Williams %R Color MapThis script is used to have a quick view for my triple screen trading system.
I use it in 1 hour chart so that the higher timeframe is 5-hour and daily.
Visual for the current price on which fib area of 5-hour and daily chart.
Cari skrip untuk "williams"
Williams Gator Oscillator// The Gator Oscillator histogram above zero shows the absolute difference between blue and red lines of Alligator indicator,
// while histogram below zero shows the absolute difference between red and green lines.
//
// There are green and red bars on the Gator Oscillator histograms.
// A green bar appears when its value is higher than the value of the previous bar.
// A red bars appears when its value is lower than the value of the previous bar.
//
// Gator Oscillator helps to better visualize the upcoming changes in the trends: to know when Alligator sleeps, eats, fills //out and is about to go to sleep.
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.
BW MFI fixed v6Bill Williams MFI
Sure! Here’s an English description of the indicator you have:
---
### Bill Williams Market Facilitation Index (MFI) — Indicator Description
This indicator implements the **Market Facilitation Index (MFI)** as introduced by Bill Williams. The MFI measures the market's willingness to move the price by comparing the price range to the volume.
---
### How it works:
* **MFI Calculation:**
The MFI is calculated as the difference between the current bar’s high and low prices divided by the volume of that bar:
$$
\text{MFI} = \frac{\text{High} - \text{Low}}{\text{Volume}}
$$
* **Color Coding Logic:**
The indicator compares the current MFI and volume values to their previous values and assigns colors to visualize market conditions according to Bill Williams’ methodology:
| Color | Condition | Market Interpretation |
| ----------- | ------------------ | --------------------------------------------------------------------------------------------- |
| **Green** | MFI ↑ and Volume ↑ | Strong trend continuation or acceleration (increased price movement supported by volume) |
| **Brown** | MFI ↓ and Volume ↓ | Trend weakening or possible pause (both price movement and volume are decreasing) |
| **Blue** | MFI ↑ and Volume ↓ | Possible false breakout or lack of conviction (price moves but volume decreases) |
| **Fuchsia** | MFI ↓ and Volume ↑ | Market indecision or battle between bulls and bears (volume rises but price movement shrinks) |
| **Gray** | None of the above | Neutral or unchanged market condition |
* **Display:**
The indicator plots the MFI values as colored columns on a separate pane below the price chart, providing a visual cue of the market’s behavior.
---
### Purpose:
This tool helps traders identify changes in market momentum and the strength behind price moves, providing insight into when trends might accelerate, weaken, or potentially reverse.
---
If you want, I can help you write a more detailed user guide or trading strategy based on this indicator!
COT IndexReference:
Trade Stocks and Commodities with the Insiders
Secrets of the COT Report by Larry Williams pg34
The equation is as below:
Current week's value- Lowest value of last three years
---------------------------------------------------------------------------- X 100%
Highest high of last three years-Lowest low of last three years
According to Larry Williams, traders should follow commercials direction. When the commercial index line (yellow line) is above 80, this indicates commercials are bullish. Hence, traders can look for potential buy setup. Conversely, when commercials index line (yellow line) is below 20, this indicates commercials are bearish, we can look for sell setup.
Do note that this is only applicable on Weekly chart as COT reports come out on weekly basis.
Modification from the original COT index from Larry Williams:
1) I've added 1year and 6months period, so traders maybe can look for pullback using shorter period. By default, Larry Williams uses 3 years Commercial index.
2) I've added non-commercials and retail traders index, they basically trade opposite way of commercials.
This indicator should not be used as a timing tool or entry tool, you can use it as your weekly or monthly bias tool. For more information, please read the books. Feel free to modify the code, if u have a better version of this, you may share to me if you want, I will be very grateful!
Setup Max e Min Larry WilliansLarry Williams used this system to win the trading championship
Hello friends, I bring a script with a trading strategy to be used in futures such as Index, Forex and Commodities. Developed by famous trader Larry Williams.
In them we use two 3-period Simple Moving Averages (Arithmetic) (one with the high price, the other with the low price), and a 21-period Moving Average (Arithmetic) to determine the trend. This will form an average channel with the prices of the maximums and minimums of the last three candles.
Best time charts use the strategy: from 5 minutes to 60 minutes.
This strategy is quite simple. The 21 Moving Average will color according to the trend (Green for bullish, Red for bearish and Gray for transitions). The Script will signal the entry according to the trend by the colors of the candles and also by the signal:
When green, the buy will be on the crossing of the lower Moving Average crossing the candlestick, and the exit will be on the crossing of the candlestick on the next Upper Moving Average.
When red, the sell will be at the crossing of the Upper Moving Average crossing the candlestick, and the exit will be at the crossing of the candlestick on the next Lower Moving Average.
When the Script signals the candle with a purple X, it means that the trend is changing and the entire open operation must be closed.
This system has no Stop, so be careful when using it.
Na linguagem do autor:
Larry Williams usou esse sistema ganhar campeonato de trade
Olá amigos, trago um script com uma estratégia de trade pra ser usada em futuros como Índice, Forex e Commodities. Desenvolvido pelo famoso trader Larry Willians.
Neles usamos duas Médias Móveis Simples (Aritmética) de 3 períodos (uma com o preço da máxima, outra com o preço da mínima), e uma Média Móvel (Aritmética) de 21 períodos para determinar a tendência. Nisso vai formar uma canal de médias com os preços das máximas e mínimas dos últimos três candles.
Melhores tempos gráficos usar a estratégia: de 5 minutos até 60 minutos.
Essa estratégia é bem simples. A Média Móvel de 21 irá colorir de acordo com a tendência (Green pra alta, Red para baixa e Gray para transições). O Script irá sinalizar a entrada de acordo com a tendência pela cores dos candles e também pela sinalização:
Quando green, a compra será no cruzamento da Média Móvel inferior cruzando o candle, e a saida será no cruzamento do candle na Média Móvel Superior seguinte.
Quando red, a venda será no cruzamento da Média Móvel Superior cruzando o candle, e a saida será no cruzamento do candle na Média Móvel Inferior seguinte.
Quando o Script sinaliza o candle com X purple, significa que a tendência está em mudança e deve ser fechada toda a operação em aberto.
Este sistema não possui Stop, portando cuidado quanto a seu uso.
100PipsADay third screen / triple screen strategy MACD and W%RThird Screen Strategy
This particular script is specifically designed around this strategy. D1 MACD & H1 Williams %.
I coded the script in a way that you automatically get the signal that is calculated taking in consideration both the indicators (macd and w%R)
Green means that the daily MACD histogram is above 0 (crowd is bullish) but w%R shows that momentarily there is a lower price (W%R is oversold),
Red is vice versa.
Quote from original post :
Below is how I would normally take a trade using my strategy.
As you can see below in my chart, I look on the D1 chart for the MACD to cross over.
Once it is clear that it has crossed over, I will enter positions on the H1 chart using Williams %.
end quote.
This Script i coded in a way that automatically account for both the indicators, so you don't have to switch between timeframes.
3 Important rules :
To get the indicator set correctly you need to use on 1 Hour time frame
-----------------------
You should wait 6 hours when signal appear to open an other position on the same pair
-----------------------
I coded an alarm that gets triggered when the pair meet both condition (when the bar and/or the background is green) so you can just set it by right clicking the indicator and be relaxed!
Italiano :
Strategia Third screen
Questo particolare script è specificamente progettato attorno a questa strategia. D1 MACD e H1 Williams%.
Ho codificato lo script in modo da ottenere automaticamente il segnale calcolato tenendo conto di entrambi gli indicatori (macd e w% R)
Verde indica che l'istogramma MACD giornaliero è superiore a 0 (la folla è rialzista) ma w% R mostra che momentaneamente esiste un prezzo inferiore (W% R è sotto il livello di oversold),
Il rosso è viceversa.
Ho codificato questo script in un modo che tiene conto automaticamente di entrambi gli indicatori, quindi non è necessario passare da un intervallo di tempo all'altro.
3 Regole importanti:
Per impostare correttamente l'indicatore è necessario utilizzare nel periodo di 1 ora
-----------------------
Dovresti aspettare 6 ore una volta che arriva il segnale per aprire un'altra posizione sullo stessa moneta
-----------------------
Ho codificato un allarme che viene attivato quando sono soddisfatte entrambe le condizioni (ossia quando lo sfondo è verde), quindi puoi semplicemente impostarlo facendo clic con il pulsante destro del mouse sull'indicatore ed essere rilassato!
$MTF Fractal Echo DetectorMIL:MTVFR FRACTAL ECHO DETECTOR by Timmy741
The first public multi-timeframe fractal convergence system that actually works.
Market makers don’t move price randomly.
They test the same fractal structure on lower timeframes first → then execute the real move on higher timeframes.
This indicator catches the “echo” — when 3–5 timeframes are printing fractals at almost the exact same price level.
That’s not coincidence. That’s preparation.
FEATURES
• 5 simultaneous timeframes (1min → 4H by default)
• Real Williams Fractal detection (configurable period)
• Dynamic echo tolerance & minimum TF alignment
• Visual S/R zones from every timeframe
• Bullish / Bearish echo convergence signals
• Strength meter (3/5, 4/5, 5/5 TF alignment)
• Zero repainting — uses proper lookahead=off
• Fully Pine v6 typed + optimized
USE CASE
When you see a 4/5 or 5/5 echo:
→ That level is being defended or attacked with intent
→ 80%+ chance the next real move comes from there
→ Trade the breakout or reversal at that exact fractal cluster
Works insane on:
• BTC / ETH (all timeframes)
• Nasdaq / SPX futures
• Forex majors (especially GBP & gold)
• 2025 small-cap rotation setups
100% Open Source • MPL 2.0 • Built by Timmy741 • December 2024
If you know about fractal echoes… you already know.
#fractal #mtf #echo #williamsfractal #multitimeframe #smartmoney #ict #smc #orderflow #convergence #timmy741 #snr #structure
Profitunity - Beginner [TC]This indicator aggregates the knowledges of the first level of the Trading Chaos approach by Bill Williams. It uses the Market Facilitation Index (MFI) in conjunction with the type of bar(candle) to generate strong long and strong short signals.
General information
Bars numeration
All bars or candles could be numbered with the following algorithm. If we divide the candle for 3 equal parts from high to low. The highest third have the number 1, the middle one - 2, the lowest one - 3. Hence we can define the first number as the number of the third where the price opened, second - where the price closed. For example, if the price opened at the highest third and closed at the lowest one this candle has the number 13.
Trend defining
Also candles could be divided into three groups according to the trend condition: uptrend, downtrend, sideways. If the middle of the candle's trading range is above the high of the previous candle - it's uptrend candle, if below the low of the previous candle - it's downtrend candle, sideways in other candles.
Profitunity windows
According to Bill Williams MFI has 4 windows - fake, green, fade and squat. I am not going to describe here the methodology of MFI, but one thing you should know that the most valuable windows are green and squat. Green state is an indication of the true move on the market. Squat the sign that the increase in volume have not triggered the trend continuation and reverse is about to happen.
