AI SMC Pro v2AI SMC Order Flow Pro v2.0 is an advanced Smart Money Concepts indicator combining ICT methodology, multi-timeframe analysis, Bayesian AI scoring, and order flow estimation — all in a single non-repainting overlay.
Core Features:
BOS & CHoCH structure detection
Bullish & Bearish Order Blocks (auto-invalidation)
Fair Value Gaps (auto-fill detection)
Liquidity levels (LQH / LQL)
Premium & Discount zones
Session High/Low (Asia, London, New York)
Support & Resistance (50-bar dynamic)
AI Engine:
Bayesian confidence score (0–100%) combining trend, momentum, MACD, volume, structure, order flow, MTF bias, session and zone
Three modes: Conservative / Balanced / Aggressive
Order Flow Module:
Estimated buy/sell pressure
Estimated delta & cumulative delta
Volume spike detection
Signals:
LONG / SHORT entries with SL, TP1, TP2
ATR-based risk management (customizable multipliers)
Minimum R:R filter (1:2 / 1:3 / 1:4)
Session filter (London & New York only)
MTF confirmation required
Built-in Backtest:
Win rate, Profit Factor, Expectancy
Max win/loss streak
Trailing stop & Break-even options
Best used on: EUR/USD · GBP/USD · 15m timeframe during London or New York session. Indicator
[3Commas] Trail Hunter - Indicator Trail Hunter - Indicator
🔷 What it does:
This indicator visualizes a long-only mean-reversion signal framework on liquid instruments. It marks dual-confluence entry signals (MA cross-under + CCI oversold), tracks a virtual deal lifecycle on the chart with trailing take-profit and hard stop loss management, and exposes webhook-ready alerts for automated execution through an external DCA Bot. No orders are placed by the indicator itself — it is a pure signal and visualization layer.
Base Order signal: SMA(24) crosses below SMA(31) on 1h (default) AND CCI(11) on 1h crosses below −80
Exit signal: trailing take-profit activated at +1.5% with 0.05% trailing deviation, or hard stop at −3.25%
Single entry per cycle — no averaging, no safety order ladder
On-chart virtual P&L tracker: Net Profit, Max Drawdown, Trades, Win Rate, Profit Factor
🔷 Who is it for:
Bot operators who need a visual confirmation layer for automated mean-reversion execution.
Discretionary traders who use dual-indicator confluence logic manually and want clear on-chart triggers.
Free-tier PulseWire users who want access to the same signal logic as the Strategy version without requiring backtest functionality.
Cross-instrument testers who run the same signal framework across crypto perpetuals, spot pairs, and equity tickers.
🔷 How does it work:
Long Entry: A long signal fires when two conditions align within a configurable keep-alive window — SMA(24) crosses below SMA(31) on the signal timeframe AND CCI(11) drops below −80 on the same timeframe. The indicator marks the entry with a green "L" triangle below the bar and stores the entry price as the reference for the trailing exit.
Short Entry: Not used — long-only signal framework by design.
Exit Management: Two exit conditions are armed simultaneously after entry. The trailing exit activates when price reaches Entry × (1 + Take Profit %), then follows the highest price reached with the deviation gap; if price retraces by the deviation amount from peak, the indicator marks the exit with a cyan diamond. The hard stop closes the virtual deal if price drops to Entry × (1 − Stop Loss %). Whichever condition fires first wins. The virtual P&L tracker captures the realized return at the actual fill price (peak − deviation for trail; SL price for stop).
🔷 Why it's unique:
Dual-indicator confluence — neither signal acts alone. The MA cross-under confirms short-term momentum exhaustion against the medium-term trend, and the CCI extreme confirms statistical oversold conditions. Requiring both filters out single-indicator false positives common to either condition during sideways regimes. Configurable keep-alive window (default 3 bars) lets the two confirmations align without requiring exact same-bar synchronization.
Trailing-exit architecture with full peak-tracking — the indicator computes the running peak from entry and triggers exit only when price retraces by the configured deviation from that peak. This is a true trailing simulation, not a fixed take-profit shortcut, and produces stats that match the underlying Strategy version closely.
Bot Integration — entry and exit alerts ship with webhook-ready JSON payloads, enabling direct trigger of a connected DCA Bot. Bot ID, Email Token, and pair label are exposed as inputs and automatically embedded into the alert message format.
🔷 What you'll see on the chart:
Cyan line — Fast MA on the signal timeframe (default SMA 24)
Orange line — Slow MA on the signal timeframe (default SMA 31)
Orange triangle (above bar) — MA cross-under signal fired
Cyan triangle (below bar) — CCI cross-under −80 signal fired
Green "L" triangle (below bar) — Combined entry signal armed; virtual deal opens
Cyan diamond — Trailing TP, fixed TP, or hard SL triggered; virtual deal closes
Cyan line (when in deal) — Entry price reference
Lime line (when in deal) — Trailing TP activation level
Red line (when in deal) — Stop Loss level
Stats card (top-left, configurable) — Live virtual backtest results: Net Profit, Max Drawdown, Total Trades, Win Rate, Profit Factor
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Designed for 1-hour base charts on liquid instruments with frequent MA crossings — major crypto perpetuals (BTC, ETH, SOL), spot pairs on Coinbase and Bybit, and high-volume equities. The signal timeframe is independent of the chart timeframe — you can run on a 15m chart with 1h signals if you want fine-grained visualization with structural signal timing.
Limitations: The indicator does not place orders. It tracks a "virtual deal" state on the chart for visualization purposes only — actual execution must be performed through a connected bot or manually. This is a single-entry framework with no averaging, so a wrong entry caps at the −3.25% hard stop without recovery. The strategy carries no higher-timeframe regime filter, so it can signal long entries during sustained downtrends. For deployment in bearish regimes, consider gating the alerts manually with a higher-timeframe trend filter.
Virtual P&L Accuracy: The on-chart stats card uses a simplified internal accounting model — it does not factor exchange commission or slippage. The trailing exit simulation uses peak-tracking on the chart bar's high, which is an approximation of real intra-bar execution. Use the Strategy version for fee-adjusted backtest results.
Backtesting & Demo Testing: Always validate the signal framework on historical data before connecting to a live bot. The companion Strategy version of this script is available on the same profile for full backtest analysis with realistic commissions and slippage. Demo-trade for at least one month to observe behavior in conditions not represented in historical data. Past performance is not indicative of future results.
Parameter Adjustments: MA lengths, CCI threshold, signal timeframe, take-profit activation, trailing deviation, and stop loss should all be tuned per instrument volatility profile. Lower-volatility instruments work better with tighter MA pair, lower CCI threshold, and smaller trailing deviation. Higher-volatility instruments need wider parameters.
🔷 Backtest Validation:
This indicator shares identical signal logic with the Strategy version of the same framework, available on this profile for full historical performance review with realistic commission and slippage:
Strategy version:
Reference results from the Strategy version on COINBASE:BTCUSD, 1h chart, tested period May 12, 2025 — May 12, 2026:
Net Profit: +13.09 USD (+0.13%) | Max Drawdown: 7.91 USD (0.08%) | Total Trades: 66 | Win Rate: 69.70% (46/66) | Profit Factor: 1.254
The strategy is positioned as a capital-preservation framework — extreme drawdown control (under 0.1% on the tested window) with positive expectancy. Refer to the Strategy publication for the complete equity curve, trade-by-trade breakdown, and Strategy Tester report.
🔷 How to Use It:
🔸 Adjust Settings: Configure the MA lengths, CCI threshold, signal timeframe, and exit parameters for the instrument you intend to trade. Defaults are calibrated for 1-hour BTC Spot on Coinbase. For lower-volatility instruments, tighten the MA pair and lower the trailing deviation; for higher-volatility instruments, do the opposite. The Initial Capital input (default 10,000) is used only for percentage calculations in the stats card — it does not affect signal logic.
