Volatility Managed Kelly LeverageThe Volatility Managed Kelly Leverage (VMKL) indicator is a tool that dynamically adjusts position sizing based on forecasted market volatility. It helps you to optimize leverage exposure by systematically reducing risk during high volatility periods and increasing exposure when markets are calm.
VMKL adapts in real-time to changing market conditions, potentially generating alpha while smoothing volatility and reducing maximum drawdown.
This indicator implements the Optimal Volatility Plus Mean Strategy (OVPMS) from one of my favorite leverage papers:
" Alpha Generation and Risk Smoothing using Managed Volatility " by Tony Cooper (2010)
These are the key findings from the paper, which this indicator translates to real life:
Volatility is predictable while returns are not
Dynamic leverage based on volatility forecasts can generate significant excess returns
The strategy reduces volatility of volatility (vovo), kurtosis, and maximum drawdown
Tested on 125+ years of market data across multiple global indices
The OVPMS strategy (translated into this indicator) returned 12.6% annual return vs 7.0% for buy-and-hold, with the same volatility as the underlying index. Outstanding.
The indicator calculates optimal leverage using a three-step process
1. Volatility Forecasting
Uses Exponential Weighted Moving Average (EWMA):
σ²(t) = λ·σ²(t-1) + (1-λ)·r²(t-1)
This predicts next-day volatility from recent price movements
2. Return Prediction
Expected Return = a × σ^(b+1)
Where:
a = Power coefficient (baseline return, default: 0.10)
b = Power exponent (return-volatility relationship, default: -1.76 for SPY)
σ = Forecasted volatility
The negative exponent means returns decrease as volatility increases - a well-documented market behaviour.
3. Optimal Leverage Calculation
Full Kelly Leverage = μ / σ²
Actual Leverage = Full Kelly × Kelly Fraction × Caps × Smoothing
The Kelly Criterion provides the theoretically optimal leverage, which is then reduced via:
Kelly Fraction: Safety margin (default 75% = three-quarter Kelly)
Leverage Caps: Hard maximum and minimum limits
Smoothing: SMA to reduce rebalancing frequency
The Core Insight: Volatility varies over time (volatility of volatility), and this variation is costly. By targeting consistent volatility through dynamic leverage:
Reduces volatility drag - Compounding works better with stable volatility
Reduces drawdowns - Automatically deleverages before crashes
Reduces kurtosis - Fewer extreme return events
Generates alpha - Exploits the return-volatility relationship
The indicator calculates optimal leverage in real-time using EWMA volatility forecasting and Kelly Criterion mathematics, automatically detecting market regimes from CASH to VERY AGGRESSIVE and respective leverages. The statistics table shows Full Kelly leverage, Kelly Fraction leverage, forecasted volatility, predicted returns, and current regime.
Settings Guide
Please check the informational "i" in setting to get a lot more info.
You can also use preset configurations:
Conservative (Safe)
Kelly Fraction: 0.50
Max Leverage: 2.0x
Lambda: 0.97
Sensitivity: Enhanced
Moderate (Balanced) ⭐ DEFAULT
Kelly Fraction: 0.75
Max Leverage: 3.0x
Lambda: 0.94
Sensitivity: Enhanced
Aggressive (Maximum)
Kelly Fraction: 1.0
Max Leverage: 5.0x
Lambda: 0.90
Sensitivity: Standard
Paper Replication (Academic)
Kelly Fraction: 1.0
Max Leverage: 3.0x
Lambda: 0.94
Sensitivity: Standard
Adaptive: ON
Smoothing: 1
Remember: LEVERAGE MAGNIFIES BOTH GAINS AND LOSSES
Let me know if you have questions!
By Henrique Centieiro Indicator
Indicator
Indicator
Indicator
Indicator
Gann Time Cycles Pro: Confluence
Think of the stock market like a giant, calm pond.
When the market has a **massive crash** (a bottom) or hits a **crazy all-time high** (a top), it is like dropping a giant boulder into that pond.