How to use?
You can use this script as the helper in automatic defining the type of candle. Indicator shows only green (green candle color) and squat (red candle color) MFI states. Add script to any timeframe and asset chart to see labels.
The "strong long" label flashes when 3 conditions are met:
1. Squat candle
2. Candle number 13
3. Downtrend candle
"Strong short" label flashes when:
1. Squat candle
2. Candle number 31
3. Uptrend candle
This indicator helps to find the trend reversal points, can be used in conjunction with other TA tools to find the entry points.
Mean Reversion Oscillator [Alpha Extract]An advanced composite oscillator system specifically designed to identify extreme market conditions and high-probability mean reversion opportunities, combining five proven oscillators into a single, powerful analytical framework.
By integrating multiple momentum and volume-based indicators with sophisticated extreme level detection, this oscillator provides precise entry signals for contrarian trading strategies while filtering out false reversals through momentum confirmation.
🔶 Multi-Oscillator Composite Framework
Utilizes a comprehensive approach that combines Bollinger %B, RSI, Stochastic, Money Flow Index, and Williams %R into a unified composite score. This multi-dimensional analysis ensures robust signal generation by capturing different aspects of market extremes and momentum shifts.
// Weighted composite (equal weights)
normalized_bb = bb_percent
normalized_rsi = rsi
normalized_stoch = stoch_d_val
normalized_mfi = mfi
normalized_williams = williams_r
composite_raw = (normalized_bb + normalized_rsi + normalized_stoch + normalized_mfi + normalized_williams) / 5
composite = ta.sma(composite_raw, composite_smooth)
🔶 Advanced Extreme Level Detection
Features a sophisticated dual-threshold system that distinguishes between moderate and extreme market conditions. This hierarchical approach allows traders to identify varying degrees of mean reversion potential, from moderate oversold/overbought conditions to extreme levels that demand immediate attention.
🔶 Momentum Confirmation System
Incorporates a specialized momentum histogram that confirms mean reversion signals by analyzing the rate of change in the composite oscillator. This prevents premature entries during strong trending conditions while highlighting genuine reversal opportunities.
// Oscillator momentum (rate of change)
osc_momentum = ta.mom(composite, 5)
histogram = osc_momentum
// Momentum confirmation
momentum_bullish = histogram > histogram
momentum_bearish = histogram < histogram
// Confirmed signals
confirmed_bullish = bullish_entry and momentum_bullish
confirmed_bearish = bearish_entry and momentum_bearish
🔶 Dynamic Visual Intelligence
The oscillator line adapts its color intensity based on proximity to extreme levels, providing instant visual feedback about market conditions. Background shading creates clear zones that highlight when markets enter moderate or extreme territories.
🔶 Intelligent Signal Generation
Generates precise entry signals only when the composite oscillator crosses extreme thresholds with momentum confirmation. This dual-confirmation approach significantly reduces false signals while maintaining sensitivity to genuine mean reversion opportunities.
How It Works
🔶 Composite Score Calculation
The indicator simultaneously tracks five different oscillators, each normalized to a 0-100 scale, then combines them into a smoothed composite score. This approach eliminates the noise inherent in single-oscillator analysis while capturing the consensus view of multiple momentum indicators.
// Mean reversion entry signals
bullish_entry = ta.crossover(composite, 100 - extreme_level) and composite < (100 - extreme_level)
bearish_entry = ta.crossunder(composite, extreme_level) and composite > extreme_level
// Bollinger %B calculation
bb_basis = ta.sma(src, bb_length)
bb_dev = bb_mult * ta.stdev(src, bb_length)
bb_percent = (src - bb_lower) / (bb_upper - bb_lower) * 100
🔶 Extreme Zone Identification
The system automatically identifies when markets reach statistically significant extreme levels, both moderate (65/35) and extreme (80/20). These zones represent areas where mean reversion has the highest probability of success based on historical market behavior.
🔶 Momentum Histogram Analysis
A specialized momentum histogram tracks the velocity of oscillator changes, helping traders distinguish between healthy corrections and potential trend reversals. The histogram's color-coded display makes momentum shifts immediately apparent.
🔶 Divergence Detection Framework
Built-in divergence analysis identifies situations where price and oscillator movements diverge, often signaling impending reversals. Diamond-shaped markers highlight these critical divergence patterns for enhanced pattern recognition.
🔶 Real-Time Information Dashboard
An integrated information table provides instant access to current oscillator readings, market status, and individual component values. This dashboard eliminates the need to manually check multiple indicators while trading.
🔶 Individual Component Display
Optional display of individual oscillator components allows traders to understand which specific indicators are driving the composite signal. This transparency enables more informed decision-making and deeper market analysis.
🔶 Adaptive Background Coloring
Intelligent background shading automatically adjusts based on market conditions, creating visual zones that correspond to different levels of mean reversion potential. The subtle color gradations make pattern recognition effortless.
1D
3D
🔶 Comprehensive Alert System
Multi-tier alert system covers confirmed entry signals, divergence patterns, and extreme level breaches. Each alert type provides specific context about the detected condition, enabling traders to respond appropriately to different signal strengths.
🔶 Customizable Threshold Management
Fully adjustable extreme and moderate levels allow traders to fine-tune the indicator's sensitivity to match different market volatilities and trading timeframes. This flexibility ensures optimal performance across various market conditions.
🔶 Why Choose AE - Mean Reversion Oscillator?
This indicator provides the most comprehensive approach to mean reversion trading by combining multiple proven oscillators with advanced confirmation mechanisms. By offering clear visual hierarchies for different extreme levels and requiring momentum confirmation for signals, it empowers traders to identify high-probability contrarian opportunities while avoiding false reversals. The sophisticated composite methodology ensures that signals are both statistically significant and practically actionable, making it an essential tool for traders focused on mean reversion strategies across all market conditions.
Willams %R extreme and MACD DivergenceThis is two different indicators combine into one.
First is the two different period of Williams% 5 mins and 15 mins.
Second is the MACD line of 5 mins chart.
Both will be primarily use on the 5 mins chart, you can use on another time frame if you wish
Williams %:
green = uptrending
red = downtrending
Bright green: overbought condition, look to Short at the end of the signal
Bright Red: oversold condition, look to Long at the end of the signal
MACD:
I also added the MACD line which you can use for divergence
when price move higher and MACD is moving down, expecting price to drop sometime soon or vice versa. See chart for example.
Scout Regiment - KSI# Scout Regiment - KSI Indicator
## English Documentation
### Overview
Scout Regiment - KSI (Key Stochastic Indicators) is a comprehensive momentum oscillator that combines three powerful technical indicators - RSI, CCI, and Williams %R - into a single, unified display. This multi-indicator approach provides traders with diverse perspectives on market momentum, overbought/oversold conditions, and potential reversal points through advanced divergence detection.
### What is KSI?
KSI stands for "Key Stochastic Indicators" - a composite momentum indicator that:
- Displays multiple oscillators normalized to a 0-100 scale
- Uses standardized bands (20/50/80) for consistent interpretation
- Combines RSI for trend, CCI for cycle, and Williams %R for reversal detection
- Provides enhanced divergence detection specifically for RSI
### Key Features
#### 1. **Triple Oscillator System**
**① RSI (Relative Strength Index)** - Primary Indicator
- **Purpose**: Measures momentum and identifies overbought/oversold conditions
- **Default Length**: 22 periods
- **Display**: Blue line (2px)
- **Key Levels**:
- Above 50: Bullish momentum
- Below 50: Bearish momentum
- Above 80: Overbought
- Below 20: Oversold
- **Special Features**:
- Background color indication (green/red)
- Crossover labels at 50 level
- Full divergence detection (4 types)
**② CCI (Commodity Channel Index)** - Dual Period
- **Purpose**: Identifies cyclical trends and extreme conditions
- **Dual Display**:
- CCI(33): Short-term cycle - Green line (1px)