🔸 Visual Confirmation: Use the on-chart projections (entry line, TP activation, SL level) to verify that the active virtual deal aligns with your bot's actual position. The indicator's virtual deal state is a 1-to-1 mirror of the Strategy version's signal logic, so any divergence between chart visuals and bot position is a flag for investigation. The MA and CCI signal triangles let you trace exactly when each condition fired in the entry stack.
🔸 Create alerts to trigger the DCA Bot: Two alert events are exposed by the indicator — "Deal Start" fires on each new combined entry signal, and "Deal Close" fires when any of the three exit conditions (trailing TP, fixed TP, or stop loss) triggers. Configure both alerts in PulseWire with the webhook URL pointing to your DCA Bot's signal endpoint. The Bot ID, Email Token, and Pair label can be set in the script's inputs and are automatically embedded into the alert JSON payload.
🔷 INDICATOR SETTINGS
MA Type — Moving average type for entry calculation (SMA or EMA).
Fast MA Length — Period of the fast moving average (default 24).
Slow MA Length — Period of the slow moving average (default 31).
MA Cross Timeframe — Timeframe on which the MA cross is computed.
Use MA Cross signal — Toggle the MA condition on or off in the entry stack.
CCI Length — Period for the CCI indicator (default 11).
CCI Oversold Threshold — Value below which CCI must cross to qualify as oversold (default −80).
CCI Timeframe — Timeframe on which the CCI cross is computed.
Use CCI signal — Toggle the CCI condition on or off.
Combine Signals — AND requires both conditions within the keep-alive window; OR fires on either alone.
Signal Keep-Alive (bars) — Number of bars within which both signals must align for AND mode (default 3).
Base Order Volume (USDT, ref) — Reference notional for virtual P&L calculation.
Take Profit % (activation) — Profit level at which the trailing exit arms.
Enable Trailing — Toggle trailing behavior on the take-profit exit.
Trailing Deviation % — Distance from the peak price at which the trailing exit fires.
Enable Stop Loss — Toggle the hard stop loss on or off.
Stop Loss % (from entry) — Maximum acceptable loss from entry price.
Initial Capital (ref for % calc) — Reference capital base for percentage metrics in the stats card.
Visual Layer toggles — Show/hide MA lines, entry line, TP/SL lines, signal triangles.
Stats card / Watermark — Display layer controls for on-chart virtual backtest summary and branding.
Webhook — Bot ID, Email Token, and Pair label for DCA Bot signal routing.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas PulseWire account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. Indicator
Lempel Ziv Trend Coder [forexobroker]Lempel Ziv Trend Coder encodes the recent sign sequence of price changes into 3-bit (sign , sign , sign ) windows and tracks the frequency distribution of the eight resulting patterns. When one pattern dominates the share, the price sequence is structurally biased — that is the trending regime. Direction comes from the up-bar fraction.
🔶 ALGORITHM
1. For each k in , encode (b0, b1, b2) where bi = close > close .
2. Increment count where p = b0 * 4 + b1 * 2 + b2 (0..7).
3. dominance = max(count) / sum(count). Uniform random = 0.125.
4. Trending regime when dominance >= threshold.
5. Direction bias from up-bar fraction in the same window.
🔶 SIGNAL LOGIC
- Buy: trending AND up-fraction > 0.5 AND close crosses EMA up AND not already long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: trending AND up-fraction < 0.5 AND close crosses EMA down.
- Position-lock state machine.
🔶 INPUTS
- Sign Window (default 40)
- Pullback EMA Length (default 8)
- Min Dominance (default 0.20)
- Cooldown Bars (default 4)
- Visual: dashboard, glow, EMA toggle, buy / sell colors
🔶 ALERTS
LZT Buy, LZT Sell, LZT Any Signal, LZT Trend Start, LZT Chop Start, LZT Very Trendy, LZT Very Choppy, LZT EMA Up, LZT Webhook JSON.
🔶 LIMITATIONS
- 3-bit encoding ignores bar magnitude; a tiny tick contributes the same as a large move.
- "Distinct patterns observed" alone saturates at 8 quickly with N >= 40 bars; dominance is a more discriminative measure but still coarse.
- LZ true complexity is closer to a substring count than a pattern-frequency count; this is a tractable approximation.
- Direction comes from up-fraction, not the LZ measure itself; in true random regimes the direction signal is meaningless and the regime gate correctly mutes signals.
Indicator
Indicator
WaveTrend XWaveTrend X (WVTX)
A WaveTrend rebuild from first principles. Where the classic WaveTrend ( LazyBear ) normalizes its Channel Index by an arbitrary 0.015 constant inherited from CCI and smooths the result with double exponential moving averages, WVTX replaces both with components that adapt to the data:
The CI normalization uses rolling standard deviation instead of 0.015.
The smoothing uses a 1-D Kalman filter with ATR-adaptive process noise instead of double-EMA.
The fixed ±60 / ±53 OB/OS bands become adaptive rolling-percentile bands.
Signals are gated by a Hurst regime proxy (mean-reversion vs trending) and a Shannon entropy filter (noise suppression).
Liquidity quality scales line opacity so low-volume readings visually fade.
All markers fire only on confirmed bars — explicitly no-repaint.
The default channel and signal periods are tuned for slower, more structural use than classic WaveTrend — see the Notes section for how to revert to classic intraday WT speeds.
How it works
The oscillator is built in five layers:
1. Channel Index (std-normalized). The standard WaveTrend CI is price's deviation from a moving average, normalized by a hard-coded constant. WVTX uses:
CI = (src − anchor) / stdev × 50
The anchor is VWMA (default) or EMA over the channel period. The stdev is computed over the same window. The constant disappears — the oscillator's amplitude now reflects actual recent volatility, not a one-size-fits-all multiplier.
2. Kalman smoothing. A 1-D Kalman filter replaces the double-EMA that produces the WT1 line in classic WaveTrend. The filter balances two tunable noise terms:
Process noise Q — how much you trust the CI to change between bars. Higher = faster, less smooth.
Measurement noise R — how much measurement error you assume. Higher = smoother, more lag.
With ATR-adaptive Q enabled (default), Q scales with normalized ATR — so the filter responds faster in volatile conditions and smooths harder in calm ones. This addresses classic WaveTrend's weakness of being either too slow during impulsive moves or too noisy during chop, never both right at once.
WT2 is then a longer EMA of WT1 (the signal line, classic WaveTrend convention).
3. Hurst regime proxy. A two-window standard-deviation ratio approximates the Hurst exponent:
H ≈ log₂(stdev(src, n) / stdev(src, n/2))
H > 0.5 = trending (volatility grows faster than √n); H < 0.5 = mean-reverting; H ≈ 0.5 = random walk. The configurable dead-band around 0.5 prevents constant regime-flipping near the boundary.
Signals are gated accordingly: in trending regimes, both cross directions are allowed; in mean-reverting regimes, signals only fire from the extremes (WT1 in the bottom or top 30%) where reversion probability is structurally elevated.
4. Shannon entropy noise gate. The recent return distribution is binned into 8 equal-width bins, and Shannon entropy computed:
H = −Σ pᵢ · log(pᵢ) / log(N_bins)
Bounded . Low entropy = concentrated return distribution (structured market); high entropy = uniform distribution (random/noise). When entropy exceeds the configured maximum (default 0.72), signals are suppressed — the oscillator stops emitting markers in conditions where the return statistics suggest no exploitable structure.
5. Adaptive OB/OS. Instead of fixed thresholds, OB and OS bands are the configurable percentiles (default 82% and 18%) of WT1's distribution over a rolling window. The bands move as the oscillator's range shifts — useful for instruments whose volatility regime changes substantially over time.