That boulder creates ripples. Those ripples travel forward in time. According to W.D. Gann, those ripples hit the shore at very specific mathematical intervals: **90 days, 180 days, 270 days, and 360 days** later. When a ripple hits, the market usually changes direction violently.
### How to Use the Custom Features (User-Defined)
**1. The 5 Anchors (Your "Boulders")**
Instead of just tracking one boulder, the system lets you drop up to 5.
* **How to use it:** Look at a Daily chart. Find the lowest low of last year. Make that **Anchor 1**. Find the highest high of six months ago. Make that **Anchor 2**.
* *Layman Translation:* You are telling the system, "Hey, these two dates were super important. Show me where their future ripples are going to land."
**2. The Custom Cycles (Your "Custom Ripples")**
You already have the standard ripples (90, 180, 270, 360). But what if a specific stock, like Tesla or Reliance, has its own weird, unique rhythm? Or what if you want to use the famous "144" Fibonacci number?
* **How to use it:** Go into the settings and type `144` into Custom Cycle 1, and maybe `45` into Custom Cycle 2.
* *Layman Translation:* You are telling the system, "I don't just want the standard ripples. I want to see a special ripple exactly 144 days after my boulder dropped."
---
### Your Step-by-Step Action Plan (How to trade it tomorrow)
Here is exactly what you do when you open PulseWire:
**Step 1: Turn on the Engine**
Apply the indicator to your chart. Go to the settings.
**Step 2: Set your Anchors (The Past)**
Look back at the chart and find 2 or 3 major turning points (big V-shaped bottoms or upside-down V-shaped tops).
* Check the box for `Use A1` and put in the date of the first bottom.
* Check the box for `Use A2` and put in the date of the top.
**Step 3: Set your Cycles (The Rhythm)**
Leave the standard 90, 180, 270, and 360 as they are. If you like a specific number (like 45 or 144), type it into the Custom slots. If you don't want custom ones, just type `0` to turn them off.
**Step 4: Hunt for the "Time Cluster" (The Future)**
Now, look at the blank, empty space on the right side of your screen (the future). The system has drawn a bunch of vertical lines (Orange for Calendar days, Blue for Trading days).
**THIS IS THE MOST IMPORTANT PART:**
You are looking for a spot where a line from Anchor 1 lands **right next to, or exactly on top of**, a line from Anchor 2.
* *Example:* Let's say Anchor 1's 360-day line lands on October 15th. And Anchor 2's 180-day line lands on October 16th.
* *What it means:* Two massive historical ripples are crashing into each other at the exact same time.
**Step 5: How to Trade It**
When the actual date arrives (October 15th), you do not just blindly buy or sell. You watch the price action.
* If the stock has been going up, up, up into that October 15th date... expect it to suddenly reverse and crash down. (Take profits, or prepare to Short).
* If the stock has been bleeding and crashing down into that October 15th date... expect it to suddenly find a bottom and shoot up. (Get ready to Buy).
**In short:** You use the overlapping lines to circle dates on your calendar. When that date arrives, expect the current trend to suddenly flip directions. Indicator
Indicator
Indicator
Indicator
Strategy
Indicator
Strategy
PrismPrism : Integrated Trend Flow & Structural Risk Engine**
**Prism ** is a high-precision trend-following system designed to filter market noise and provide institutional-grade trade management. By combining **Guppy Multiple Moving Average (GMMA)** logic with **Dynamic Structural Walls** and an **Automated Entry Advice Engine**, it offers a comprehensive solution for traders who prioritize confluence over guesswork.
### **Core Logic: The Triple-Filter Approach**
Prism PRO doesn't just look at price; it analyzes the "fabric" of the market through three distinct layers:
1. **The Ribbon Stack (Sentiment & Flow):** Utilizing 12 EMA layers, the script identifies when short-term sentiment (the fast group) is perfectly aligned with long-term capital flow (the slow group). Signals only fire when the trend is "stacked" and healthy.