- CCI(77): Medium-term cycle - Orange line (1px)
- **Default Source**: HLC3 (typical price)
- **Normalized Scale**: Mapped from ±100 to 0-100 for consistency
- **Interpretation**:
- Above 80: Strong upward momentum
- Below 20: Strong downward momentum
- 50 level: Neutral
- Divergence between periods: Trend change warning
**③ Williams %R** - Optional
- **Purpose**: Identifies overbought/oversold extremes
- **Default Length**: 28 periods
- **Display**: Magenta line (2px)
- **Scale**: Inverted and normalized to 0-100
- **Best For**: Short-term reversal signals
- **Default**: Disabled (enable when needed for extra confirmation)
#### 2. **Standardized Band System**
**Three-Level Structure:**
- **Upper Band (80)**: Overbought zone
- Strong momentum area
- Watch for reversal signals
- Divergences here are most reliable
- **Middle Line (50)**: Equilibrium
- Separates bullish/bearish zones
- Crossovers indicate momentum shifts
- Key decision level
- **Lower Band (20)**: Oversold zone
- Weak momentum area
- Look for bounce signals
- Divergences here signal potential reversals
**Band Fill**: Dark background between 20-80 for visual clarity
#### 3. **RSI Visual Enhancements**
**Background Color Indication**
- Green background: RSI above 50 (bullish bias)
- Red background: RSI below 50 (bearish bias)
- Optional display for cleaner charts
- Helps identify overall momentum direction
**Crossover Labels**
- "突破" (Breakout): RSI crosses above 50
- "跌破" (Breakdown): RSI crosses below 50
- Marks momentum shift points
- Can be toggled on/off
#### 4. **Advanced RSI Divergence Detection**
The indicator includes comprehensive divergence detection for RSI only (most reliable oscillator):
**Regular Bullish Divergence (Yellow)**
- **Price**: Lower lows
- **RSI**: Higher lows
- **Signal**: Potential upward reversal
- **Label**: "涨" (Up)
- **Most Common**: Near oversold levels (below 30)
**Regular Bearish Divergence (Blue)**
- **Price**: Higher highs
- **RSI**: Lower highs
- **Signal**: Potential downward reversal
- **Label**: "跌" (Down)
- **Most Common**: Near overbought levels (above 70)
**Hidden Bullish Divergence (Light Yellow)**
- **Price**: Higher lows
- **RSI**: Lower lows
- **Signal**: Uptrend continuation
- **Label**: "隐涨" (Hidden Up)
- **Use**: Add to existing longs
**Hidden Bearish Divergence (Light Blue)**
- **Price**: Lower highs
- **RSI**: Higher highs
- **Signal**: Downtrend continuation
- **Label**: "隐跌" (Hidden Down)
- **Use**: Add to existing shorts
**Divergence Parameters** (Fully Customizable):
- **Right Lookback**: Bars to right of pivot (default: 5)
- **Left Lookback**: Bars to left of pivot (default: 5)
- **Max Range**: Maximum bars between pivots (default: 60)
- **Min Range**: Minimum bars between pivots (default: 5)
### Configuration Settings
#### KSI Display Settings
- **Show RSI**: Toggle RSI indicator
- **Show CCI**: Toggle both CCI lines
- **Show Williams %R**: Toggle Williams %R (optional)
#### RSI Settings
- **RSI Length**: Period for calculation (default: 22)
- **Data Source**: Price source (default: close)
- **Show Background**: Toggle green/red background
- **Show Cross Labels**: Toggle 50-level crossover labels
#### RSI Divergence Settings
- **Right Lookback**: Pivot detection right side
- **Left Lookback**: Pivot detection left side
- **Max Range**: Maximum lookback distance
- **Min Range**: Minimum lookback distance
- **Show Regular Divergence**: Enable regular divergence lines
- **Show Regular Labels**: Enable regular divergence labels
- **Show Hidden Divergence**: Enable hidden divergence lines
- **Show Hidden Labels**: Enable hidden divergence labels
#### CCI Settings
- **CCI Length**: Short-term period (default: 33)
- **CCI Mid Length**: Medium-term period (default: 77)
- **Data Source**: Price calculation (default: HLC3)
- **Show CCI(33)**: Toggle short-term CCI
- **Show CCI(77)**: Toggle medium-term CCI
#### Williams %R Settings
- **Length**: Calculation period (default: 28)
- **Data Source**: Price source (default: close)
### How to Use
#### For Basic Momentum Trading
1. **Enable RSI Only** (primary indicator)
- Focus on 50-level crossovers
- Enable crossover labels for signals
2. **Identify Momentum Direction**
- RSI > 50 = Bullish momentum
- RSI < 50 = Bearish momentum
- Background color confirms direction
3. **Look for Extremes**
- RSI > 80 = Overbought (consider selling)
- RSI < 20 = Oversold (consider buying)
4. **Trade Setup**
- Enter long when RSI crosses above 50 from oversold
- Enter short when RSI crosses below 50 from overbought
#### For Divergence Trading
1. **Enable RSI with Divergence Detection**
- Turn on regular divergence
- Optionally add hidden divergence
2. **Wait for Divergence Signal**
- Yellow label = Bullish divergence
- Blue label = Bearish divergence
3. **Confirm with Price Structure**
- Wait for support/resistance break
- Look for candlestick patterns
- Check volume confirmation
4. **Enter Position**
- Enter after confirmation
- Stop beyond divergence pivot
- Target next key level
#### For Multi-Oscillator Confirmation
1. **Enable All Three Indicators**
- RSI (momentum)
- CCI dual (cycle analysis)
- Williams %R (extremes)
2. **Look for Alignment**
- All above 50 = Strong bullish
- All below 50 = Strong bearish
- Mixed signals = Consolidation
3. **Identify Extremes**
- All indicators > 80 = Extreme overbought
- All indicators < 20 = Extreme oversold
4. **Trade Reversals**
- Enter counter-trend when all aligned at extremes
- Confirm with divergence if available
- Use tight stops
#### For CCI Dual-Period Analysis
1. **Enable Both CCI Lines**
- CCI(33) = Short-term
- CCI(77) = Medium-term
2. **Watch for Crossovers**
- Green crosses above orange = Bullish acceleration
- Green crosses below orange = Bearish acceleration
3. **Analyze Divergence Between Periods**
- Short-term rising, medium falling = Potential reversal
- Both rising together = Strong trend
4. **Trade Accordingly**
- Follow crossover direction
- Exit when lines converge
### Trading Strategies
#### Strategy 1: RSI 50-Level Crossover
**Setup:**
- Enable RSI with background and labels
- Wait for clear trend
- Look for retracement to 50 level
**Entry:**
- Long: "突破" label appears after pullback
- Short: "跌破" label appears after bounce
**Stop Loss:**
- Long: Below recent swing low
- Short: Above recent swing high
**Exit:**
- Opposite crossover label
- Or predetermined target (2:1 risk-reward)
**Best For:** Trend following, clear markets
#### Strategy 2: RSI Divergence Reversal
**Setup:**
- Enable RSI with regular divergence
- Wait for extreme levels (>70 or <30)
- Look for divergence signal
**Entry:**
- Long: Yellow "涨" label at oversold level
- Short: Blue "跌" label at overbought level
**Confirmation:**
- Wait for price to break structure
- Check for volume increase
- Look for candlestick reversal pattern
**Stop Loss:**
- Beyond divergence pivot point
**Exit:**
- Take partial profit at 50 level
- Exit remainder at opposite extreme or divergence
**Best For:** Swing trading, range-bound markets
#### Strategy 3: Triple Oscillator Confluence
**Setup:**
- Enable all three indicators
- Wait for all to reach extreme (>80 or <20)
- Look for alignment
**Entry:**
- Long: All three below 20, first one crosses above 20
- Short: All three above 80, first one crosses below 80
**Confirmation:**
- All indicators must align
- Price at support/resistance
- Volume spike helps
**Stop Loss:**
- Fixed percentage or ATR-based
**Exit:**
- When any indicator crosses 50 level
- Or at predetermined target
**Best For:** High-probability reversals, volatile markets
#### Strategy 4: CCI Dual-Period System
**Setup:**
- Enable both CCI lines only
- Disable RSI and Williams %R for clarity
- Watch for crossovers
**Entry:**
- Long: CCI(33) crosses above CCI(77) below 50 line
- Short: CCI(33) crosses below CCI(77) above 50 line
**Confirmation:**
- Both should be moving in entry direction
- Price breaking key level helps
**Stop Loss:**
- When CCIs cross back in opposite direction
**Exit:**
- Both CCIs enter opposite extreme zone
- Or trailing stop
**Best For:** Catching trend continuations, momentum trading
#### Strategy 5: Hidden Divergence Continuation
**Setup:**
- Enable RSI with hidden divergence
- Confirm existing trend
- Wait for pullback
**Entry:**
- Uptrend: "隐涨" label during pullback
- Downtrend: "隐跌" label during bounce
**Confirmation:**
- Price holds key moving average
- Trend structure intact
**Stop Loss:**
- Beyond pullback extreme
**Exit:**
- Regular divergence appears (reversal warning)
- Or trend structure breaks
**Best For:** Adding to positions, trend trading
### Best Practices
#### Choosing Which Indicators to Display
**For Beginners:**
- Use RSI only
- Enable background color and labels
- Focus on 50-level crossovers
- Simple and effective
**For Intermediate Traders:**
- RSI + Regular Divergence
- Add CCI for confirmation
- Use dual perspectives
- Better accuracy
**For Advanced Traders:**
- All three indicators
- Full divergence detection
- Multi-timeframe analysis
- Maximum information
