenting the start of the next macro time. The line will not appear all the time, but it will be there based on remaining minutes specified in the option.
Daylight Saving Time (DST) : Adjust time appropriate to Daylight Saving Time of the specific region.
🔶 USAGE
A macro is a way to automate a task or procedure which you perform on a regular basis.
In the context of ICT's teachings, a macro is a small program or set of instructions that unfolds within an algorithm, which influences price movements in the market. These macros operate at specific times and can be related to price runs from one level to another or certain market behaviors during specific time intervals. They help traders anticipate market movements and potential setups during specific time intervals.
To trade these effectively, it is important to understand the time of day when certain macros come into play, and it is strongly advised to introduce the concept of liquidity in your analysis.
Macros can be classified into three categories where the Macro classification is calculated based on the Market Structure prior to macro and the Market Structure during the macro duration:
Manipulation Macro
Manipulation macros are characterized by liquidity being swept both on the buyside and sellside.
Expansion Macro
Expansion macros are characterized by liquidity being swept only on the buyside or sellside. Prices within these macros are highly correlated with the overall trend.
Accumulation Macro
Accumulation macros are characterized by an accumulation of liquidity. Prices within these macros tend to range.
The script returns the maximum/minimum price values reached during the macro interval alongside the average between the maximum/minimum and extends them until a new macro starts. These levels can act as supports and resistances.
🔶 DETAILS
All required data for the macro detection and classification is retrieved using 1 minute data sets, this includes candles as well as pivot/swing highs and lows. This approach guarantees the visually presented objects are same (same highs/lows) on higher timeframes as well as the macro classification remain same as it is in 1 min charts.
8 Macros can be displayed by the script (4 are enabled by default):
02:33 AM 03:00 London Macro
04:03 AM 04:30 London Macro
08:50 AM 09:10 New York Macro
09:50 AM 10:10 New York Macro
10:50 AM 11:10 New York Macro
11:50 AM 12:10 New York Launch Macro
13:10 PM 13:40 New York Macro
15:15 PM 15:45 New York Macro
🔶 ALERTS
When an alert is configured, the user will have the ability to be notified in advance of the next Macro time, where the value specified in 'Alert Macro Times in Advance (Minutes)' option indicates how early to be notified.
🔶 LIMITATIONS
The script is supported on 1 min, 3 mins and 5 mins charts.
🔶 RELATED SCRIPTS
ATR Table 2.0ATR Table 2.0
This script was created in order to display a table that "calculates" how far the price can go on the current day .
The script is a table with 3 lines that calculates:
First Line - Day TR: The True Range of the current day ( - , including an Opening GAP if it exists);
Second Line - 10 Day ATR: The Average True Range of the asset (including Opening GAPs) for the last 10 days;
Third LIne - Range Consumed: How much of the 10 Day ATR it was consumed on the current day.
Example of how to use the information on the table and the understanding of it's purpose:
1) Supose you are day trading an asset that, during the last 10 days, have moved around $1.00 a day - This is the 10 Day ATR.
2) On this day, after 2 hours of the opening market, the price have already moved $0.50 (supose that it has moved $0.30 up and $0.35 down from the close of the prior day and the price is now near the close of the prior day).
3) In this situation, knowing that the price often moves around $1.00 a day, and knowing that it already moved $0.65 ($0.30 up and $0.35 down based on the close of the prior day), you may pay attention when the price breaksthrough the max or the min of the day, cause it can still move $0.35 in that direction ($1.00 - $0.65).
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ATR Table 2.0
Esse script foi criado para disponibilizar uma tabela que "calcula" quanto o preço pode andar ainda no dia em questão .
O script é uma tabela com 3 linhas que calcula:
Primeira Linha - TR do Dia: O Range Verdadeira do dia em questão ( - , incluindo GAP de Abertura se for o caso);
Segunda Linha - ATR de 10 Dias: A média do Range Verdadeira do ativo (incluindo GAPs de abertura) dos últimos 10 dias;
Terceira Linha - Range Consumido: O quanto do ATR de 10dias já foi consumido no dia em questão.
Exemplo de como usar essa informação na tabela e o entendimento do seu propósito:
1) Suponha que você está realizando day trade de um ativo que, durante os últimos 10 dias, se move em torno de $1.00 por dia. Esse é o ATR de 10 dias.
2) Nesse dia, após 2 horas da abertura do pregão, o preço já se moveu $.050 (suponhamos que ele tenha se moveu $0.30 para cima e $0.35 para baixo a partir do fechamento do dia anterior e agora o preço está próximo do fechamento do dia anterior).
3) Nessa situação, sabendo que o preço se move por volta de $1.00 por dia, e sabendo que ele já se moveu $0.65 ($0.30 pra cima e $0.35 pra baixo a partir do fechamento do dia anterior), você deve se atentar para quando o preço romper a máxima ou a mínima do dia, pois ele pode se mover ainda $.035 na direção do rompimento ($1.00 - $0.65).