2. **Momentum Confirmation:** A built-in RSI filter ensures that signals are only triggered when momentum is on your side ( NYSE:RSI > 50$ for Longs, NYSE:RSI < 50$ for Shorts), preventing "drift" entries in low-volatility environments.
3. **Structural Wall Confluence:** This is the heart of the system. The script identifies the nearest **Auto-Fibonacci level** and compares it with the **EMA 12**. It selects the strongest level to create a "Structural Wall," which serves as the basis for the **Advised Stop Loss**.
### **Key Features**
* **Dynamic Entry Advice Engine:** The dashboard provides real-time feedback. It labels entries as **IDEAL**, **LATE**, or **OVEREXTENDED** based on the price's deviation from the EMA 12 and the live Reward-to-Risk (R/R) ratio.
* **Frozen State Persistence:** Unlike standard indicators that reset when a trend breaks, Prism PRO "freezes" your trade data (Entry, Stop, Target). If the ribbon stack breaks while you are in a trade, the dashboard keeps showing your last valid levels (marked with an `*`) so you can monitor your exit.
* **Ratchet Trailing Stop:** An ATR-based trailing stop that only moves in a favorable direction, protecting your capital as the trade progresses.
* **Fibo-Compression Alerts:** The dashboard monitors the distance between the current price and major Fibonacci levels. If the price is too close to a major level, it triggers a **⚠️ Warning**, alerting you to potential reversal zones or "compression" before a breakout.
### **The Dashboard Breakdown**
* **System Mode:** Instant visual of current trend bias.
* **Risk Metrics:** Live ATR volatility and percentage-based risk/reward calculations.
* **Final Call:** A "Engine Status" indicator showing the strength of the current flow.
* **Entry Advice:** Direct instructions (e.g., "Wait Pullback" or "Monitor Open Position").
### **How to Use**
1. **The Setup:** Look for a **BUY** or **SELL** label.
2. **The Filter:** Check the **Entry Advice**. If it says "OVEREXTENDED," wait for a pullback to the ribbon.
3. **Risk Management:** Use the **Advised Stop** or the **Trailing Stop** provided on the dashboard to manage your exit.
4. **Targeting:** The script plots a 1:2 R/R target by default, which is automatically cross-referenced with the nearest Fibonacci level for higher probability.
---
Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial or investment advice. Trading financial markets involves significant risk of loss. Past performance is not indicative of future results. Always perform your own due diligence and consult with a professional financial advisor before making any investment decisions. The author assumes no responsibility for any financial losses incurred through the use of this script.
Indicator
Liquidity Surge Forecast with Markov Chains [TechnicalZen]Clear direction from Markov Chains confirmed projections.
Publishing this v3 with all the enhancements users desired and more. Thank you for your feedback.
What This Is
A 3D liquidity-and-momentum visualization that tells you where the market is heading right now, how long the current state is likely to hold, and when the next regime change is expected — all backed by a 2nd-order Markov chain that learns from your chart's own history.
Two independent systems — Money Flow (MFI-driven) and Price Current (Hull-VWMA or signed-ADX) — render as layered dotted carpets inside a bounded 3D box. When both systems agree on direction AND the Markov chain confirms, a whale surfaces — 🐳 bullish, 🐋 bearish. Chop gets a shark 🦈. Sideways drift gets a crab 🦀. And when the Markov chain predicts an imminent regime transition, a small hatchling whale appears before confluence forms.
The Current State row tells you, in one line, exactly what to expect next.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Built On
Money Flow Dynamics Forecaster 3D — the original 3D layered-terrain architecture, MFI/RSI momentum carpet, Hull-VWMA price current carpet, slope-extrapolated forecast, rider + whale system.