#### Oscillator Priority
**Primary**: RSI (22)
- Most reliable
- Best divergence detection
- Good for all timeframes
- Use this as your main decision maker
**Secondary**: CCI (33/77)
- Adds cycle analysis
- Great for confirmation
- Dual-period crossovers valuable
- Use to confirm RSI signals
**Tertiary**: Williams %R (28)
- Extreme readings useful
- More volatile
- Best for short-term
- Use sparingly for extra confirmation
#### Timeframe Considerations
**Lower Timeframes (1m-15m):**
- More signals, less reliable
- Use tight divergence parameters
- Focus on RSI crossovers
- Quick entries and exits
**Medium Timeframes (30m-4H):**
- Balanced signal frequency
- Default settings work well
- Best for divergence trading
- Swing trading optimal
**Higher Timeframes (Daily+):**
- Fewer but stronger signals
- Widen divergence ranges
- All indicators more reliable
- Position trading best
#### Divergence Trading Tips
1. **Wait for Confirmation**
- Divergence alone isn't enough
- Need price structure break
- Volume helps validate
2. **Best at Extremes**
- Divergences near 80/20 levels most reliable
- Mid-level divergences often fail
- Combine with support/resistance
3. **Multiple Divergences**
- Second divergence stronger than first
- Third divergence extremely powerful
- Watch for "triple divergence"
4. **Timeframe Alignment**
- Check higher timeframe for direction
- Trade divergences in direction of larger trend
- Counter-trend divergences riskier
### Indicator Combinations
**With Moving Averages:**
- Use EMAs (21/55/144) for trend
- KSI for entry timing
- Enter when both align
**With Volume:**
- Volume confirms breakouts
- Divergence + volume divergence = Stronger
- Low volume at extremes = Reversal likely
**With Support/Resistance:**
- Price levels for targets
- KSI for entry timing
- Divergences at levels = Highest probability
**With Bias Indicator:**
- Bias shows price deviation
- KSI shows momentum
- Both diverging = Strong reversal signal
**With OBV Indicator:**
- OBV shows volume trend
- KSI shows price momentum
- Volume/momentum divergence powerful
### Common Patterns
1. **Bullish Reversal**: All oscillators oversold + RSI bullish divergence
2. **Bearish Reversal**: All oscillators overbought + RSI bearish divergence
3. **Trend Acceleration**: RSI > 50, both CCIs rising, Williams %R not extreme
4. **Weakening Trend**: RSI declining while price rising (pre-divergence warning)
5. **Strong Trend**: All oscillators stay above/below 50 for extended period
6. **Consolidation**: Oscillators crossing 50 frequently without extremes
7. **Exhaustion**: Multiple oscillators at extreme + hidden divergence failure
### Performance Tips
- Start simple: RSI only
- Add indicators gradually as you learn
- Disable unused features for cleaner charts
- Use labels strategically (not always on)
- Test different RSI lengths for your market
- Adjust divergence parameters based on volatility
### Alert Conditions
The indicator includes alerts for:
- RSI crossing above 50
- RSI crossing below 50
- RSI regular bullish divergence
- RSI regular bearish divergence
- RSI hidden bullish divergence
- RSI hidden bearish divergence
---
## 中文说明文档
### 概述
Scout Regiment - KSI（关键随机指标）是一个综合性动量振荡器，将三个强大的技术指标 - RSI、CCI和威廉指标 - 组合到一个统一的显示中。这种多指标方法为交易者提供了市场动量、超买超卖状况和通过高级背离检测发现潜在反转点的多元视角。
### 什么是KSI？
KSI代表"关键随机指标" - 一个综合动量指标：
- 显示多个振荡器，标准化到0-100刻度
- 使用标准化波段（20/50/80）便于一致解读
- 结合RSI用于趋势、CCI用于周期、威廉指标用于反转检测
- 专门为RSI提供增强的背离检测
### 核心功能
#### 1. **三重振荡器系统**
**① RSI（相对强弱指数）** - 主要指标
- **用途**：测量动量并识别超买超卖状况
- **默认长度**：22周期
- **显示**：蓝色线（2像素）
- **关键水平**：
- 50以上：看涨动量
- 50以下：看跌动量
- 80以上：超买
- 20以下：超卖
- **特殊功能**：
- 背景颜色指示（绿色/红色）
- 50水平穿越标签
- 完整背离检测（4种类型）
**② CCI（顺势指标）** - 双周期
- **用途**：识别周期性趋势和极端状况
- **双重显示**：
- CCI(33)：短期周期 - 绿色线（1像素）
- CCI(77)：中期周期 - 橙色线（1像素）
- **默认数据源**：HLC3（典型价格）
- **标准化刻度**：从±100映射到0-100以保持一致性
- **解读**：
- 80以上：强劲上升动量
- 20以下：强劲下降动量
- 50水平：中性
- 周期间背离：趋势变化警告
**③ 威廉指标 %R** - 可选
- **用途**：识别超买超卖极值
- **默认长度**：28周期
- **显示**：洋红色线（2像素）
- **刻度**：反转并标准化到0-100
- **最适合**：短期反转信号
- **默认**：禁用（需要额外确认时启用）
#### 2. **标准化波段系统**
**三层结构：**
- **上轨（80）**：超买区域
- 强动量区域
- 注意反转信号
- 此处的背离最可靠
- **中线（50）**：均衡线
- 分隔看涨/看跌区域
- 穿越表示动量转变
- 关键决策水平
- **下轨（20）**：超卖区域
- 弱动量区域
- 寻找反弹信号
- 此处的背离预示潜在反转
**波段填充**：20-80之间的深色背景，增强视觉清晰度
#### 3. **RSI视觉增强**
**背景颜色指示**
- 绿色背景：RSI在50以上（看涨偏向）
- 红色背景：RSI在50以下（看跌偏向）
- 可选显示，图表更清爽
- 帮助识别整体动量方向
**穿越标签**
- "突破"：RSI向上穿越50
- "跌破"：RSI向下穿越50
- 标记动量转变点
- 可开关
#### 4. **高级RSI背离检测**
指标仅为RSI（最可靠的振荡器）提供全面背离检测：
**常规看涨背离（黄色）**
- **价格**：更低的低点
- **RSI**：更高的低点
- **信号**：潜在向上反转
- **标签**："涨"
- **最常见**：在超卖水平附近（30以下）
**常规看跌背离（蓝色）**
- **价格**：更高的高点
- **RSI**：更低的高点
- **信号**：潜在向下反转
- **标签**："跌"
- **最常见**：在超买水平附近（70以上）
**隐藏看涨背离（浅黄色）**
- **价格**：更高的低点
- **RSI**：更低的低点
- **信号**：上升趋势延续
- **标签**："隐涨"
- **用途**：加仓现有多头
**隐藏看跌背离（浅蓝色）**
- **价格**：更低的高点
- **RSI**：更高的高点
- **信号**：下降趋势延续
- **标签**："隐跌"
- **用途**：加仓现有空头
**背离参数**（完全可自定义）：
- **右侧回溯**：枢轴点右侧K线数（默认：5）
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **最大范围**：枢轴点之间最大K线数（默认：60）
- **最小范围**：枢轴点之间最小K线数（默认：5）
### 配置设置
#### KSI显示设置
- **显示RSI**：切换RSI指标
- **显示CCI**：切换两条CCI线
- **显示威廉指标 %R**：切换威廉指标（可选）
#### RSI设置
- **RSI长度**：计算周期（默认：22）
- **数据源**：价格源（默认：收盘价）
- **显示背景**：切换绿色/红色背景
- **显示穿越标签**：切换50水平穿越标签
#### RSI背离设置
- **右侧回溯**：枢轴检测右侧
- **左侧回溯**：枢轴检测左侧
- **回溯范围最大值**：最大回溯距离
- **回溯范围最小值**：最小回溯距离
- **显示常规背离**：启用常规背离线
- **显示常规背离标签**：启用常规背离标签
- **显示隐藏背离**：启用隐藏背离线
- **显示隐藏背离标签**：启用隐藏背离标签
#### CCI设置
- **CCI长度**：短期周期（默认：33）
- **CCI中期长度**：中期周期（默认：77）
- **数据源**：价格计算（默认：HLC3）
- **显示CCI(33)**：切换短期CCI
- **显示CCI(77)**：切换中期CCI
#### 威廉指标 %R 设置
- **长度**：计算周期（默认：28）
- **数据源**：价格源（默认：收盘价）
### 使用方法
#### 基础动量交易
1. **仅启用RSI**（主要指标）
- 关注50水平穿越
- 启用穿越标签获取信号
2. **识别动量方向**
- RSI > 50 = 看涨动量
- RSI < 50 = 看跌动量
- 背景颜色确认方向
3. **寻找极值**
- RSI > 80 = 超买（考虑卖出）
- RSI < 20 = 超卖（考虑买入）
4. **交易设置**
- RSI从超卖区向上穿越50时做多
- RSI从超买区向下穿越50时做空
#### 背离交易
1. **启用RSI和背离检测**
- 打开常规背离
- 可选添加隐藏背离
2. **等待背离信号**
- 黄色标签 = 看涨背离
- 蓝色标签 = 看跌背离
3. **用价格结构确认**
- 等待支撑/阻力突破
- 寻找K线形态
- 检查成交量确认
4. **进入仓位**
- 确认后进入
- 止损设在背离枢轴点之外
- 目标下一个关键水平
#### 多振荡器确认
1. **启用全部三个指标**
- RSI（动量）
- CCI双周期（周期分析）
- 威廉指标 %R（极值）
2. **寻找一致性**
- 全部在50以上 = 强劲看涨
- 全部在50以下 = 强劲看跌
- 信号混合 = 盘整
3. **识别极值**
- 所有指标 > 80 = 极度超买
- 所有指标 < 20 = 极度超卖
4. **交易反转**
- 所有指标在极值一致时逆势进入
- 可能的话用背离确认
- 使用紧密止损
#### CCI双周期分析
1. **启用两条CCI线**
- CCI(33) = 短期
- CCI(77) = 中期
2. **观察穿越**
- 绿色线穿越橙色线向上 = 看涨加速
- 绿色线穿越橙色线向下 = 看跌加速
3. **分析周期间背离**
- 短期上升，中期下降 = 潜在反转
- 两者同时上升 = 强趋势
4. **相应交易**
- 跟随穿越方向
- 线条汇合时退出
### 交易策略
#### 策略1：RSI 50水平穿越
**设置：**
- 启用RSI及背景和标签
- 等待明确趋势
- 寻找回调至50水平
**入场：**
- 多头：回调后出现"突破"标签
- 空头：反弹后出现"跌破"标签
**止损：**
- 多头：近期波动低点之下
- 空头：近期波动高点之上
**离场：**
- 出现相反穿越标签
- 或预定目标（2:1风险收益比）
**适合：**趋势跟随、明确市场
#### 策略2：RSI背离反转
**设置：**
- 启用RSI和常规背离
- 等待极端水平（>70或<30）
- 寻找背离信号
**入场：**
- 多头：超卖水平出现黄色"涨"标签
- 空头：超买水平出现蓝色"跌"标签
**确认：**
- 等待价格突破结构
- 检查成交量增加
- 寻找K线反转形态
**止损：**
- 背离枢轴点之外
**离场：**
- 在50水平部分获利
- 其余在相反极值或背离处离场
**适合：**波段交易、震荡市场
#### 策略3：三重振荡器汇合
**设置：**
- 启用全部三个指标
- 等待全部达到极值（>80或<20）
- 寻找一致性
**入场：**
- 多头：三个全部低于20，第一个向上穿越20
- 空头：三个全部高于80，第一个向下穿越80
**确认：**
- 所有指标必须一致
- 价格在支撑/阻力位
- 成交量激增有帮助
**止损：**
- 固定百分比或基于ATR
**离场：**
- 任一指标穿越50水平时
- 或在预定目标
**适合：**高概率反转、波动市场
#### 策略4：CCI双周期系统
**设置：**
- 仅启用两条CCI线
- 禁用RSI和威廉指标以保持清晰
- 观察穿越
**入场：**
- 多头：CCI(33)在50线下方向上穿越CCI(77)
- 空头：CCI(33)在50线上方向下穿越CCI(77)
**确认：**
- 两者都应朝入场方向移动
- 价格突破关键水平有帮助
**止损：**
- CCI反向穿越时
**离场：**
- 两条CCI进入相反极值区域
- 或移动止损
**适合：**捕捉趋势延续、动量交易
#### 策略5：隐藏背离延续
**设置：**
- 启用RSI和隐藏背离
- 确认现有趋势
- 等待回调
**入场：**
- 上升趋势：回调期间出现"隐涨"标签
- 下降趋势：反弹期间出现"隐跌"标签
**确认：**
- 价格守住关键移动平均线
- 趋势结构完整
**止损：**
- 回调极值之外
**离场：**
- 出现常规背离（反转警告）
- 或趋势结构破坏
**适合：**加仓、趋势交易
### 最佳实践
#### 选择显示哪些指标
**新手：**
- 仅使用RSI
- 启用背景颜色和标签
- 关注50水平穿越
- 简单有效
**中级交易者：**
- RSI + 常规背离
- 添加CCI确认
- 使用双重视角
- 更高准确度
**高级交易者：**
- 全部三个指标
- 完整背离检测
- 多时间框架分析
- 信息最大化
#### 振荡器优先级
**主要**：RSI (22)
- 最可靠
- 最佳背离检测
- 适用所有时间框架
- 用作主要决策依据
**次要**：CCI (33/77)
- 添加周期分析
- 确认效果好
- 双周期穿越有价值
- 用于确认RSI信号
**第三**：威廉指标 %R (28)
- 极值读数有用
- 更波动
- 最适合短期
- 谨慎使用以获额外确认
#### 时间框架考虑
**低时间框架（1分钟-15分钟）：**
- 更多信号，可靠性较低
- 使用紧密背离参数
- 关注RSI穿越
- 快速进出
**中等时间框架（30分钟-4小时）：**
- 信号频率平衡
- 默认设置效果好
- 最适合背离交易
- 波段交易最优
**高时间框架（日线+）：**
- 信号较少但更强
- 扩大背离范围
- 所有指标更可靠
- 最适合仓位交易
#### 背离交易技巧
1. **等待确认**
- 仅背离不够
- 需要价格结构突破
- 成交量帮助验证
2. **极值处最佳**
- 80/20水平附近的背离最可靠
- 中间水平背离常失败
- 结合支撑/阻力
3. **多重背离**
- 第二次背离强于第一次
- 第三次背离极其强大
- 注意"三重背离"
4. **时间框架对齐**
- 检查更高时间框架方向
- 顺大趋势方向交易背离
- 逆势背离风险更大
### 指标组合
**与移动平均线配合：**
- 使用EMA（21/55/144）确定趋势
- KSI用于入场时机
- 两者一致时进入
**与成交量配合：**
- 成交量确认突破
- 背离 + 成交量背离 = 更强
- 极值处低成交量 = 可能反转
**与支撑/阻力配合：**
- 价格水平作为目标
- KSI用于入场时机
- 水平处的背离 = 最高概率
**与Bias指标配合：**
- Bias显示价格偏离
- KSI显示动量
- 两者都背离 = 强反转信号
**与OBV指标配合：**
- OBV显示成交量趋势
- KSI显示价格动量
- 成交量/动量背离强大
### 常见形态
1. **看涨反转**：所有振荡器超卖 + RSI看涨背离
2. **看跌反转**：所有振荡器超买 + RSI看跌背离
3. **趋势加速**：RSI > 50，两条CCI上升，威廉指标不极端
4. **趋势减弱**：价格上升时RSI下降（背离前警告）
5. **强趋势**：所有振荡器长时间保持在50上方/下方
6. **盘整**：振荡器频繁穿越50无极值
7. **衰竭**：多个振荡器在极值 + 隐藏背离失败
### 性能提示
- 从简单开始：仅RSI
- 学习时逐渐添加指标
- 禁用未使用功能以保持图表清晰
- 策略性使用标签（不总是开启）
- 为您的市场测试不同RSI长度
- 根据波动性调整背离参数
### 警报条件
指标包含以下警报：
- RSI向上穿越50
- RSI向下穿越50
- RSI常规看涨背离
- RSI常规看跌背离
- RSI隐藏看涨背离
- RSI隐藏看跌背离
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
Phicube EMASAR ( EMA Support and Resistance )Indicator based on the Concept created by Bo Williams. But unlike the original that uses MIMAs, EMAs are used here.