How to read it
Three lines and an area:
WT1 (main oscillator) — colored by its rolling percentile rank. Cool teal at the high extreme, slate near the middle, coral at the low extreme.
WT2 (signal line) — light slate, follows WT1 with EMA lag.
Diff = WT1 − WT2 (area) — teal area above zero, coral below. Visualizes the momentum between WT1 and the signal line.
Adaptive OB and OS bands are colored by direction (coral above, teal below), with tinted fills extending to the ±50 boundaries.
Background regime tint:
Teal — trending regime (Hurst above the band)
Purple — mean-reverting regime (Hurst below)
No tint — neutral / random walk
Entropy trace (amber, optional) — recentered around zero and scaled for visibility in the same pane. Above zero = recent returns more random than baseline; below zero = more structured.
Signal markers:
Teal triangle below pane — confirmed bullish cross (WT1 crosses up WT2, entropy structured, regime allows, WT1 in lower half)
Coral triangle above pane — confirmed bearish cross (same gates, opposite direction, WT1 in upper half)
Markers fire only on closed bars. There is no intra-bar signal display, by design.
Inputs
Price source — default hlc3.
Channel period — lookback for the VWMA/EMA anchor and stdev normalization. Default 40.
Signal period — EMA period for the WT2 signal line. Default 16.
VWMA anchor — use VWMA instead of EMA as the price anchor. Default on.
Kalman Q / R — process and measurement noise. Defaults 0.02 / 0.8.
ATR-adaptive Q — scale Q with normalized ATR. Default on.
Hurst regime gate / window / band — toggle, window, dead-band around 0.5. Defaults on / 60 / ±0.05.
Entropy noise gate / window / max — toggle, window, entropy ceiling. Defaults on / 40 / 0.72.
Liquidity quality scale / window — fade line opacity by recent volume rank. Defaults on / 50.
OB/OS rank window / overbought / oversold percentile — sets the adaptive bands. Defaults 100 / 82% / 18%.
Regime background / entropy trace — display toggles.
Built-in alerts
Bull cross — confirmed bullish crossover, gates passed
Bear cross — confirmed bearish crossover, gates passed
Bull cross, deep OS — bull cross from below the 20th percentile (high-quality setup)
Bear cross, deep OB — bear cross from above the 80th percentile (high-quality setup)
Trending regime — Hurst transitions into the trending zone
Mean-rev regime — Hurst transitions into the mean-reverting zone
The two "deep" alerts are the most actionable — a confirmed cross from the extremes of the rolling distribution is structurally more interesting than a cross near the middle.
Notes
The classic LazyBear WaveTrend uses channel period 10 and signal period 21 — fast, oscillator-style behavior suited to intraday momentum trading. WVTX's defaults are 40 and 16, four times slower. This is deliberate: with adaptive smoothing (Kalman + ATR), liquidity scaling, and entropy/regime gating layered on top, fast periods produce too many marginal signals for the gates to filter cleanly. Slower periods produce fewer but more structural crosses, which is where the gates earn their keep. If you want classic intraday WaveTrend behavior, set channel period to 10 and signal period to 21 — the math still works, just with more frequent (and noisier) output.
The Kalman smoother is the most consequential of the rebuilds. Classic WaveTrend's double-EMA introduces predictable lag that traders learn to anticipate; the Kalman filter's adaptive smoothing means the lag isn't constant — it tightens in fast moves and relaxes in chop. For mean-reversion traders, this means signal markers are closer to the actual reversal pivot. For trend-followers, it means the oscillator follows directional moves more responsively.
The Hurst regime gate makes the indicator behave differently in different markets. In a trending instrument (most major indices in their secular uptrends), the gate is permissive — crosses fire freely. In a mean-reverting instrument (ranging FX pairs, sideways equities), the gate restricts crosses to the extremes of the rolling distribution, where reversion probability is highest. The dead-band around 0.5 prevents flickering when the regime is ambiguous.
The entropy gate is the most novel filter. It asks a different question from regime detection: not "what kind of market is this" but "is there any structure in the recent return distribution?" When entropy is high (close to 1.0), the distribution looks essentially uniform — no recurring pattern for an oscillator to exploit. The gate stops signals from firing in those conditions, which historically catches a lot of false WaveTrend crosses during news-driven chop.
The adaptive OB/OS bands are tuned for traders who switch between instruments. Fixed ±60/±53 levels work fine on a single instrument with stable volatility; they're systematically wrong on instruments whose volatility regime changes substantially. Percentile bands self-calibrate, so the same indicator settings work across SPY, BTC, and EURUSD without manual retuning.
The non-repaint design is enforced by barstate.isconfirmed — signals fire only when the bar has closed and won't be revised. Intra-bar, you may see WT1 approaching a cross; the marker only appears once the bar closes with the cross confirmed. The conservative choice: signals you can rely on for backtesting and live execution, at the cost of waiting until the bar ends.
This is a signal generator with multiple filtering layers — but a signal is information, not an instruction.
Five years of work on a trading system left me with dozens of indicators that ultimately didn't earn a place in the final build. They're not failures — they're tools that solved problems I no longer needed solved. So instead of shelving them, I'm publishing the majority of them open-source.
If you're a discretionary trader, take what's useful. If you're a systems builder, the source is yours to dissect, modify, and improve. The best return on five years of work is for it to keep working — for someone.
If you use this script — or part of it — in your own work, please credit the original with a link back to my profile.
Note: these indicators have been updated to Pine Script v6 — some manually, some with AI assistance. Indicator
Indicator
Neural Weight Oscillator (Zeiierman)█ Overview
The Neural Weight Oscillator (Zeiierman) is an adaptive multi-factor oscillator that combines structured decision-making with dynamic market learning.
The script analyzes three core market behaviors: Trend, Mean Reversion, and Momentum. Instead of treating these components equally, the oscillator uses the Best-Worst Method (BWM) to determine which market behavior should have the greatest influence under current market conditions.
An adaptive training layer then studies historical market reactions and gradually amplifies the features that have recently produced the strongest directional behavior.
The result is a hybrid oscillator that blends:
Human-defined market logic
Adaptive feature weighting
Multi-factor momentum analysis
Dynamic market learning
Unlike traditional oscillators that rely on static formulas, the Neural Weight Oscillator continuously adjusts its internal structure based on both trader-defined weighting preferences and changing market behavior.
█ How It Works
⚪ Market Structure Engine
The oscillator builds its analysis from three independent behavioral models: Trend, Mean Reversion, and Momentum.
The Trend component measures structural direction by comparing the fast EMA against the slow EMA, then adds the EMA slope to capture acceleration.
trendSpread = (emaFast - emaSlow) / atr
trendSlope = (emaFast - emaFast ) / atr
trendScore = normalize(trendSpread + trendSlope, -2.5, 2.5)
The Mean Reversion component measures stretched conditions using RSI exhaustion and statistical deviation from the market mean.
zScore = dev == 0 ? 0 : (close - basis) / dev
meanScore = (100 - rsi) * 0.5 + normalize(-zScore, -2.5, 2.5) * 0.5
The Momentum component measures directional acceleration using ROC, RSI momentum, and EMA velocity.
rocNorm = normalize(close / close - 1.0, -0.05, 0.05)
momentumScore = rocNorm * 0.45 + rsi * 0.35 + emaMomentum * 0.20
Each component produces its own normalized score before being blended into the final oscillator.
⚪ Best-Worst Method (BWM)
The core weighting system in the oscillator is based on the Best-Worst Method (BWM), a structured decision-making framework that creates balanced weighting relationships among multiple factors.
bestIdx = criterionIndex(bestCriterion)
worstIdx = criterionIndex(worstCriterion)
array.set(bo, bestIdx, 1.0)
array.set(ow, worstIdx, 1.0)
Instead of assigning arbitrary percentages manually, BWM allows the trader to define which market behavior matters most and which matters least. The script then automatically calculates balanced internal weights.