Same 3D engine. Same dual-system confluence as the foundation. Then: regime classification, Markov statistical learning, current-state intelligence, and a live win-rate scoreboard on top.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Clear Direction — At A Glance
Most indicators show you lines and ask you to interpret. This one tells you plainly, in a single dashboard row:
What regime you're in right now — 🐳 Bull, 🐋 Bear, 🦈 Chop-zone, or 🦀 Sideways
How long it's been held — in bars
Whether the regime is BALANCED or IMBALANCED — based on the Markov chain's next-bar probabilities
When the next regime change is expected — in bars, computed from the stay-probability
Which direction the market leans next — the highest-probability non-current state
Example readouts:
"Current State: 🐳 Bull held 5b · IMBALANCED — stay 68%, change expected in ~3b · next lean: 🦀 Sideways"
"Current State: 🦀 Sideways held 12b · BALANCED — change imminent · next lean: 🐳 Bull"
"Current State: 🐋 Bear held 2b · IMBALANCED — stay 82%, change expected in ~5b · next lean: 🦀 Sideways"
No interpretation required. You read the line, you know where you are, you know what to expect.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
New Features — And Why Each Exists
1. Current State intelligence row
Why: Confluence indicators tell you WHEN a signal fires. They don't tell you "how solid is the current regime," "is a change coming," or "how long do I have before conditions flip." The Current State row answers all three in one glance.
The balanced / imbalanced distinction matters most:
BALANCED — the three next-bar probabilities are close to 1/3 each. No clear direction. A regime change is imminent (could go anywhere). Trade lighter, wait for resolution.
IMBALANCED — one direction dominates. Regime has a preferred path. The stay-probability tells you how long it's likely to persist; the next-lean tells you which direction it will tilt when it does flip.
The expected-bars-to-change is a geometric distribution mean: 1 / (1 − P(stay)). If a regime has 80% stay probability, it's expected to persist ~5 more bars. If 33%, it's expected to flip in ~1.5 bars.
2. 2nd-order Markov chain regime predictor
Why: the original whale logic was reactive — it fires after confluence forms. Markov is predictive — it learns your instrument's transition habits and uses them to gate and anticipate whale signals.
Pure statistics, no black box:
2nd-order — predicts the next regime from the pair of previous regimes, not just one. Captures patterns like "Chop → Sideways → 68% Bull next" that a 1st-order chain would miss.
Laplace smoothing (α=1) — every transition count gets a +1 pseudocount before normalization. Prevents "never observed → 0% forever" failure. Standard in real statistics.
Exponential recency decay — newer transitions count more than old ones (default 0.995/bar). Markets drift; stale history shouldn't dominate current prediction.
Duration conditioning — separate transition matrices for "current state held <5 bars" vs "held ≥5 bars." Regimes behave differently after they've been running. Real statistical sub-populations.
Confidence gating — if the current context has fewer than 10 observations, predictions are flagged low-n . No fabricated probabilities.
Maximum useful substance without gimmick. 3rd-order Markov would need thousands of regime transitions per cell to converge — doesn't happen on typical charts. 2nd-order is the ceiling before diminishing returns.
3. Dual-layer regime classification — Chop-zone 🦈 vs Sideways 🦀
Why: prior versions treated "not trending" as a single category. But there are two fundamentally different kinds of non-trending market:
🦈 Chop-zone — violent range-bound circling. Detected via classic Choppiness Index . Often precedes a sharp breakout.
🦀 Sideways — slow drift, flat angles across close/high/low at both short and long periods. Detected via angle consensus . Often indicates accumulation or distribution.
Showing them separately lets you read which kind of non-trending you're in. Different implications, different decisions.
4. Hatchling whales — pre-signal pre-whales
Why: the Markov chain lets us anticipate confluence before it forms. When the current state is Sideways AND Markov predicts Bull (or Bear) with confidence above the hatchling threshold, a small whale appears at the mid-forecast position — a heads-up that confluence is probabilistically coming.
Full whale (size.huge at forecast edge) = confluence is here now.
Hatchling whale (size.small at forecast mid) = confluence is probably coming soon.
Better entries on regime changes.
5. Markov-gated whale confirmation
Why: sometimes projected-confluence fires, but the instrument's historical pattern says "from this context, the opposite is more likely." That's exactly the setup a trader wants the indicator to filter out .
The gate is permissive — Markov blocks a whale only if it's confident AND its argmax points the opposite direction. Uncertainty or agreement = pass through. Reduces false confluence without over-filtering.