Exponential moving averages will be shown according to fractal alignment, in order to show the important support and resistance levels ( SAR ).
When the fractals are aligned to become support,
we will have the EMA in the graph with a bright color.
When the fractals are aligned to become resistance, we will have EMA in the graph with a matte color.
Available exponential moving averages: 17,34,72,144,305,610,1292 and 2584
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Indicador baseado no Conceito criado pelo Bo Williams. Mas diferente do original que utiliza MIMAs, aqui é utilizado EMAs.
As médias móveis exponenciais serão mostradas de acordo com o alinhamento dos fractais, com objetivo de mostrar os níveis importantes
de suporte e resistência( SAR ).
Quando estiver com os fractais alinhados virando suporte, teremos no gráfico a EMA com uma cor em tom brilhante.
Quando estiver com os fractais alinhados virando resistência, teremos no gráfico a EMA com uma cor em tom fosco.
Médias móveis exponenciais disponíveis: 17,34,72,144,305,610,1292 e 2584
Custom EMA + FIBOThis script combines 6 EMAs with 3 Donchian Channel 78.6% and 21.4% intermediary level lines to perform trade analysis. The 6 EMAs (I, II, III , IV, V and VI ) default lengthes come from one of the Fibonacci Phi^3 and Phi^3/2 sub series (17, 34, 72, 144, 305 and 610), but can be changed to any values, particularly to the traditionally used 20, 40, 50, 100, 200 and 300. Up to my knowledge, Fibonacci Phi^3 and Phi^3/2 sub series lengthes were first proposed by Bo Williams.
The 3 Donchian Channels used have default lengthes 72, 305 and 1292, calculated after the first length default value of 72. For each of the 3 Donchian Channels only an upper line, set by default at 78.6%, is plotted in green and its complement, set to 21.4%, is plotted in red. When the closing price is above 3 green lines, we say it is Forbidden to Sell ( PV ), and when the closing price is below 3 red lines, we say it is Forbidden to Buy ( PC ). Those conditions are flagged on the chart. These PV-PC conditions were, up to my knowledge, first proposed by Bo Williams.
Bullish/Bearish Reversal Bars Indicator [Skyrexio]Introduction
Bullish/Bearish Reversal Bars Indicator leverages the combination of candlestick reversal bar pattern and the Williams Alligator indicator to help traders in understanding where there is a high probability of market reversal or correction. Indicator works for both bearish and bullish cases. It visualizes the bearish and bullish reversal bars with red and green dots and also plots the Alligator's lips to make it more convenient for traders to understand if price is above or below lips line (more information in "Methodology and it's justification" paragraph).
Features
Market Facilitation Index(MFI) filter: with the specified parameter in settings user can choose to filter bullish and bearish reversal bars which passed the MFI condition.
Awesome Oscillator(AO) filter: with the specified parameter in settings user can choose to filter bullish and bearish reversal bars which passed the AO condition.
Alerts: user can set up the alert and have notifications when bullish/bearish reversal bar has been printed.
Methodology and it's justification
In the script’s methodology, we apply the concepts of bullish and bearish reversal bars introduced by Bill Williams in his book Trading Chaos. So, what exactly is a bullish or bearish reversal bar? At its core, it’s a candlestick pattern. A bullish reversal bar is a bar that closes in its upper half, while a bearish reversal bar closes in its lower half.
Why is this type of bar significant? Let’s look at the bullish reversal bar as an example. When the price is trending upward, forming higher highs with each candle, and we suddenly see a bullish bar that makes a new high but ultimately closes in its lower half, it signals a shift in control. Bears have taken control toward the end of that candle's period, pushing the price back down. This can be interpreted as a sign of trend weakness and a potential reversal (or at least a correction).
An additional key point is that a reversal bar often indicates a possible end to the trend. Therefore, for a reversal bar to be valid, several preceding candles should show lower highs (for bullish bars) or higher lows (for bearish bars), reinforcing the likelihood of a trend change.
The second step on methodology is the location of the bar related to Williams Alligator. The Williams Alligator Indicator, developed by Bill Williams, is a technical analysis tool that helps traders identify trends and potential turning points in the market. It consists of three lines, often called the jaw, teeth, and lips of the alligator, each representing different moving averages:
Jaw (Blue Line): A slower moving average, typically a 13-period smoothed moving average shifted 8 bars into the future.
Teeth (Red Line): A medium moving average, typically an 8-period smoothed moving average shifted 5 bars into the future.
Lips (Green Line): A faster moving average, usually a 5-period smoothed moving average shifted 3 bars into the future.
When the three lines are spread out and moving in the same direction, it suggests a strong trend (the "alligator" is "awake and feeding"). When they intertwine, the indicator suggests that the market is moving sideways, or in a range, signaling a lack of clear trend (the "alligator" is "sleeping"). Traders use the Alligator Indicator to enter trades in trending markets and avoid trades in choppy, non-trending markets.
If bullish reversal bar's high is not below and bearish reversal bar's low is not above all three Alligator's lines (jaw, lips, teeth) they cannot be interpreted as these types of bars. It can be explained as following: if we are waiting for the bullish reversal bar it shall be reversal from downtrend. If price is not below all three lines it can't be interpret as the downtrend according to this method. The opposite is true for the bearish reversal bar.
All described above are obligatory conditions for reversal bar, now let's discuss two not obligatory conditions. The first one is Market Facilitation Index (MFI) restriction. Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
The second additional filter is Awesome Oscillator. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator that measures market momentum by comparing recent price action to a longer historical context. It helps traders identify potential trend reversals and the strength of trends. Formula:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
If AO is decreasing momentum is bearish, if increasing - bullish. According to Bill Williams approach reversal bars are the potential trades against the trend. As a result we added second filter for bullish reversal bars AO shall be decreasing, for bearish increasing.
How to use indicator
Apply it to desired chart and time frame. It works on every time frame.
Setup the filters with the "Enable MFI" and "Enable AO" checkboxes in the settings. By default they are turned on.
Analyze the price action. Indicator plotted the white line, this is the lips of an Alligator. It will help you to understand how price is moving in comparison to lips line. Indicator will print the green dot and text "BULL" below it current bar is bullish reversal. It will print the red dot and text "BEAR" above it if current bar is interpreted by algorithm as a bearish reversal.
Set up the alerts if it's needed. Indicator has two custom alerts called "Bullish reversal bar has been printed" and "Bearish reversal bar has been printed"
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test indicators before live implementation.
Quantum Momentum FusionPurpose of the Indicator
"Quantum Momentum Fusion" aims to combine the strengths of RSI (Relative Strength Index) and Williams %R to create a hybrid momentum indicator tailored for volatile markets like crypto:
RSI: Measures the strength of price changes, great for understanding trend stability but can sometimes lag.
Williams %R: Assesses the position of the price relative to the highest and lowest levels over a period, offering faster responses but sensitive to noise.
Combination: By blending these two indicators with a weighted average (default 50%-50%), we achieve both speed and reliability.
Additionally, we use the indicator’s own SMA (Simple Moving Average) crossovers to filter out noise and generate more meaningful signals. The goal is to craft a simple yet effective tool, especially for short-term trading like scalping.
How Signals Are Generated
The indicator produces signals as follows:
Calculations:
RSI: Standard 14-period RSI based on closing prices.
Williams %R: Calculated over 14 periods using the highest high and lowest low, then normalized to a 0-100 scale.
Quantum Fusion: A weighted average of RSI and Williams %R (e.g., 50% RSI + 50% Williams %R).
Fusion SMA: 5-period Simple Moving Average of Quantum Fusion.
Signal Conditions:
Overbought Signal (Red Background):
Quantum Fusion crosses below Fusion SMA (indicating weakening momentum).
And Quantum Fusion is above 70 (in the overbought zone).
This is a sell signal.
Oversold Signal (Green Background):
Quantum Fusion crosses above Fusion SMA (indicating strengthening momentum).
And Quantum Fusion is below 30 (in the oversold zone).
This is a buy signal.
Filtering:
The background only changes color during crossovers, reducing “fake” signals.
The 70 and 30 thresholds ensure signals trigger only in extreme conditions.
On the chart:
Purple line: Quantum Fusion.
Yellow line: Fusion SMA.
Red background: Sell signal (overbought confirmation).
Green background: Buy signal (oversold confirmation).
Overall Assessment
This indicator can be a fast-reacting tool for scalping. However:
Volatility Warning: Sudden crypto pumps/dumps can disrupt signals.
Confirmation: Pair it with price action (candlestick patterns) or another indicator (e.g., volume) for validation.
Timeframe: Works best on 1-5 minute charts.
Suggested Settings for Long Timeframes
Here’s a practical configuration for, say, a 4-hour chart:
RSI Period: 20
Williams %R Period: 20
RSI Weight: 60%
Williams %R Weight: 40% (automatically calculated as 100 - RSI Weight)
SMA Period: 15
Overbought Level: 75
Oversold Level: 25
Stochastic Vix Fix SVIX (Tartigradia)The Stochastic Vix or Stochastic VixFix (SVIX), just like the Williams VixFix, is a realized volatility indicator, and can help in finding market bottoms as well as tops without requiring bollinger bands or any other construct, as the SVIX is bounded between 0-100 which allows for an objective thresholding regardless of the past.
Mathematically, SVIX is the complement of the original Stochastic Oscillator, with such a simple transform reproducing Williams' VixFix and the VIX index signals of high volatility and hence of market bottoms quite accurately but within a bounded 0-100 range. Having a predefined range allows to find markets bottoms without needing to compare to past prices using a bollinger band (Chris Moody on TradingView) nor a moving average (Hesta 2015), as a simple threshold condition (by default above 80) is sufficient to reliably signal interesting entry points at bottoming prices.