The process begins by selecting:
The “Best” factor → the market behavior trusted most
The “Worst” factor → the market behavior trusted least
relWeight = math.sqrt((aBW / boVal) * owVal)
The oscillator then compares all remaining factors relative to those two extremes and converts those relationships into normalized internal weights.
⚪ How To Think About The BWM Weights
The easiest way to think about BWM is:
“What type of market behavior do I trust most in the current environment?”
Different market conditions naturally favor different behaviors.
In strong directional trends , traders often prioritize Trend because structural continuation becomes the dominant force.
In choppy or range-bound markets , Mean Reversion may become more important because the market repeatedly returns back toward equilibrium.
During aggressive breakout environments , Momentum may deserve the highest weighting because acceleration becomes the primary driver.
The goal is not to find a “perfect” weight configuration, but rather to align the oscillator with the type of behavior currently dominating the market.
⚪ Adaptive Neural Training Layer
The oscillator includes an adaptive learning layer that learns how the market has recently reacted to the model’s internal features.
The script looks back at prior Trend, Mean Reversion, and Momentum feature values, then compares them to the future price reaction.
target = close / close - 1.0
targetDirection = target > 0 ? 1.0 : target < 0 ? -1.0 : 0.0
High-quality samples are ranked by how strong the move was relative to volatility.
sampleScore = math.abs(target) / qualityVol
The model then compares its internal prediction against the actual market direction and adjusts the learned feature weights over time.
pred = twTrend * s.trend + twMean * s.mean + twMomentum * s.momentum + tbias
err = pred - s.target
This allows the oscillator to gradually learn which features are producing the strongest directional behavior.
⚪ Adaptive Feature Amplification
The learned weights are converted into feature amplifiers.
trendAmplifier = 1.0 + learnTrend * blend
meanAmplifier = 1.0 + learnMean * blend
momentumAmplifier = 1.0 + learnMomentum * blend
This allows stronger features to gain more influence, while weaker features receive less influence.
█ How to Use
⚪ Reading the Oscillator
The oscillator operates between 0 and 100.
Values above 50 suggest bullish pressure dominates the market, while values below 50 suggest bearish pressure dominates.
As the oscillator moves farther away from the neutral 50 level, directional imbalance becomes stronger.
Readings above 70 typically indicate strong bullish expansion, while readings below 30 indicate strong bearish pressure. Extreme zones above 80 or below 20 may signal exhaustion conditions where reversals become more likely.
⚪ Using the BWM Weighting System
The BWM system allows traders to align the oscillator with current market behavior by controlling how much influence Trend, Mean Reversion, and Momentum should have inside the model.
Imagine the market is trending strongly upward.
You may believe:
Trend is the dominant market behavior.
Mean Reversion still matters during pullbacks.
Momentum should have the least influence.
In this case, you could choose:
Best = Trend
Worst = Momentum
You then control how strongly Trend dominates the other factors through the comparison inputs.
For example:
Best-to-Others:
Trend = 1
Mean = 3
Mom = 6
Relative-to-Worst:
Trend = 4
Mean = 2
Mom = 1
This tells the oscillator:
Trend is selected as the strongest market behavior.
Momentum is selected as the weakest market behavior.
Trend is 3x more important than Mean Reversion.
Trend is 6x more important than Momentum.
Mean Reversion is 2x more important than Momentum.
The script automatically converts these relationships into balanced internal weights.
As a result, the oscillator becomes more trend-sensitive while reducing the influence of short-term momentum fluctuations and weak counter-trend behavior.
If the market becomes highly rotational or range-bound, traders may instead increase the importance of Mean Reversion so the oscillator becomes more responsive to exhaustion and reversal conditions.
During aggressive breakout environments, increasing Momentum weighting can help the oscillator react faster to acceleration phases.
The weighting system is designed to adapt the oscillator’s personality to different market environments rather than forcing one static interpretation onto every condition.
█ Settings
Fast EMA: controls the responsiveness of the Trend and Momentum calculations.
Slow EMA: controls the structural trend baseline used throughout the oscillator.
Smoothing: controls the smoothness of the final oscillator line.
The Best and Worst: determine how the BWM weighting model prioritizes market behaviors.
Best-to-Others: define how strongly the selected Best factor dominates the remaining components.
Relative-to-Worst: define how much stronger each component is compared to the selected Worst factor.
Use Training: enables the adaptive learning layer.
Influence: controls how strongly the learned model amplifies features.
Line Impact: controls how much the adaptive model can directly influence the oscillator line itself.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
VuManChu B PRO - Confluence EditionVersão refinada do clássico VuManChu Cipher B Divergences, focada em reduzir ruído e aumentar a assertividade dos sinais através de filtros de contexto e um sistema de score de confluência.
🙏 Créditos
Este indicador é uma evolução do trabalho original do VuManChu (Cipher B Divergences), que por sua vez foi inspirado em códigos de:
dynausmaux — código base
LazyBear — WaveTrend Oscillator
RicardoSantos — Divergence Detector
LucemAnb — Plain Stochastic Divergence
andreholanda73 — MFI+RSI Area
falconCoin — Market Cipher B free version
Todo o crédito da matemática original (WaveTrend, divergências, MFI, Stoch RSI, Schaff) vai para esses autores. Esta versão mantém os cálculos e adiciona uma camada de filtros e lógica de sinal.
⚡ O que mudou em relação ao original
🐛 Correções de bugs
Removido barmerge.lookahead_on no acesso a timeframes superiores. O original "vazava" dados do futuro no backtest, gerando uma falsa impressão de precisão. Agora usa lookahead_off — backtest honesto.
Migração para Pine Script v5 — código mais performático, seguro e moderno.
Alertas só disparam em barstate.isconfirmed — eliminado o problema de alertas que apareciam intrabar e sumiam (repaint de alerta).
🛡️ Filtros de contexto (a maior mudança)
O original mostrava sinais sem considerar o contexto de mercado. Agora há 4 filtros que podem ser ligados/desligados individualmente:
Filtro de tendência (EMA 50/200): bloqueia sinais contra-tendência quando a tendência é forte. Evita "pegar faca caindo".
Filtro de regime (ADX 14): descarta sinais em mercado morto (ADX < 15) e bloqueia divergências contrárias em tendência muito forte (ADX > 40).
Filtro de volume: exige volume acima da média (configurável). Divergência sem volume é quase sempre falsa.
Filtro de volatilidade (ATR): descarta velas pequenas demais (ruído de range).
🎯 Sistema de Score de Confluência
Em vez de plotar todos os sinais (como o original fazia), o PRO usa um score de 0 a 6 pontos. O sinal só aparece quando o score atinge o mínimo configurável (padrão: 3).
Critério Pontos padrão
WT cross em zona OB/OS +1
Divergência WaveTrend +2
Divergência RSI +1
MFI alinhado (>0 compra, <0 venda) +1
Stoch RSI cruzando em zona extrema +1
Tendência a favor (EMA) +1
Triângulo verde-claro = score atingiu o mínimo.
Triângulo verde-escuro = score forte (mínimo + 1 ou mais).
Todos os pesos são configuráveis — você pode dar mais peso ao critério que confia mais.
🕐 Cooldown anti-whipsaw
Configurável (padrão: 5 barras). Após um sinal, bloqueia novos sinais na mesma direção pelo período definido. Elimina aqueles clusters de pontos seguidos que confundiam o original.