6. Regime-aware 4-column win-rate dashboard
Why: knowing how much time the instrument actually spends in each regime is as actionable as the signals themselves.
Four parallel columns:
🐳 Bull — confluence signals and win rate
🐋 Bear — same, opposite direction
🦈 Chop-zone — CI chop events and % of bars
🦀 Sideways — angle-sideways events and % of bars
If your instrument spends 80% of bars in Chop/Sideways, confluence will be rare — adjust timeframe or instrument. If Markov shows low-n on most bars, the matrix isn't populated yet — wait for more history before trusting predictions.
7. Session-aware for futures
Why: NQ, ES, CL and other overnight-session futures stamp their daily bar at session start , which is the previous calendar evening. Naive `dayofweek(time)` reads NQ's "Friday session" as Thursday. The indicator uses `time_close("D")` — the close of the daily bar, always on the trading date — so regime classification is correct for both cash equities (TSLA, SPY) and overnight futures (NQ, ES). Same indicator, any asset class.
8. Honest evaluation — next-signal MFE or directional close
Why: "close-at-N-bars" is dishonest. Price can move 2×ATR favorably then retrace — close-at-N logs that as a loss. MFE logs it as what it actually was.
Each signal is held pending until the next signal fires. It's a win if either:
The close at next-signal bar was directionally favorable vs entry, OR
The Maximum Favorable Excursion between the two signals reached the ATR-scaled threshold (default 0.5×ATR at entry bar)
Either qualifies. Transparent. Computed live. Disclaimer embedded in the dashboard footer.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
How to Read the Dashboard
┌────────────────────────────────────────────────┐
│ Liquidity Surge + Markov · Win Rate │
├────────┬────────┬─────────────┬───────────────┤
│🐳 Bull │🐋 Bear │🦈 Chop-zone │🦀 Sideways │
│42 sigs │38 sigs │7 events │12 events │
│31 wins │24 wins │120 bars │45 bars │
│73.8% │63.2% │23% │8.6% │
├────────────────────────────────────────────────┤
│Markov Forecast Next: 🐳 52% · 🦀 31% · 🐋 17% │
├────────────────────────────────────────────────┤
│Current State: 🐳 Bull held 5b · IMBALANCED │
│ stay 68%, change expected in ~3b · next: 🦀 │
├────────────────────────────────────────────────┤
│⚠ Not financial advice · Learned on chart hist │
└────────────────────────────────────────────────┘
Reading order:
Column data — how Bull/Bear signals have performed, how much time is spent in each regime
Markov Forecast Next — next-bar regime probabilities (with sample-size confidence)
Current State — the single-line answer to "where am I and what's next"
Footer — disclaimer + config
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
How to Use
Load with defaults.
Wait for ~100-200 bars of history. The Markov matrix needs observations to learn.
Read Current State first. It tells you what to expect.
If BALANCED → expect a regime change, trade light.
If IMBALANCED + change in ~N bars → plan around that window.
Watch for 🐳 / 🐋 full whales at the forecast edge — confluence + Markov confirmed.
Watch for small hatchling whales at forecast mid-point — Markov's early prediction of confluence coming.
Respect 🦈 (chop-zone) and 🦀 (sideways). Don't fight the regime.
