MM Day Trader LevelsAs an intraday trader, there are certain key levels that I care about for short-term price action on every single chart. When I first began day trading, each morning I would painstakingly mark those key levels off on the charts I planned to trade each day. Depending on the number of charts I was watching, this would take up quite a bit of my time that I felt would have been much better spent doing other things. It also meant that those levels would often be left behind, and on later days I might be trading a symbol and get confused when a line appeared and I'd be paying attention to it only to later discover that it wasn't from prior day, but from some other day in the past when I had marked it off.
I looked all over TradingView to find indicators that did this automatically for me, and I found a lot of them. One by one I tried them, and inevitably I would always find that something was wrong with them. Often they didn't have all of the levels I wanted (so I would have to combine multiple indicators), but more often I found that the levels would be incorrect, or they would be buggy and not appear consistently, or they would not appear at the right time, or they would not work on futures! The list of problems went on and on. And the biggest issue I found was that nobody knew how to get session volume profile in an indicator.
So, over the course of a few years I figured out how to solve all of those problems and now I'm thrilled to present this free indicator for everyone like me who trades intraday and wants a clean consistent way to see the prior day levels that they care about automatically on every single chart (even futures). The levels the indicator provides are:
Yesterday High & Low
Value Area High & Low & Point of Control
Today's Open
Yesterday's Close (aka "Settlement" on futures)
Premarket High & Low (non-futures only)
Overnight High & Low (futures only)
These levels are extremely important, and I expect price to be reactive to them, so each level has a shaded background behind it so that the levels stand out against other lines you may have on your chart. I try to keep configuration as simple as possible, but there are configuration options that allow you to:
Hide any of the levels
Change the color for the levels
Shade the value area (or not)
Change the label text, size, type (basic label or plain text) and location (how far to the right of last candle to place the label
Adjust session volume profile value area volume & number of rows
The biggest advantage to this indicator over others on TradingView is how it handles session volume profile. When it comes to futures, TradingView does differentiate between regular trading hours and "electronic" trading hours on the charts, but their timeframes for those sessions are unusual, and they do not provide any programmatic way to differentiate between them. So, I created a whole new library for dealing with futures sessions that is fully integrated into both my Session Volume Profile library and this indicator, allowing me to bring you the best and only custom indicator available on TradingView that provides you with true regular session volume profile information across every type of symbol, including futures.
I'm incredibly proud of everything I've been able to provide with this indicator, and even more thrilled to say that I'm proud of how the indicator has been implemented. Once again releasing this indicator and all associated code for free and open source. I encourage you to take a look at the source code to see how it all works, take advantage of the free underlying libraries I created to make all of this possible: Session Library and Session Volume Profile Library.
Поиск скриптов по запросу "Futures"
Adaptivity: Measures of Dominant Cycles and Price Trend [Loxx]Adaptivity: Measures of Dominant Cycles and Price Trend is an indicator that outputs adaptive lengths using various methods for dominant cycle and price trend timeframe adaptivity. While the information output from this indicator might be useful for the average trader in one off circumstances, this indicator is really meant for those need a quick comparison of dynamic length outputs who wish to fine turn algorithms and/or create adaptive indicators.
This indicator compares adaptive output lengths of all publicly known adaptive measures. Additional adaptive measures will be added as they are discovered and made public.
The first released of this indicator includes 6 measures. An additional three measures will be added with updates. Please check back regularly for new measures.
Ehers:
Autocorrelation Periodogram
Band-pass
Instantaneous Cycle
Hilbert Transformer
Dual Differentiator
Phase Accumulation (future release)
Homodyne (future release)
Jurik:
Composite Fractal Behavior (CFB)
Adam White:
Veritical Horizontal Filter (VHF) (future release)
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman's adaptive moving average (KAMA) and Tushar Chande's variable index dynamic average (VIDYA) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is this Hilbert Transformer?