📋 Painel de status em tempo real
Label flutuante no canto direito mostra:
Score atual de compra e venda
Valor do ADX e classificação (forte/ok/fraco)
Direção da tendência (UP/DOWN/FLAT)
Status dos filtros de volume e ATR
Você vê na hora por que um sinal está ou não sendo gerado.
🔄 Modo Clássico opcional
Toggle no topo: desligando o "Modo PRO", o indicador volta ao comportamento original do VuManChu. Útil pra comparar lado a lado.
🥇 Gold Buy preservado
O famoso círculo dourado do VuManChu foi mantido, mas agora também passa pelos filtros de contexto — fica ainda mais raro e ainda mais confiável.
📈 Como usar
Sinais principais
Sinal Significado
🔺 Triângulo verde PRO BUY — confluência mínima atingida
🟢 Triângulo verde escuro PRO BUY forte — score acima do mínimo
🔻 Triângulo vermelho PRO SELL
🟡 Círculo dourado Gold Buy — alta probabilidade (raro)
⚪ Círculos pequenos WaveTrend cross (informacional)
Timeframes recomendados
Sweet spot: 1h, 4h, 12h
Excelente para swing/DCA: Diário, Semanal
Funciona com ajustes: 15m, 30m (subir score mínimo para 4)
Não recomendado: abaixo de 15m
Configuração rápida por estilo
Day trade (15m–1h):
Score mínimo: 4
Cooldown: 8 barras
ADX mínimo: 20
Swing (4h–12h):
Score mínimo: 3 (padrão)
Cooldown: 5 (padrão)
DCA / Position (Diário–Semanal):
Score mínimo: 4
Foco em Gold Buy
Ignorar sinais de venda
🚨 Alertas disponíveis
PRO Buy — sinal de compra com score atingido
PRO Sell — sinal de venda com score atingido
Gold Buy — sinal raro de alta probabilidade
Classic Buy/Sell — versão original (se quiser usar)
Todos os alertas disparam apenas em barra fechada (sem repaint).
⚠️ Disclaimer
Este indicador é uma ferramenta de análise, não uma recomendação de investimento. Nenhum indicador acerta 100%. Use sempre:
Gerenciamento de risco (stop loss, position sizing)
Confluência com sua própria análise
Backtest no seu ativo e timeframe antes de usar capital real
Mercado é probabilidade, não certeza. DYOR.
🤝 Open Source
Código aberto sob licença Mozilla Public License 2.0 (mesma do original). Fique à vontade para forkar, melhorar e contribuir.
Se gostou, deixe um boost ⚡ e compartilhe seu setup nos comentários — ajuda outros traders a calibrar os filtros para seu mercado.
Bons trades! 📈 Indicator
Indicator
Momentum Pulse | AnonycryptousMomentum Pulse | Anonycryptous
Description & user manual
Why this indicator is different
Standard momentum indicators give you one line. RSI tells you whether the market is overbought or oversold at one specific lookback period. MACD tells you whether one moving average is pulling away from another. One perspective. One answer.
The problem is that momentum does not exist at one lookback period. A 14-period RSI can be flat while a 7-period RSI is already reversing. A 21-period RSI can still be bullish while the fast momentum has already rolled over. By looking at one line you are always missing what is happening at adjacent timescales — and those are precisely where the early signals live.
Momentum Pulse works differently.
Instead of one RSI it runs twenty simultaneously, each at a different lookback period. The shortest strand captures the fastest momentum shifts. The longest strand reflects the slower, sustained trend. Together they form a ribbon — a fluid, living visualization of where momentum is coming from, where it is heading, and how much agreement exists across timescales.
The ribbon does not just show direction. It shows compression and expansion. When the strands fan out, momentum is building with conviction. When they compress, the market is coiling — and that compression often precedes the next directional move. When the fast strands lead the slow strands, the trend has energy behind it. When they cross or collapse toward each other, momentum is fading before it is visible in price.
This is momentum before the move.
Important notice
Momentum Pulse is provided for analytical and educational purposes only.
It does not generate trading signals.
It does not predict market direction.
It does not guarantee any outcome.
All trading decisions remain entirely with the user.
Always apply your own judgment and manage your own risk.
1. Overview
Momentum Pulse is a twenty-strand RSI ribbon oscillator built on RSI processed through zero lag EMA smoothing. It maps momentum across twenty simultaneous lookback periods and visualizes the full structure of momentum strength, direction, compression, and divergence in a single pane.
What it includes:
- Twenty RSI strands normalized to a −50 to +50 scale around a zero midline
- Zero lag EMA smoothing applied per strand to reduce response lag
- Fast and slow group averaging with spread-based trend detection
- Twist/Squeeze detection when fast and slow groups compress below the threshold
- Momentum histogram showing the distance between fast and slow group averages
- Ribbon slope line showing the rate of change of the fast group average
- Divergence detection comparing price pivots with fast group momentum pivots
- Three presets: default for swing, fast for scalping, smooth for position trading
- Live dashboard showing momentum state, averages, spread, twist, zone, slope, and divergence
- Six alert conditions covering state changes, compression, and divergence events
2. Core components
2.1 RSI strands
Twenty RSI calculations run simultaneously, each at a different lookback period. The first strand uses the base length. Each subsequent strand adds the length step, spreading the ribbon from fast to slow momentum perspectives. All values are normalized to a −50 to +50 scale around a zero midline, making every strand directly comparable regardless of its period.
2.2 Zero lag EMA smoothing
Each RSI strand is smoothed using a zero lag EMA. Standard EMA smoothing introduces lag because it weights recent bars less than current price. ZLEMA compensates by incorporating the momentum of recent change before applying the average — the ribbon reacts to momentum shifts on the current bar, before the move has confirmed on price.
2.3 Fast and slow group trend detection
The ribbon is divided into two groups. The fast group uses strands one through five — the shortest lookback periods. The slow group uses strands sixteen through twenty — the longest. When the fast group average is above the slow group average, momentum is bullish. When it is below, momentum is bearish. When the spread between the two groups falls below the twist threshold, the oscillator enters a Twist/Squeeze state.
This logic is independent of overbought and oversold levels and works reliably in all market conditions.
2.4 Momentum histogram
The histogram plots the distance between the fast and slow group averages near the zero midline. Wide bars indicate strong momentum separation — the trend has conviction. Narrow bars indicate the ribbon is compressing — momentum is fading or transitioning.
2.5 Ribbon slope
The slope line measures the rate of change of the fast group average over a configurable number of bars. A rising slope indicates momentum is accelerating into the trend. A falling slope indicates momentum is decelerating, a possible sign of exhaustion. A flat slope indicates consolidation or a transition that has not committed to a direction.
2.6 Divergence detection
The indicator compares recent price pivots against fast group average pivots over a configurable lookback window. A bullish divergence fires when price makes a lower low but the fast group average holds higher — hidden strength beneath the surface. A bearish divergence fires when price makes a higher high but the fast group average rolls over — hidden weakness. Both conditions trigger a background flash on the pane.
3. Presets
Three preset configurations are available. Selecting a preset overrides the core calculation parameters.
-Default — swing trading on 4H and daily charts
RSI base 10 | ZLEMA 5 | step 2 | twist threshold 1.5
Balanced ribbon for trend following and swing setups across most market conditions.
-Fast — scalping on 1 minute to 15 minute charts
RSI base 7 | ZLEMA 3 | step 2 | twist threshold 1.0
Shorter periods and a tighter twist threshold for early detection of momentum shifts and reversals before they appear in price.
-Smooth — position trading on daily and weekly charts
RSI base 14 | ZLEMA 8 | step 3 | twist threshold 2.5
Wider spread and longer periods. Only high-conviction momentum moves register. Filters out intraday noise.
4. Visual guide
Ribbon fanning upward — bullish momentum expanding across multiple timescales.
Ribbon fanning downward — bearish momentum expanding.