Tune Hatchling Threshold and Win Threshold (×ATR) to your instrument and style.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Best Paired With Smart Candle Structures
This indicator answers whether and when to trust the flow. Smart Candle Structures answers where to act. Together: right place, right moment, measurable conviction, regime-aware.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Key Settings
Time Span — past bars rendered + forecast horizon (default 15)
Momentum Source — MFI (default) or RSI
Oscillator Type — Hull-VWMA (default) or signed-ADX
Slope Lookback — bars for slope that fires whales (default 4)
Evaluation Window — bars after a signal to measure MFE (default 5)
Win Threshold (× ATR) — minimum favorable excursion as a multiple of ATR (default 0.5)
Gate Whale by Choppiness — master toggle for 🦈 / 🦀 filter
CI Length / CI Threshold — classic Choppiness Index tuning
Angle Short / Long Period — angle-based sideways lookbacks
Angle Trend / Sideways Threshold — angle degrees defining trending vs sideways
Use Markov Predictor — master toggle for the 2nd-order chain
Count Decay per Bar — recency weighting for Markov counts (default 0.995)
Hatchling Threshold — minimum Markov probability to fire pre-whale (default 55%)
Dashboard Text Size — Tiny / Small / Normal / Large / Huge
Camera — yaw / pitch / scales for the 3D view
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Disclaimer
This is a visualization and analytical tool, not financial advice or a signal service. The Markov chain is trained on your chart's history — it describes what has happened on this instrument at this timeframe, not what will happen. Regime transition probabilities are learned estimates; past frequencies do not guarantee future outcomes. Markets are reflexive and can transition in ways the chain has never observed. Hatchlings, whales, sharks and crabs are visualizations of mathematical predictions — they do not constitute buy or sell recommendations. Trade with your own risk management. Every trade can lose.
The indicator echoes this disclaimer in its dashboard footer so you see it every time you read the chart. It's always there because it's always true.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Clear direction from learned regimes.
— TechnicalZen
Indicator
ATR Daily Time Frame Display BoxATR Display Box
A clean, minimal ATR display that sits in the corner of your chart without getting in the way.
The indicator pulls ATR from the daily timeframe regardless of what chart you're on — so whether you're on a 1 minute, 5 minute, or any intraday timeframe, you're always seeing the true daily ATR value. No more manually switching timeframes or calculating inflated period numbers to approximate a daily ATR on lower timeframes.
Features:
Always references the daily timeframe for accurate ATR readings
Adjustable ATR period (7, 9, 14 or any value you choose)
Compact table display — stays out of the way of your chart
Fully customisable: position, background colour, text colour, border colour
Adjustable decimal places to suit any instrument
Best used for:
Gauging daily range on futures (ES, NQ, CL, GC etc.)
Setting realistic profit targets and stop distances based on true daily range
Quick reference during intraday trading without cluttering your chart
Works on any instrument and any timeframe. Indicator
Indicator
Indicator
Indicator
Indicator
Indicator
Ram-ban Support & Resistance System [% Adaptive for Stocks]📌 Overview
The Ram-ban Support & Resistance System is an advanced, fully dynamic mapping tool engineered to identify crucial market turning points without cluttering your chart. By referencing higher timeframe (HTF) pivot structures and utilizing a percentage-based mapping logic, this indicator seamlessly scales to any asset class—from Crypto and Forex to Equities and Indices—without the need for manual point adjustments.
🚀 Key Features
Adaptive % Model: Forget rigid point values. Settings for spacing, signals, and stop-loss are percentage-based, ensuring the indicator works flawlessly on BTCUSD just as well as it does on AAPL or NIFTY.
Dynamic Consolidation Heatmap: Not all levels are created equal. As price consolidates around a specific support or resistance zone, the line dynamically increases in thickness. A thicker line represents a heavily tested zone with stronger historical relevance.
Intelligent "Option Mode" (Fading): Keep your focus where the action is. Levels that are far from the current market price will automatically fade out, keeping your chart clean and eliminating noise.
Wick-Based Signal Engine: Captures sniper-like entries by looking for wick rejections at key levels. When price reaches a specified tolerance zone (%) of a major level, a Buy or Sell signal is generated.
Built-in Risk Management: Automatically calculates a dynamic Stop Loss based on your preset percentage. Visual labels tell you exactly where your invalidation point is upon entry.
Session Filtering: Confine your trading signals strictly to active market hours, filtering out erratic overnight or pre-market moves.
🛠️ How to Use
Trend Context: Use the HTF Support/Resistance rails as major boundaries. Green rails act as support (demand), red rails act as resistance (supply).
Observe the Line Thickness: A very thin line is a fresh level. A thick, bold line indicates high historical contention. Treat thick lines as high-probability reversal zones.