Having a predefined range allows to find markets bottoms without needing to compare to past prices using a bollinger band (Chris Moody on TradingView) nor a moving average (Hesta 2015), as a simple threshold condition (by default above 80) is sufficient to reliably signal interesting entry points at bottoming prices.
Indeed, as Williams describes in his paper, markets tend to find the lowest prices during times of highest volatility, which usually accompany times of highest fear.
Although the VixFix originally only indicates market bottoms, the Stochastic VixFix can also indicate good times to exit, when SVIX is at a low value (default: below 20), but just like the original VixFix and VIX index, exit signals are as usual much less reliable than long entries signals, because: 1) mature markets such as SP500 tend to increase over the long term, 2) when market fall, retail traders panic and hence volatility skyrockets and bottom is more reliably signalled, but at market tops, no one is panicking, price action only loses momentum because of liquidity drying up.
Compared to Hesta 2015 strategy of using a moving average over Williams' VixFix to generate entry signals, SVIX generates much fewer false positives during ranging markets, which drastically reduce Hesta 2015 strategy profitability as this incurs quite a lot of losses.
This indicator goes further than the original SVIX, by restoring the smoothed D and second-level smoothed D2 oscillators from the original Stochastic Oscillator, and use a 14-period ZLMA instead of the original 20-period SMA, to generate smoother yet responsive signals compared to using just the raw SVIX (by default, this is disabled, as the original raw SVIX is used to produce more entry signals).
Usage:
Set the timescale to daily or weekly preferably, to reduce false positives.
When the background is highlighted in green or when the highlight disappears, it is usually a good time to enter a long position.
Red background highlighting can be enabled to signal good exit zones, but these generate a lot of false positives.
To further reduce false positives, the SVIX_MA can be used to generate signals instead of the raw SVIX.
For more information on Williams' Vix Fix, which is a strategy published under public domain:
The VIX Fix, Larry Williams, Active Trader magazine, December 2007, web.archive.org
Fixing the VIX: An Indicator to Beat Fear, Amber Hestla-Barnhart, Journal of Technical Analysis, March 13, 2015, ssrn.com
For more information on the Stochastic Vix Fix (SVIX), published under Creative Commons:
Replicating the CBOE VIX using a synthetic volatility index trading algorithm, Dayne Cary and Gary van Vuuren, Cogent Economics & Finance, Volume 7, 2019, Issue 1, doi.org
Note: strangely, in the paper, the authors failed to mention that the SVIX is the complement of the original Stochastic Oscillator, instead reproducing just the original equation. The correct equation for the SVIX was retroengineered by comparing charts they published in the paper with charts generated by this pinescript indicator.
For a more complete indicator, see:
Ultimate Oscillator (ULTOSC)The Ultimate Oscillator (ULTOSC) is a technical momentum indicator developed by Larry Williams that combines three different time periods to reduce the volatility and false signals common in single-period oscillators. By using a weighted average of three Stochastic-like calculations across short, medium, and long-term periods, the Ultimate Oscillator provides a more comprehensive view of market momentum while maintaining sensitivity to price changes.
The indicator addresses the common problem of oscillators being either too sensitive (generating many false signals) or too slow (missing opportunities). By incorporating multiple timeframes with decreasing weights for longer periods, ULTOSC attempts to capture both short-term momentum shifts and longer-term trend strength, making it particularly valuable for identifying divergences and potential reversal points.
## Core Concepts
* **Multi-timeframe analysis:** Combines three different periods (typically 7, 14, 28) to capture various momentum cycles
* **Weighted averaging:** Assigns higher weights to shorter periods for responsiveness while including longer periods for stability
* **Buying pressure focus:** Measures the relationship between closing price and the true range rather than just high-low range
* **Divergence detection:** Particularly effective at identifying momentum divergences that precede price reversals
* **Normalized scale:** Oscillates between 0 and 100, with clear overbought/oversold levels
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Fast Period | 7 | Short-term momentum calculation | Lower (5-6) for more sensitivity, higher (9-12) for smoother signals |
| Medium Period | 14 | Medium-term momentum calculation | Adjust based on typical swing duration in the market |
| Slow Period | 28 | Long-term momentum calculation | Higher values (35-42) for longer-term position trading |
| Fast Weight | 4.0 | Weight applied to fast period | Higher weight increases short-term sensitivity |
| Medium Weight | 2.0 | Weight applied to medium period | Adjust to balance medium-term influence |
| Slow Weight | 1.0 | Weight applied to slow period | Usually kept at 1.0 as the baseline weight |
**Pro Tip:** The classic 7/14/28 periods with 4/2/1 weights work well for most markets, but consider using 5/10/20 with adjusted weights for faster markets or 14/28/56 for longer-term analysis.
## Calculation and Mathematical Foundation
**Simplified explanation:**
The Ultimate Oscillator calculates three separate "buying pressure" ratios using different time periods, then combines them using weighted averaging. Buying pressure is defined as the close minus the true low, divided by the true range.
**Technical formula:**
```
BP = Close - Min(Low, Previous Close)
TR = Max(High, Previous Close) - Min(Low, Previous Close)
BP_Sum_Fast = Sum(BP, Fast Period)
TR_Sum_Fast = Sum(TR, Fast Period)
Raw_Fast = 100 × (BP_Sum_Fast / TR_Sum_Fast)
BP_Sum_Medium = Sum(BP, Medium Period)
TR_Sum_Medium = Sum(TR, Medium Period)
Raw_Medium = 100 × (BP_Sum_Medium / TR_Sum_Medium)
BP_Sum_Slow = Sum(BP, Slow Period)
TR_Sum_Slow = Sum(TR, Slow Period)
Raw_Slow = 100 × (BP_Sum_Slow / TR_Sum_Slow)
ULTOSC = 100 × / (Fast_Weight + Medium_Weight + Slow_Weight)
```
Where:
- BP = Buying Pressure
- TR = True Range
- Fast Period = 7, Medium Period = 14, Slow Period = 28 (defaults)
- Fast Weight = 4, Medium Weight = 2, Slow Weight = 1 (defaults)
> 🔍 **Technical Note:** The implementation uses efficient circular buffers for all three period calculations, maintaining O(1) time complexity per bar. The algorithm properly handles true range calculations including gaps and ensures accurate buying pressure measurements across all timeframes.
## Interpretation Details
ULTOSC provides several analytical perspectives:
* **Overbought/Oversold conditions:** Values above 70 suggest overbought conditions, below 30 suggest oversold conditions
* **Momentum direction:** Rising ULTOSC indicates increasing buying pressure, falling indicates increasing selling pressure
* **Divergence analysis:** Divergences between ULTOSC and price often precede significant reversals
* **Trend confirmation:** ULTOSC direction can confirm or question the prevailing price trend
* **Signal quality:** Extreme readings (>80 or <20) indicate strong momentum that may be unsustainable
* **Multiple timeframe consensus:** When all three underlying periods agree, signals are typically more reliable
## Trading Applications
**Primary Uses:**
- **Divergence trading:** Identify when momentum diverges from price for reversal signals
- **Overbought/oversold identification:** Find potential entry/exit points at extreme levels
- **Trend confirmation:** Validate breakouts and trend continuations
- **Momentum analysis:** Assess the strength of current price movements
**Advanced Strategies:**
- **Multi-divergence confirmation:** Look for divergences across multiple timeframes
- **Momentum breakouts:** Trade when ULTOSC breaks above/below key levels with volume
- **Swing trading entries:** Use oversold/overbought levels for swing position entries
- **Trend strength assessment:** Evaluate trend quality using momentum consistency
## Signal Combinations
**Strong Bullish Signals:**
- ULTOSC rises from oversold territory (<30) with positive price divergence
- ULTOSC breaks above 50 after forming a base near 30
- All three underlying periods show increasing buying pressure
**Strong Bearish Signals:**
- ULTOSC falls from overbought territory (>70) with negative price divergence
- ULTOSC breaks below 50 after forming a top near 70
- All three underlying periods show decreasing buying pressure
**Divergence Signals:**
- **Bullish divergence:** Price makes lower lows while ULTOSC makes higher lows
- **Bearish divergence:** Price makes higher highs while ULTOSC makes lower highs
- **Hidden bullish divergence:** Price makes higher lows while ULTOSC makes lower lows (trend continuation)
- **Hidden bearish divergence:** Price makes lower highs while ULTOSC makes higher highs (trend continuation)
## Comparison with Related Oscillators
| Indicator | Periods | Focus | Best Use Case |
|-----------|---------|-------|---------------|
| **Ultimate Oscillator** | 3 periods | Buying pressure | Divergence detection |
| **Stochastic** | 1-2 periods | Price position | Overbought/oversold |
| **RSI** | 1 period | Price momentum | Momentum analysis |
| **Williams %R** | 1 period | Price position | Short-term signals |
## Advanced Configurations
**Fast Trading Setup:**
- Fast: 5, Medium: 10, Slow: 20
- Weights: 4/2/1, Thresholds: 75/25
**Standard Setup:**
- Fast: 7, Medium: 14, Slow: 28
- Weights: 4/2/1, Thresholds: 70/30
**Conservative Setup:**
- Fast: 14, Medium: 28, Slow: 56
- Weights: 3/2/1, Thresholds: 65/35
**Divergence Focused:**
- Fast: 7, Medium: 14, Slow: 28
- Weights: 2/2/2, Thresholds: 70/30
## Market-Specific Adjustments
**Volatile Markets:**
- Use longer periods (10/20/40) to reduce noise
- Consider higher threshold levels (75/25)
- Focus on extreme readings for signal quality
**Trending Markets:**
- Emphasize divergence analysis over absolute levels
- Look for momentum confirmation rather than reversal signals
- Use hidden divergences for trend continuation
**Range-Bound Markets:**
- Standard overbought/oversold levels work well
- Trade reversals from extreme levels
- Combine with support/resistance analysis
## Limitations and Considerations
* **Lagging component:** Contains inherent lag due to multiple moving average calculations
* **Complex calculation:** More computationally intensive than single-period oscillators
* **Parameter sensitivity:** Performance varies significantly with different period/weight combinations
* **Market dependency:** Most effective in trending markets with clear momentum patterns
* **False divergences:** Not all divergences lead to significant price reversals
* **Whipsaw potential:** Can generate conflicting signals in choppy markets
## Best Practices
**Effective Usage:**
- Focus on divergences rather than absolute overbought/oversold levels
- Combine with trend analysis for context
- Use multiple timeframe analysis for confirmation
- Pay attention to the speed of momentum changes
**Common Mistakes:**
- Over-relying on overbought/oversold levels in strong trends
- Ignoring the underlying trend direction
- Using inappropriate period settings for the market being analyzed
- Trading every divergence without additional confirmation
**Signal Enhancement:**
- Combine with volume analysis for confirmation
- Use price action context (support/resistance levels)
- Consider market volatility when setting thresholds
- Look for convergence across multiple momentum indicators
## Historical Context and Development
The Ultimate Oscillator was developed by Larry Williams and introduced in his 1985 article "The Ultimate Oscillator" in Technical Analysis of Stocks and Commodities magazine. Williams designed it to address the limitations of single-period oscillators by:
- Reducing false signals through multi-timeframe analysis
- Maintaining sensitivity to short-term momentum changes
- Providing more reliable divergence signals
- Creating a more robust momentum measurement tool
The indicator has become a standard tool in technical analysis, particularly valued for its divergence detection capabilities and its balanced approach to momentum measurement.