Ribbon compressing toward center — Twist/Squeeze state, potential breakout building.
Grey background shading — active Twist/Squeeze state.
Green background flash — bullish breakout bar, ribbon exiting compression.
Red background flash — bearish breakout bar.
Warm/orange flash — bullish divergence detected.
Red dim flash — bearish divergence detected.
Green circle at oversold — bullish signal condition.
Red circle at overbought — bearish signal condition.
Histogram bars — momentum strength between fast and slow groups. Wide = strong trend. Narrow = compression.
Slope line — acceleration or deceleration of fast group momentum.
5. Dashboard reference
The dashboard provides live readings across all components.
Momentum — current ribbon state: bullish, bearish, or twist.
Fast avg — average of the five fastest strands.
Slow avg — average of the five slowest strands.
Spread — distance between fast and slow group averages.
Twist — whether the ribbon is compressed below the twist threshold.
Zone — whether the ribbon is extended, compressed, or neutral relative to overbought/oversold levels.
Slope — momentum acceleration state: accel, decel, or flat.
Divergence — active bullish divergence, bearish divergence, or none.
Signal — last signal fired.
6. Alerts
Six alert conditions are available:
- Bullish: ribbon flips to bullish state.
- Bearish: ribbon flips to bearish state.
- Twist: ribbon enters Twist/Squeeze compression.
- Bullish divergence: price makes a lower low while momentum holds higher.
- Bearish divergence: price makes a higher high while momentum weakens.
- Any change: fires on any of the above transitions.
All alerts include exchange, ticker, and interval in the message.
7. Settings reference
Calculation parameters
- Source: price input for RSI calculations
- Base length: lookback period for the fastest ribbon strand
- Length step: increment between each subsequent strand
- RSI length: base RSI period for all strand calculations
- ZLEMA length: zero lag EMA smoothing period per strand
- Twist threshold: minimum spread required to declare a trend; below this = Twist/Squeeze
- Divergence lookback: window for comparing price and momentum pivots
- Slope length: bars used to calculate ribbon acceleration
- Preset: default, fast, or smooth
Visualization settings
- Color preset: classic (green/red) or custom
- Bullish, bearish, and twist/squeeze colors
- Min transparency: opacity of the fastest (leading) strand
- Max transparency: opacity of the slowest (lagging) strand
Level settings
- Overbought level: reference line (does not affect trend logic)
- Oversold level: reference line (does not affect trend logic)
Dashboard settings
- Show dashboard
- Dashboard size: tiny, small, or normal
8. How to use
8.1 Lower timeframes (1 minute to 15 minutes)
Use the fast preset. Monitor the ribbon for compression before expansion — Twist/Squeeze states often precede directional moves. A rising slope combined with bullish ribbon expansion confirms momentum is accelerating. A divergence forming while the ribbon is still in compression indicates a directional move is building before it appears in price.
Only take bullish setups when the ribbon is bullish or just exiting a Twist state with a rising slope and no active bearish divergence. Only take bearish setups with the reverse conditions.
8.2 Higher timeframes (1H, 4H, daily)
Use the default preset on 1H and 4H. Use the smooth preset on daily and weekly charts.
A wide, sustained ribbon fan on higher timeframes confirms momentum has conviction. Ribbon compression while price action narrows indicates trend exhaustion — consider reducing exposure and waiting for re-expansion. Divergence on daily charts carries significant weight and should be treated as a major reversal warning.
8.3 Dashboard reading guide
Slope accel + momentum bullish — trend strengthening, momentum building.
Slope decel + momentum bullish — trend weakening, watch for reversal.
Divergence bear + trend bullish — exit warning, confluence fading.
Twist yes + spread narrowing — breakout setup forming, wait for direction.
8.4 Standalone use
Momentum Pulse works as a standalone oscillator for any strategy or existing indicator setup. The ribbon provides directional momentum bias. The divergence detector flags hidden reversals before they appear in price. The slope line shows whether momentum is building or fading. The histogram confirms trend strength between fast and slow groups. No other indicator is required.
9. Disclaimer
This indicator is provided for educational and informational purposes only.
All outputs are based on historical price action calculations and do not guarantee future results.
Trading financial instruments involves significant risk of loss.
Past performance does not indicate future results.
Use at your own discretion.
Indicator
Indicator
Goertzel Cycle Hunter [forexobroker]Goertzel Cycle Hunter scans seven Fibonacci-spaced cycle periods (5, 8, 13, 21, 34, 55, 89) using the Goertzel filter — a tuned single-frequency DFT that runs in O(N) per period. The dominant cycle's reconstructed cosine drives the trigger, gated by a power-ratio regime that confirms the cycle is real and not noise.
🔶 ALGORITHM
1. Detrend source = (high + low) / 2 minus its N-bar SMA, isolating the oscillatory component.
2. For each period N in , run the Goertzel recursion: s = x + 2 cos(2 pi / N) * s - s .
3. Power = s1^2 + s2^2 - 2 cos(omega) * s1 * s2; reconstructed cosine = s1 - s2 * cos(omega).
4. Dominant period = argmax(power); power ratio = max_power / sum_power.
5. Rhythm regime active when power ratio >= threshold AND ATR > k * 50-bar SMA.
🔶 SIGNAL LOGIC
- Buy: rhythm active AND reconstructed cosine crosses zero up AND not already long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: mirror with crossunder.
- Position-lock state machine.
🔶 INPUTS
- Goertzel Window (default 120)
- Min Power Ratio (default 0.20)
- ATR Activity Floor (default 0.20)
- Cooldown Bars (default 4)
- Visual: dashboard, glow, trend mid line, buy / sell colors
🔶 ALERTS
GCH Buy, GCH Sell, GCH Any Signal, GCH Rhythm Start, GCH Rhythm End, GCH Phase Up, GCH Phase Down, GCH Strong Cycle, GCH Webhook JSON.
🔶 LIMITATIONS
- Cycle hunting is meaningful only when the market actually has a dominant rhythm; in trending or trapped regimes the power ratio stays low and signals mute correctly.
- Computational cost = 7 Goertzel runs of N samples per bar. Defaults (N = 120) balance fidelity vs load.
- The seven Fibonacci periods are a coarse grid; true dominant cycle may fall between (e.g., 16, 27 bars). User can re-tune the window length to bias toward shorter or longer cycles.
- Detrend is SMA-based; structural breaks within the window can bias the cosine reconstruction for a few bars.
Indicator
Fourier Phase Rotation [forexobroker]Fourier Phase Rotation reconstructs the fundamental phase of a 4-bar sliding window using sine and cosine projections. The phase angle phi rotates through the unit circle as the cycle progresses; a zero-cross of phi marks a cycle low (buy timing) or high (sell timing). Distinct from Hilbert: 4-point projection, no IIR filter ringing.
🔶 ALGORITHM
1. Detrended source = close - sma(close, N).
2. 4-point DFT bin 1 cosine: re = c0 - c2; sine: im = c1 - c3 where c_k = detrended source at lag k.
3. phase phi = atan(im / re), in .
4. Cycle-low complete = phi crosses zero up; cycle-high complete = phi crosses zero down.
5. Bias from close vs detrend SMA gates direction.
🔶 SIGNAL LOGIC
- Buy: phase up-cross AND close > detrend SMA AND not already long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: phase down-cross AND close < detrend SMA.
- Position-lock state machine.
🔶 INPUTS
- Detrend SMA Length (default 20)
- Pullback EMA Length (default 8)
- Cooldown Bars (default 4)
- Visual: dashboard, glow, SMA toggle, buy / sell colors
🔶 ALERTS
FPR Buy, FPR Sell, FPR Any Signal, FPR Phase Up, FPR Phase Down, FPR Bias Up, FPR Bias Down, FPR Near Pi/2, FPR Webhook JSON.