An analytic signal allows for time-variable parameters and is a generalization of the phasor concept, which is restricted to time-invariant amplitude, phase, and frequency. The analytic representation of a real-valued function or signal facilitates many mathematical manipulations of the signal. For example, computing the phase of a signal or the power in the wave is much simpler using analytic signals.
The Hilbert transformer is the technique to create an analytic signal from a real one. The conventional Hilbert transformer is theoretically an infinite-length FIR filter. Even when the filter length is truncated to a useful but finite length, the induced lag is far too large to make the transformer useful for trading.
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, pages 186-187:
"I want to emphasize that the only reason for including this section is for completeness. Unless you are interested in research, I suggest you skip this section entirely. To further emphasize my point, do not use the code for trading. A vastly superior approach to compute the dominant cycle in the price data is the autocorrelation periodogram. The code is included because the reader may be able to capitalize on the algorithms in a way that I do not see. All the algorithms encapsulated in the code operate reasonably well on theoretical waveforms that have no noise component. My conjecture at this time is that the sample-to-sample noise simply swamps the computation of the rate change of phase, and therefore the resulting calculations to find the dominant cycle are basically worthless.The imaginary component of the Hilbert transformer cannot be smoothed as was done in the Hilbert transformer indicator because the smoothing destroys the orthogonality of the imaginary component."
What is the Dual Differentiator, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 187:
"The first algorithm to compute the dominant cycle is called the dual differentiator. In this case, the phase angle is computed from the analytic signal as the arctangent of the ratio of the imaginary component to the real component. Further, the angular frequency is defined as the rate change of phase. We can use these facts to derive the cycle period."
What is the Phase Accumulation, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 189:
"The next algorithm to compute the dominant cycle is the phase accumulation method. The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle's worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio."
What is the Homodyne, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 192:
"The third algorithm for computing the dominant cycle is the homodyne approach. Homodyne means the signal is multiplied by itself. More precisely, we want to multiply the signal of the current bar with the complex value of the signal one bar ago. The complex conjugate is, by definition, a complex number whose sign of the imaginary component has been reversed."
What is the Instantaneous Cycle?
The Instantaneous Cycle Period Measurement was authored by John Ehlers; it is built upon his Hilbert Transform Indicator.
From his Ehlers' book Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading by John F. Ehlers, 2004, page 107:
"It is obvious that cycles exist in the market. They can be found on any chart by the most casual observer. What is not so clear is how to identify those cycles in real time and how to take advantage of their existence. When Welles Wilder first introduced the relative strength index (rsi), I was curious as to why he selected 14 bars as the basis of his calculations. I reasoned that if i knew the correct market conditions, then i could make indicators such as the rsi adaptive to those conditions. Cycles were the answer. I knew cycles could be measured. Once i had the cyclic measurement, a host of automatically adaptive indicators could follow.
Measurement of market cycles is not easy. The signal-to-noise ratio is often very low, making measurement difficult even using a good measurement technique. Additionally, the measurements theoretically involve simultaneously solving a triple infinity of parameter values. The parameters required for the general solutions were frequency, amplitude, and phase. Some standard engineering tools, like fast fourier transforms (ffs), are simply not appropriate for measuring market cycles because ffts cannot simultaneously meet the stationarity constraints and produce results with reasonable resolution. Therefore i introduced maximum entropy spectral analysis (mesa) for the measurement of market cycles. This approach, originally developed to interpret seismographic information for oil exploration, produces high-resolution outputs with an exceptionally short amount of information. A short data length improves the probability of having nearly stationary data. Stationary data means that frequency and amplitude are constant over the length of the data. I noticed over the years that the cycles were ephemeral. Their periods would be continuously increasing and decreasing. Their amplitudes also were changing, giving variable signal-to-noise ratio conditions. Although all this is going on with the cyclic components, the enduring characteristic is that generally only one tradable cycle at a time is present for the data set being used. I prefer the term dominant cycle to denote that one component. The assumption that there is only one cycle in the data collapses the difficulty of the measurement process dramatically."