## References
* Williams, L. R. (1985). The Ultimate Oscillator. Technical Analysis of Stocks and Commodities, 3(4).
* Williams, L. R. (1999). Long-Term Secrets to Short-Term Trading. Wiley Trading.
Advanced Speedometer Gauge [PhenLabs]Advanced Speedometer Gauge
Version: PineScript™v6
📌 Description
The Advanced Speedometer Gauge is a revolutionary multi-metric visualization tool that consolidates 13 distinct trading indicators into a single, intuitive speedometer display. Instead of cluttering your workspace with multiple oscillators and panels, this gauge provides a unified interface where you can switch between different metrics while maintaining consistent visual interpretation.
Built on PineScript™ v6, the indicator transforms complex technical calculations into an easy-to-read semi-circular gauge with color-coded zones and a precision needle indicator. Each of the 13 available metrics has been carefully normalized to a 0-100 scale, ensuring that whether you’re analyzing RSI, volume trends, or volatility extremes, the visual interpretation remains consistent and intuitive.
The gauge is designed for traders who value efficiency and clarity. By consolidating multiple analytical perspectives into one compact display, you can quickly assess market conditions without the visual noise of traditional multi-indicator setups. All metrics are non-overlapping, meaning each provides unique insights into different aspects of market behavior.
🚀 Points of Innovation
13 selectable metrics covering momentum, volume, volatility, trend, and statistical analysis, all accessible through a single dropdown menu
Universal 0-100 normalization system that standardizes different indicator scales for consistent visual interpretation across all metrics
Semi-circular gauge design with 21 arc segments providing smooth precision and clear visual feedback through color-coded zones
Non-redundant metric selection ensuring each indicator provides unique market insights without analytical overlap
Advanced metrics including MFI (volume-weighted momentum), CCI (statistical deviation), Volatility Rank (extended lookback), Trend Strength (ADX-style), Choppiness Index, Volume Trend, and Price Distance from MA
Flexible positioning system with 5 chart locations, 3 size options, and fully customizable color schemes for optimal workspace integration
🔧 Core Components
Metric Selection Engine: Dropdown interface allowing instant switching between 13 different technical indicators, each with independent parameter controls
Normalization System: All metrics converted to 0-100 scale using indicator-specific algorithms that preserve the statistical significance of each measurement
Semi-Circular Gauge: Visual display using 21 arc segments arranged in curved formation with two-row thickness for enhanced visibility
Color Zone System: Three distinct zones (0-40 green, 40-70 yellow, 70-100 red) providing instant visual feedback on metric extremes
Needle Indicator: Dynamic pointer that positions across the gauge arc based on precise current metric value
Table Implementation: Professional table structure ensuring consistent positioning and rendering across different chart configurations
🔥 Key Features
RSI (Relative Strength Index): Classic momentum oscillator measuring overbought/oversold conditions with adjustable period length (default 14)
Stochastic Oscillator: Compares closing price to price range over specified period with smoothing, ideal for identifying momentum shifts
MFI (Money Flow Index): Volume-weighted RSI that combines price movement with volume to measure buying and selling pressure intensity
CCI (Commodity Channel Index): Measures statistical deviation from average price, normalized from typical -200 to +200 range to 0-100 scale
Williams %R: Alternative overbought/oversold indicator using high-low range analysis, inverted to match 0-100 scale conventions
Volume %: Current volume relative to moving average expressed as percentage, capped at 100 for extreme spikes
Volume Trend: Cumulative directional volume flow showing whether volume is flowing into up moves or down moves over specified period
ATR Percentile: Current Average True Range position within historical range using specified lookback period (default 100 bars)
Volatility Rank: Close-to-close volatility measured against extended historical range (default 252 days), differs from ATR in calculation method
Momentum: Rate of change calculation showing price movement speed, centered at 50 and normalized to 0-100 range
Trend Strength: ADX-style calculation using directional movement to quantify trend intensity regardless of direction
Choppiness Index: Measures market choppiness versus trending behavior, where high values indicate ranging markets and low values indicate strong trends
Price Distance from MA: Measures current price over-extension from moving average using standard deviation calculations
🎨 Visualization
Semi-Circular Arc Display: Curved gauge spanning from 0 (left) to 100 (right) with smooth progression and two-row thickness for visibility
Color-Coded Zones: Green zone (0-40) for low/oversold conditions, yellow zone (40-70) for neutral readings, red zone (70-100) for high/overbought conditions
Needle Indicator: Downward-pointing triangle (▼) positioned precisely at current metric value along the gauge arc
Scale Markers: Vertical line markers at 0, 25, 50, 75, and 100 positions with corresponding numerical labels below
Title Display: Merged cell showing “𓄀 PhenLabs” branding plus currently selected metric name in monospace font
Large Value Display: Current metric value shown with two decimal precision in large text directly below title
Table Structure: Professional table with customizable background color, text color, and transparency for minimal chart obstruction
📖 Usage Guidelines
Metric Selection
Select Metric: Default: RSI | Options: RSI, Stochastic, Volume %, ATR Percentile, Momentum, MFI (Money Flow), CCI (Commodity Channel), Williams %R, Volatility Rank, Trend Strength, Choppiness Index, Volume Trend, Price Distance | Choose the technical indicator you want to display on the gauge based on your current analytical needs
RSI Settings
RSI Length: Default: 14 | Range: 1+ | Controls the lookback period for RSI calculation, shorter periods increase sensitivity to recent price changes
Stochastic Settings
Stochastic Length: Default: 14 | Range: 1+ | Lookback period for stochastic calculation comparing close to high-low range
Stochastic Smooth: Default: 3 | Range: 1+ | Smoothing period applied to raw stochastic value to reduce noise and false signals
Volume Settings
Volume MA Length: Default: 20 | Range: 1+ | Moving average period used to calculate average volume for comparison with current volume
Volume Trend Length: Default: 20 | Range: 5+ | Period for calculating cumulative directional volume flow trend
ATR and Volatility Settings
ATR Length: Default: 14 | Range: 1+ | Period for Average True Range calculation used in ATR Percentile metric
ATR Percentile Lookback: Default: 100 | Range: 20+ | Historical range used to determine current ATR position as percentile
Volatility Rank Lookback (Days): Default: 252 | Range: 50+ | Extended lookback period for Volatility Rank metric using close-to-close volatility
Momentum and Trend Settings
Momentum Length: Default: 10 | Range: 1+ | Lookback period for rate of change calculation in Momentum metric
Trend Strength Length: Default: 20 | Range: 5+ | Period for directional movement calculations in ADX-style Trend Strength metric
Advanced Metric Settings
MFI Length: Default: 14 | Range: 1+ | Lookback period for Money Flow Index calculation combining price and volume
CCI Length: Default: 20 | Range: 1+ | Period for Commodity Channel Index statistical deviation calculation
Williams %R Length: Default: 14 | Range: 1+ | Lookback period for Williams %R high-low range analysis
Choppiness Index Length: Default: 14 | Range: 5+ | Period for calculating market choppiness versus trending behavior
Price Distance MA Length: Default: 50 | Range: 10+ | Moving average period used for Price Distance standard deviation calculation
Visual Customization
Position: Default: Top Right | Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Right | Controls gauge placement on chart for optimal workspace organization
Size: Default: Normal | Options: Small, Normal, Large | Adjusts overall gauge dimensions and text size for different monitor resolutions and preferences
Low Zone Color (0-40): Default: Green (#00FF00) | Customize color for low/oversold zone of gauge arc
Medium Zone Color (40-70): Default: Yellow (#FFFF00) | Customize color for neutral/medium zone of gauge arc
High Zone Color (70-100): Default: Red (#FF0000) | Customize color for high/overbought zone of gauge arc
Background Color: Default: Semi-transparent dark gray | Customize gauge background for contrast and chart integration
Text Color: Default: White (#FFFFFF) | Customize all text elements including title, value, and scale labels
✅ Best Use Cases
Quick visual assessment of market conditions when you need instant feedback on whether an asset is in extreme territory across multiple analytical dimensions
Workspace organization for traders who monitor multiple indicators but want to reduce chart clutter and visual complexity
Metric comparison by switching between different indicators while maintaining consistent visual interpretation through the 0-100 normalization
Overbought/oversold identification using RSI, Stochastic, Williams %R, or MFI depending on whether you prefer price-only or volume-weighted analysis
Volume analysis through Volume %, Volume Trend, or MFI to confirm price movements with corresponding volume characteristics
Volatility monitoring using ATR Percentile or Volatility Rank to identify expansion/contraction cycles and adjust position sizing
Trend vs range identification by comparing Trend Strength (high values = trending) against Choppiness Index (high values = ranging)
Statistical over-extension detection using CCI or Price Distance to identify when price has deviated significantly from normal behavior
Multi-timeframe analysis by duplicating the gauge on different timeframe charts to compare metric readings across time horizons
Educational purposes for new traders learning to interpret technical indicators through consistent visual representation
⚠️ Limitations
The gauge displays only one metric at a time, requiring manual switching to compare different indicators rather than simultaneous multi-metric viewing
The 0-100 normalization, while providing consistency, may obscure the raw values and specific nuances of each underlying indicator
Table-based visualization cannot be exported or saved as an image separately from the full chart screenshot
Optimal parameter settings vary by asset type, timeframe, and market conditions, requiring user experimentation for best results
💡 What Makes This Unique
Unified Multi-Metric Interface: The only gauge-style indicator offering 13 distinct metrics through a single interface, eliminating the need for multiple oscillator panels
Non-Overlapping Analytics: Each metric provides genuinely unique insights—MFI combines volume with price, CCI measures statistical deviation, Volatility Rank uses extended lookback, Trend Strength quantifies directional movement, and Choppiness Index measures ranging behavior
Universal Normalization System: All metrics standardized to 0-100 scale using indicator-appropriate algorithms that preserve statistical meaning while enabling consistent visual interpretation
Professional Visual Design: Semi-circular gauge with 21 arc segments, precision needle positioning, color-coded zones, and clean table implementation that maintains clarity across all chart configurations
Extensive Customization: Independent parameter controls for each metric, five position options, three size presets, and full color customization for seamless workspace integration
🔬 How It Works
1. Metric Calculation Phase:
All 13 metrics are calculated simultaneously on every bar using their respective algorithms with user-defined parameters
Each metric applies its own specific calculation method—RSI uses average gains vs losses, Stochastic compares close to high-low range, MFI incorporates typical price and volume, CCI measures deviation from statistical mean, ATR calculates true range, directional indicators measure up/down movement, and statistical metrics analyze price relationships
2. Normalization Process:
Each calculated metric is converted to a standardized 0-100 scale using indicator-appropriate transformations
Some metrics are naturally 0-100 (RSI, Stochastic, MFI, Williams %R), while others require scaling—CCI transforms from ±200 range, Momentum centers around 50, Volume ratio caps at 2x for 100, ATR and Volatility Rank calculate percentile positions, and Price Distance scales by standard deviations
3. Gauge Rendering:
The selected metric’s normalized value determines the needle position across 21 arc segments spanning 0-100
Each arc segment receives its color based on position—segments 0-8 are green zone, segments 9-14 are yellow zone, segments 15-20 are red zone
The needle indicator (▼) appears in row 5 at the column corresponding to the current metric value, providing precise visual feedback
4. Table Construction:
The gauge uses TradingView’s table system with merged cells for title and value display, ensuring consistent positioning regardless of chart configuration
Rows are allocated as follows: Row 0 merged for title, Row 1 merged for large value display, Row 2 for spacing, Rows 3-4 for the semi-circular arc with curved shaping, Row 5 for needle indicator, Row 6 for scale markers, Row 7 for numerical labels at 0/25/50/75/100
All visual elements update on every bar when barstate.islast is true, ensuring real-time accuracy without performance impact
💡 Note:
This indicator is designed for visual analysis and market condition assessment, not as a standalone trading system. For best results, combine gauge readings with price action analysis, support and resistance levels, and broader market context. Parameter optimization is recommended based on your specific trading timeframe and asset class. The gauge works on all timeframes but may require different parameter settings for intraday versus daily/weekly analysis. Consider using multiple instances of the gauge set to different metrics for comprehensive market analysis without switching between settings.