🔶 LIMITATIONS
- 4-point projection has a fixed period of 4 bars; assumes any cycle of interest is roughly that scale. Longer cycles fold into the bias trend.
- atan (vs atan2) gives phase in ; sufficient for zero-cross detection but does not preserve quadrant disambiguation.
- Detrend SMA length is the dominant smoothing knob; longer SMA = cleaner cycle, more lag.
- Best on instruments with rhythmic intraday patterns; pure trends give muted phase oscillations.
Indicator
Indicator
Cumulative Delta Divergence [forexobroker]Cumulative Delta Divergence detects exhaustion patterns where price extends but cumulative tick-rule signed volume does not follow. The z-scores of cumulative delta and price over the same window are differenced; sustained gaps mark institutional positioning against the current move. Signals fire on EMA cross in the resolution direction.
🔶 ALGORITHM
1. signed_vol = volume * sign(close - close ).
2. cum_delta = sum(signed_vol, N).
3. delta_z = cum_delta / (stdev(signed_vol, N) * sqrt(N)).
4. price_z = (close - sma(close, N)) / stdev(close, N).
5. divergence = price_z - delta_z. Bear divergence when divergence >= threshold; bull when <= -threshold.
🔶 SIGNAL LOGIC
- Buy: bull divergence AND close crosses EMA up AND not already long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: bear divergence AND close crosses EMA down.
- Position-lock state machine.
🔶 INPUTS
- Cumulative Window (default 40)
- Pullback EMA Length (default 8)
- Min Divergence Z (default 0.30)
- Cooldown Bars (default 4)
- Visual: dashboard, glow, EMA toggle, buy / sell colors
🔶 ALERTS
CDD Buy, CDD Sell, CDD Any Signal, CDD Bull Div On, CDD Bear Div On, CDD Strong Bear, CDD Strong Bull, CDD EMA Up, CDD Webhook JSON.
🔶 LIMITATIONS
- Tick-rule signed volume (sign of close - close ) is a proxy; true bid / ask delta requires order-book data not available in Pine.
- Forex broker volumes vary; instruments with consistent volume reporting produce cleaner divergences.
- Window N = 40 is the practical balance; shorter windows fire more but flag false divergences.
- Divergence resolution timing varies; some divergences last many bars before resolving.
Indicator
Bayesian Trend Posterior [forexobroker]Bayesian Trend Posterior treats each bar as a Bernoulli observation (up vs not-up) and runs a Beta-Bernoulli sequential update over a sliding window. The posterior probability P(next bar up) = (alpha + u) / (alpha + beta + N), where u is the count of up-bars in the window. Schmitt hysteresis on the posterior locks bull or bear regimes, preventing chatter near 0.5.
🔶 ALGORITHM
1. Count up-bars u in the last N closes (close > close ).
2. Posterior mean = (alpha + u) / (alpha + beta + N) using Beta(alpha, beta) prior.
3. Hysteresis: regime locks to +1 when posterior >= upper threshold, locks to -1 when posterior <= lower threshold, holds otherwise.
4. Within a locked regime, an EMA cross provides the entry trigger so the indicator can fire multiple times during sustained trends.
🔶 SIGNAL LOGIC
- Buy: bull regime locked AND close crosses pullback EMA up AND not already long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: bear regime locked AND close crosses pullback EMA down.
- Position-lock state machine.
🔶 INPUTS
- Posterior Window N (default 30)
- Prior alpha (default 2.0)
- Prior beta (default 2.0)
- Upper Hysteresis (default 0.55)
- Lower Hysteresis (default 0.45)
- Pullback EMA Length (default 8)
- Cooldown Bars (default 4)
- Visual: dashboard, glow, EMA toggle, buy / sell colors
🔶 ALERTS
BTP Buy, BTP Sell, BTP Any Signal, BTP Bull Lock, BTP Bear Lock, BTP High Posterior, BTP Low Posterior, BTP Cross 0.5, BTP Webhook JSON.
🔶 LIMITATIONS
- Bernoulli simplification ignores bar size; a tiny up-bar contributes the same as a strong one. Pair with an ATR-aware filter for size-weighted posteriors.
- Window N is the dominant tuning knob: smaller N reacts faster but flips more; larger N is steadier.
- Prior alpha = beta = 2 is uninformative; users with strong directional bias can adjust.
- Hysteresis prevents chatter but slightly delays regime detection vs threshold-only logic.
Indicator
Multi-System (RSI2 + Squeeze + MACD/ADX)Confluence Multi-System combines three independent, well-documented signal frameworks into a single overlay and only fires alerts when two or more agree on direction. The goal is to filter noise: each system has its own logic and failure mode, so coincidence between them is statistically rarer and historically higher quality than any individual signal.
THE THREE SYSTEMS
System 1 — Mean Reversion (RSI-2 + Williams %R + 200 SMA)
Larry Connors-style countertrend setup. Trades only in the direction of the 200 SMA trend filter, requires RSI(2) at an extreme (<5 long, >95 short) and Williams %R(10) confirming (<-90 long, >-10 short). Designed for pullbacks within a trend, not reversals against it.
System 2 — TTM Squeeze
Classic John Carter volatility compression setup. Detects when Bollinger Bands(20, 2.0) contract inside Keltner Channels(20, 1.5) — a "squeeze" — then signals on the release in the direction of a linear-regression momentum oscillator. Catches breakouts after consolidation.
System 3 — Triple Confirmation (MACD + RSI + ADX)
Trend-following filter stack. Long requires MACD(12,26,9) bullish cross + RSI(14) > 50 + ADX(14) > 25. Short is the mirror. ADX gates out chop; RSI confirms the cross is in the dominant momentum side.
CONFLUENCE LOGIC
The indicator counts how many systems are signaling in the same direction on the same bar:
• 3/3 → STRONG signal (background tinted, label printed, dedicated alert)
• 2/3 → MEDIUM signal (lighter tint, dedicated alert)
• <2 → no signal, no alert
The minimum number of systems required can be configured (default 2). You can also disable any system individually if you want to test 2-of-2 confluence on specific pairs.
WHAT YOU SEE ON THE CHART
• Background tint on confluence bars (green/red strong, lime/fuchsia medium)
• Labels marking the bar where confluence first appears
• 200 SMA plotted as visual reference for the System 1 trend filter
• A status table (top-right) showing for each system: long/short state, key indicator values (RSI, Williams %R, ADX, squeeze state, momentum), plus a summary row with the current confluence level
ALERTS
Six alertconditions are exposed:
• STRONG LONG (3/3) / STRONG SHORT (3/3)
• MEDIUM LONG (2/3) / MEDIUM SHORT (2/3)
• ANY CONFLUENCE LONG / ANY CONFLUENCE SHORT (respect the configured minimum)
Alerts include ticker, interval, and close price via standard PulseWire placeholders.
INPUTS
All three systems are fully parametrized: SMA length, RSI/Williams %R lengths and thresholds, Bollinger and Keltner lengths and multipliers, MACD periods, ADX length and minimum strength. Defaults match the original published values for each framework.
USE CASES
• Day trading on lower timeframes — wait for 2/3 or 3/3 to enter, exit on opposite confluence or your own stop
• Swing trading on 1H/4H/Daily — confluence becomes rare but high quality
• As a confirmation layer over your own strategy — read the table to see which systems agree before pulling the trigger
NOTES AND DISCLAIMERS
This is an indicator, not a strategy — it does not place orders, manage stops, or compute P&L. Win-rate ranges referenced for each underlying system come from the original literature (Connors, Carter, Wilder/Appel) and are heavily dependent on instrument, timeframe, and exit logic. Past performance does not guarantee future results. Always backtest with your own exit rules before trading live.