Trading Signals: Look for the "BUY" labels (with attached SL values) as price taps support rails. The "BOOK PROFIT" label triggers when a loaded position touches the upper resistance boundary.
Alerts: Create alerts directly from the indicator to be notified of "BUY", "BOOK PROFIT", or "SL HIT" events instantly.
⚙️ Core Settings Overview
HTF for Pivots: The default is 60 (1 Hour) to capture macro swings on lower timeframe charts (like 5m or 15m).
Min Distance Between Levels (%): Prevents the indicator from drawing too many lines close together. Adjust based on asset volatility.
Consolidation Zone Tolerance (%): How close a candle needs to close near a line to "thicken" it.
Stop Loss (%): Defines the dynamic Stop Loss label printed alongside entry signals.
⚠️ Disclaimer
This script is provided for educational and informational purposes only. It does not constitute financial, investment, or trading advice. Past performance is not indicative of future results. Trading in financial markets involves a high degree of risk. Always conduct your own research (DYOR), backtest thoroughly, and use proper risk management before putting real capital on the line. The author assumes no responsibility for any trading losses incurred.
SupportAndResistance, PriceAction, PivotPoints, DynamicLevels, DayTrading, Scalping, RiskManagement, StopLoss, Breakout, Reversal, MultiTimeframe, MTF Indicator
NQ/MNQ CT Scalper [BACKTEST]NQ/MNQ counter-trend scalper. 1-min chart, fades overextended moves across all sessions.
6 entry paths — FADE (overextension), DIV (delta divergence), TRAP (liquidity sweep fade), AGG (aggressive flow fade), VRZ (volume zone retest), and ABSORB (institutional absorption). Every entry requires the market to be trending AND overextended — no fading chop.
TP targets the mean — EMA21, VWAP, POC, pivot levels. Dynamically picks the closest or farthest target based on confidence. SL sits beyond the structural extreme with a 3 ATR hard cap. Session-tuned TP scaling takes quick profits during MOC/thin sessions and lets winners ride during afternoon reversions.
Backtest — MNQ, 1-min, 1 yr:
393 trades | 40.5% win rate | avg W/L ratio 2.08
PF 1.41 | Sharpe 0.40 | Sortino 1.66
MaxDD -$1,296 | Return/DD 3.14
Pyramiding 20 | $0.62/contract | 2 tick slippage
process_orders_on_close = false
Session-aware confidence boost filters out low-edge entries. Dynamic R:R floor rejects trades with bad TP/SL geometry. Hurst exponent blocks fades during persistent trends. HTF veto prevents catching knives when higher timeframes are strongly directional.
Same architecture as the trend-following companion — stateless, no cooldowns, 8 session windows, AER regime, ADF stationarity. Designed to run alongside the Super Scalper for full-spectrum NQ/MNQ coverage. Strategy
NQ/MNQ Super Scalper [BACKTEST]NQ/MNQ trend-following scalper. 1-min chart, runs all sessions 24/5.
6 entry paths — BOS, RE, OB, TRAP, and a high-conviction main signal — all scored through an 8-factor confidence engine (structure, momentum, flow, volume, regime, Hurst, ADF, HTF alignment). Every parameter is dynamic and session-aware. Nothing hardcoded.
TP scales per path, per session, per regime. SL is structural with a 3 ATR hard cap. Smart exits monitor 9 patterns and pull the trade if the thesis breaks before TP.
No martingale. No grid. No fixed lots. Most bars produce zero signals — entries require real confluence.
Backtest — MNQ, 1-min, 1 yr:
2,934 trades | 63.7% win rate
PF 1.23 | Sharpe 0.51 | Sortino 2.04
Pyramiding 20 | $0.62/contract | 2 tick slippage
process_orders_on_close = false
no barsSince counters. 8 session windows with independent tuning. AER regime detection, Hurst persistence filter, ADF stationarity, HTF veto. Per-path TP multipliers backed by signal×session performance data.
Built for NQ/MNQ only. Designed to run alongside a counter-trend companion for full coverage. Strategy