Commitment of Trader %RThis script is a TradingView Pine Script that creates a custom indicator to analyze Commitment of Traders (COT) data. It leverages the TradingView COT library to fetch data related to futures and options markets, processes this data, and then applies the Williams %R indicator to the COT data to assist in trading decisions. Here’s a detailed explanation of its components and functionality:
Importing and Configuration:
The script imports the COT library from TradingView and sets up tooltips to explain different input options to the user.
It allows the user to choose the mode for fetching COT data, which can be based on the root of the symbol, base currency, or quote currency.
Users can also input a specific CFTC code directly, instead of relying on automatic code generation.
Inputs and Parameters:
The script provides inputs to select the type of data (futures, options, or both), the type of COT data to display (long positions, short positions, etc.), and thresholds for the Williams %R indicator.
It also allows setting the period for the Williams %R calculation.
Data Request and Processing:
The dataRequest function fetches COT data for large traders, small traders, and commercial hedgers.
The script calculates the Williams %R for each type of trader, which measures overbought and oversold conditions.
Visualization:
The script uses background colors to highlight when the Williams %R crosses the specified thresholds for commercial hedgers.
It plots the COT data and Williams %R on the chart, with different colors representing large traders, small traders, and commercial hedgers.
Horizontal lines are drawn to indicate the upper and lower thresholds.
Display Information:
A table is displayed on the chart’s lower left corner showing the current COT data and CFTC code used.
Use of COT Report in Futures Trading
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides insights into the positions held by different types of traders in the futures markets. This information is valuable for traders as it shows:
Market Sentiment: By analyzing the positions of commercial traders (often considered to be more informed), non-commercial traders (speculative traders), and small traders, traders can gauge market sentiment and potential future movements.
Contrarian Indicators: Large shifts in positions, especially when non-commercial traders hold extreme positions, can signal potential reversals or trends.
Research on COT Data and Price Movements
Several academic studies have examined the relationship between COT data and price movements in financial markets. Here are a few key works:
"The Predictive Power of the Commitment of Traders Report" by Jacob J. (2009):
This paper explores how changes in the positions of different types of traders in the COT report can predict future price movements in futures markets.
Citation: Jacob, J. (2009). The Predictive Power of the Commitment of Traders Report. Journal of Futures Markets.
"A New Look at the Commitment of Traders Report" by Mitchell, C. (2010):
Mitchell analyzes the efficacy of using COT data as a trading signal and its impact on trading strategies.
Citation: Mitchell, C. (2010). A New Look at the Commitment of Traders Report. Financial Analysts Journal.
"Market Timing Using the Commitment of Traders Report" by Kirkpatrick, C., & Dahlquist, J. (2011):
This study investigates the use of COT data for market timing and the effectiveness of various trading strategies based on the report.
Citation: Kirkpatrick, C., & Dahlquist, J. (2011). Market Timing Using the Commitment of Traders Report. Technical Analysis of Stocks & Commodities.
These studies provide insights into how COT data can be utilized for forecasting and trading decisions, reinforcing the utility of incorporating such data into trading strategies.
Volatility System by W. WilderVolatility System (Volatility Stops) Similarity
Most traders adjust their stops over time in the direction of the trend in order to lock in profits. Apart from moving averages, one of the most popular techniques is trailing stops using a multiple of Average True Range. There are several variations:
The original Volatility System(Volatility Stops), introduced by Welles Wilder in his 1978 book: New Concepts in Technical Trading Systems
Chandelier exits introduced by Alexander Elder in Come Into My Trading Room (2002) trail the stops from Highs or Lows rather than Closing Price
Average True Range Trailing Stops are similar to the above, but include a ratchet mechanism to prevent stops moving down during an up-trend or rising during a down-trend, as ATR increases
WillTrend intoduced by Larry Williams in 1988
Comparison of systems
All the systems under consideration have one common ingredient - ATR. ATR was developed by Welles Wilder and described in his book in 1978, also in this book the Volatility System was described, which in the future became known as Volatility Stops.
In fact, Wilder is the father of such systems due to the presence of ATR in the calculation of this type of indicator.
The main difference of Volatility System
Followers such as Larry Williams and Alexander Elder made minor changes to the value based on the ATR, mainly focusing on changing the base to which this value is added or subtracted.
Larry Williams uses the square root of 5 as a multiplier and calculates the ATR with a period of 66, and Alexander Elder uses a multiplier of 2.5-3.5 applying it to the ATR with a period of 22. Both authors changed the original value for ATR and multiplier calculations. Alexander Elder is closest to the original Welles Wilder calculation, which used a multiplier of 2.8.-3.1 applying it to an ATR with a period of 7.
As a reference, Elder took the Highest High(22) from which he subtracts ATR*Multiplier in an uptrend or the Lowest Low(22) to which he adds ATR*Multiplier to obtain the turning point (SAR).
Larry Williams uses the average price of extremes (Highest High(10) + Lowest Low(10)) / 2 as a reference base to which he adds or subtracts the ATR*Multilpyer values.
Both systems differ from the original, because Wilder used Significan Close(SIC) in his calculations. SIC is the maximum closing price during an uptrend and the minimum closing price during a downtrend, which
does not go beyond the current trade, as in other systems. To calculate the base when a trend changes, bars that are outside the current trend will be used when calculating WillTrend and Chandelier Exit, in contrast to the Volatility System, which takes SIC values only within the current trade. This is the main difference from subsequent developments of similar systems.
Improvements made
The original Volatility System is present as an indicator on TradingView, but it is an improved version with the addition of a ratchet and works differently from the original Weilder system.
List of improvements:
Added the ability to remove the ratchet. You need to turn off the "Trail one way" checkbox in the setting menu. When this function is turned off, the system will operate in the author-inventor mode. On some instruments, the original system works much better than the improved ratchet system, which cannot be turned off.
Added the ability to use Highest High and Lowest Low as a base instead of the closing price.
Volatility Stops Formula Description
Welles Wilder's system uses Closing Price and incorporates a stop-and-reverse feature (as with his Parabolic SAR).
Determine the initial trend direction
Calculate the Significant Close ("SIC"): the highest close reached in an up-trend or the lowest close in a down-trend
Calculate Average True Range ("ATR") for the selected period (7 days in this example)
Multiply ATR by the Multiple (3.0 in this example, best values author describes as 2.8-3.1)
The first stop is calculated in day 7 and plotted for day 8
If an up-trend, the first stop is SIC - 3 * ATR, otherwise SIC + 3 * ATR for a down-trend
Repeat each day until price closes below the stop (or above in a down-trend)
Set SIC equal to the latest Close, reverse the trend and continue.
Chandelier Exit Description
Chandelier Exits subtract a multiple of Average True Range ("ATR") from the highest high for the selected period. Using the default settings as an example:
Highest High in last 22 days - 3 * ATR for 22 days
In a down-trend the formula is reversed:
Lowest Low in last 22 days + 3 * ATR for 22 days
The time period must be long enough to capture the highest point of the recent up-trend: too short and the stops move downward; too long and the high may be taken from a previous down-trend.
It is not essential to use the same period for up and down trends; down-trends are notoriously faster than up-trends and may benefit from a shorter time period.
The multiple of 3 may be varied, but most traders settle between 2.5 and 3.5.
WillTrend Description
Larry Williams is prefer to used the Square Root from 5 as a multiplayer for ATR. SQRT(5) = 2.236
WillTrend subtract a multiple of Average True Range ("ATR") from the Middle Price (Highest High for the selected period + Lowest Low for the selected period / 2).
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 - 2.236 * ATR for 66 days
In a down-trend the formula is reversed:
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 + 2.236 * ATR for 66 days
Jake Bernstein - Moving Average ChannelWe all know that moving averages, in particular, moving averages of closing prices tend to be highly inaccurate indicators and frequently miss major tops and bottoms. In backtesting, they tend to be accurate some 30 to 40% of the time which is to my way of thinking unacceptable. On the contrary moving averages of opens versus closes for highs versus lows, when used properly avoid the drawbacks of closing moving averages, particularly when combined with a trigger. Shown above is my moving average channel method which uses the 57 SMA of Williams accumulation distribution as a setup or trigger. As shown by the arrows two consecutive price bars completely below the MA channel low and triggered by Williams below SMA constitutes a sell signal. Conversely, two consecutive price bars or more above the moving average channel high accompanied by Williams above its moving average constitutes a sell trigger. The moving average channel high, the red line is a 10 period Moving average of highs. The Moving average channel low, the green line is an 8 period Moving average of the low. There are at least a dozen applications of this methodology including its ability to spot trend changes, support, resistance, swing trades, market strength, market weakness, and more. I will post some of these additional uses of the moving average channel as they present themselves. Do note that in this chart there were two instances above the moving average channel high but these were not triggered by Williams AD and therefore the trend remains down for the duration of this chart. The methodology associated with my MAC is completely rules-based and works in any timeframe. Thank you my friend Larry Williams for developing your excellent version of accumulation-distribution