Open source — fork it, adapt the thresholds, plug in your own systems. Indicator
Indicator
Detrended Price Oscillator - Valuation and Trend | Astral VisionDetrended Price Oscillator - Valuation and Trend | Astral Vision 🌠💠
The Detrended Price Oscillator removes the dominant trend from price by subtracting a lagged moving average, isolating the cyclical component that trends obscure.
The result is an oscillator centered around zero that reflects how far price has deviated from its medium-term mean, independent of whether the broader trend is up or down.
This indicator extends the standard DPO with two structural additions.
First, dynamic overbought and oversold bands are derived from the rolling standard deviation of the DPO itself, making the extremes statistically adaptive rather than fixed.
Second, an optional moving average smoothing layer can be applied to the DPO before all calculations, reducing noise on lower timeframes.
Two modes cover different use cases:
"Extremes" identifies statistically significant deviations from the mean with explicit entry/exit signals, while "Trend" tracks whether the smoothed DPO is above or below its rolling mean as a directional read.
Calculation ⚙️
`DPO = close − SMA(close, length) `
The lookback shift centers the moving average on the period being measured, removing the trend component while preserving cyclical deviations. An optional EMA or SMA of configurable length can then be applied to the raw DPO.
`Overbought = SMA(DPO, stdLookback) + ob_multiplier × StdDev(DPO, stdLookback)`
`Oversold = SMA(DPO, stdLookback) − os_multiplier × StdDev(DPO, stdLookback)`
Both bands float dynamically with the evolving distribution of DPO values, tightening during low-volatility periods and expanding during high-volatility ones.
Plots 📊
DPO line with 6-layer glow (linewidths 12/8/5/3/2/1, transparencies 88/78/65/50/30/0), colored by active regime
Dynamic overbought and oversold band lines
Rolling mean line
Zero baseline (dashed)
Triangle signals in the panel and on the price chart when DPO crosses back inside a band from an extreme (Extremes mode, signals enabled)
Candle coloring on the price chart by active regime
Background highlight on the price chart when either band is breached (Extremes mode)
Inputs 🎛️
`Mode`: Extremes (band-crossing signals) or Trend (mean-relative direction)
`DPO Length`: period of the internal SMA used to detrend price (default 21)
`StDev Lookback`: rolling window for mean and standard deviation of the DPO (default 250)
`Oversold StDev Multiplier`: band distance below the mean (default 1.8)
`Overbought StDev Multiplier`: band distance above the mean (default 2.0)
`Show Signals`: toggles triangle markers for band re-entry crossings
`Use Moving Average` applies a smoothing MA to the DPO before all calculations
`Moving Average Length` : period of the smoothing MA (default 10)
`Moving Average Type`: EMA or SMA
Colors 🎨
5 Astral Vision presets + custom override. Default: Hermes. Positive color activates at oversold extremes and above-mean trend; negative color activates at overbought extremes and below-mean trend; neutral applies to the mean line.
Purpose 🎯
Standard DPO implementations plot a raw oscillator with no threshold logic and no statistical context, leaving the trader to visually judge whether a given deviation is significant or routine. Fixed overbought/oversold levels carry no meaning as market volatility changes over time.
This indicator makes the extremes statistically rigorous: the bands adapt to the actual distribution of DPO values over the chosen lookback, so a breach always represents a genuinely unusual deviation regardless of the prevailing volatility regime.
The signal markers fire specifically on band re-entries, not on the initial breach, identifying the moment mean reversion has begun rather than flagging the extreme itself.
The six-layer glow rendering makes the oscillator's position relative to its bands immediately readable at a glance without requiring precise level inspection.
Disclaimer ⭕️
It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision. Indicator
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Real Strength Scalper Overview
A momentum-continuation scalping strategy designed for the 5-minute timeframe. It uses a single custom oscillator — the Real Strength histogram — combined with a dual SMA trend filter to capture confirmed directional moves, while a static percentage stop loss and an adaptive, regime-dependent exit logic manage open trades.
Concept and Originality
Most momentum oscillators answer either *which direction* or *how strong*, rarely both in a way that requires real conviction. The Real Strength histogram fuses three independent components into one signed value:
- Price momentum** — Rate of Change of price over N bars (provides the sign)
- Volume confirmation** — current volume divided by its moving average (amplifier)
- Trend strength** — ADX scaled around a 20 reference (amplifier)
These three are multiplied together (with a small floor to prevent the amplifiers from zeroing out the result on quiet bars) and then smoothed with an EMA. The output is an oscillator where the sign tells direction and the magnitude reflects how much *real* force is behind the move. A high histogram reading requires all three components to align — price moving, volume present, ADX confirming.
This composite differs from a standalone ROC, MACD, or volume-weighted oscillator because none of those three on their own require simultaneous confirmation across price, participation, and trend strength.
Entry Logic
A long entry requires every condition below to be true on the same bar:
- Histogram above the positive threshold (default 1.0)
- Histogram rising vs. the previous bar (no entries on a fading peak)
- ADX above the minimum level (default 14)
- DI+ greater than DI− (directional confirmation)
- Volume ratio above minimum (default 1.2× average)
- *Optional:* Fast SMA above Slow SMA (default 30/60, toggleable)
Short entries mirror these conditions on the bearish side.
Exit Logic — Regime-Dependent
The exit behavior changes based on whether the SMA trend filter still confirms the position. This is the central design choice of the strategy:
While SMA still confirms the position:
The trade exits only when the histogram crosses through zero into the opposite zone past a defined flip threshold (default ±0.8). This allows winners to ride through pullbacks and consolidations as long as the larger structure (SMA cross) still favors the trade.
After SMA reverses against the position:
The trade exits on a classic peak-drop rule — if the histogram falls 25% or more from its peak value reached during the trade, the position is closed. This protects open profits when structure breaks down.
A hard static stop loss (default 1%) is always active and overrides both exit modes if reached first. A minimum hold of 3 bars prevents premature exits caused by noise immediately after entry.
Re-Entry Lock
After a stop loss is hit, the strategy refuses to re-enter in the same direction until the histogram returns to (or crosses) zero. This prevents immediately re-entering the same momentum that just stopped the previous trade out — a common cause of consecutive losses on choppy bars.
Settings Guide
- Strength threshold (1.0):** minimum histogram magnitude required for entry. Lower values produce more trades; higher values are more selective.
- Min ADX (14):** filters out low-trending environments.
- Volume Ratio (1.2):** requires above-average participation on the entry bar.
- SMA Fast / Slow (30 / 60):** trend regime filter; can be disabled to compare baseline performance.
- Stop Loss % (1.0):** static distance from entry. Adjust per instrument volatility.
- Peak drop % (25):** how much the histogram must fall from peak to trigger peak-exit.
- Flip exit threshold (0.8):** how far the histogram must travel into the opposite zone to trigger flip-exit.
- Min bars before peak/flip (3):** protects against same-bar noise exits.
Default Properties and Backtesting Realism
- Initial capital: 100,000
- Position size: 3% of equity per trade
- Commission: 0.04%
- Slippage: 3 ticks
- Process orders on close: true
- No pyramiding
These defaults reflect realistic crypto futures conditions. Users trading other instruments or venues should adjust commission and slippage to match their broker.
Intended Use
- Built and validated on the 5-minute timeframe
- Best suited for liquid markets with consistent volume profile
- One position at a time, both long and short
- Re-tune thresholds per instrument; defaults are starting points, not optimal values for every market
Notes
Past performance does not guarantee future results. Backtest outcomes depend strongly on the chosen instrument, time range, and parameter settings. This strategy is published as an educational tool to demonstrate a composite-momentum approach with regime-dependent exits — not as a turnkey trading system. Always test with your own data and risk parameters before any live use. Strategy
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