What is the Band-pass Cycle?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 47:
"Perhaps the least appreciated and most underutilized filter in technical analysis is the band-pass filter. The band-pass filter simultaneously diminishes the amplitude at low frequencies, qualifying it as a detrender, and diminishes the amplitude at high frequencies, qualifying it as a data smoother. It passes only those frequency components from input to output in which the trader is interested. The filtering produced by a band-pass filter is superior because the rejection in the stop bands is related to its bandwidth. The degree of rejection of undesired frequency components is called selectivity. The band-stop filter is the dual of the band-pass filter. It rejects a band of frequency components as a notch at the output and passes all other frequency components virtually unattenuated. Since the bandwidth of the deep rejection in the notch is relatively narrow and since the spectrum of market cycles is relatively broad due to systemic noise, the band-stop filter has little application in trading."
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 59:
"The band-pass filter can be used as a relatively simple measurement of the dominant cycle. A cycle is complete when the waveform crosses zero two times from the last zero crossing. Therefore, each successive zero crossing of the indicator marks a half cycle period. We can establish the dominant cycle period as twice the spacing between successive zero crossings."
What is Composite Fractal Behavior (CFB)?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Commitment of Traders: Total█ OVERVIEW
This indicator displays the Commitment of Traders (COT) totals data for futures markets.
█ CONCEPTS
Commitment of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) , a US federal agency that oversees the trading of derivative markets such as futures in the US. It is weekly data that provides traders with information about open interest for an asset. The CFTC oversees derivative markets traded on different exchanges, so COT data is available for assets that can be traded on CBOT, CME, NYMEX, COMEX, and ICEUS.
A detailed description of the COT report can be found on the CFTC's website .
COT data is separated into three notable reports: Legacy, Disaggregated, and Financial. This indicator presents specific data from the COT Legacy report. The Total data details the positions held by various traders: Commercial Hedgers (traders registered with CFTC that use futures contracts in that particular commodity for hedging), Large Traders (traders registered with CFTC that do not hedge that particular commodity) and Small Traders (not registered with CFTC).
Our other COT indicators are:
• Commitment of Traders: Legacy Metrics
• Commitment of Traders: Disaggregated Metrics
• Commitment of Traders: Financial Metrics
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
By default, the indicator uses the chart's symbol to derive the COT data it displays. You can also specify a CFTC code in the "CFTC code" field of the script's inputs to display COT data from a symbol different than the chart's.
The rest of this section documents the script's input fields.
COT Selection Mode
This field's value determines how the script determines which COT data to return from the chart's symbol:
- "Root" uses the root of a futures symbol ("ES" for "ESH2020").
- "Base currency" uses the base currency in a forex pair ("EUR" for "EURUSD").
- "Currency" uses the quote currency, i.e., the currency the symbol is traded in ("JPY" for "TSE:9984" or "USDJPY").
- "Auto" tries all modes, in turn.
If no COT data can be found, a runtime error is generated.
Note that if the "CTFC Code" input field contains a code, it will override this input.
Futures/Options
Specifies the type of Commitment of Traders data to display: data concerning only Futures, only Options, or both.
Display
Determines the direction of the metrics requested from the CTFC report.
CTFC Code
Instead of letting the script generate the CFTC COT code from the chart and the "COT Selection Mode" input when this field is empty, you can specify an unrelated CFTC COT code here, e.g., 001602 for wheat futures.
Look first. Then leap.
Dskyz (DAFE) Aurora Divergence – Quant Master Dskyz (DAFE) Aurora Divergence – Quant Master
Introducing the Dskyz (DAFE) Aurora Divergence – Quant Master , a strategy that’s your secret weapon for mastering futures markets like MNQ, NQ, MES, and ES. Born from the legendary Aurora Divergence indicator, this fully automated system transforms raw divergence signals into a quant-grade trading machine, blending precision, risk management, and cyberpunk DAFE visuals that make your charts glow like a neon skyline. Crafted with care and driven by community passion, this strategy stands out in a sea of generic scripts, offering traders a unique edge to outsmart institutional traps and navigate volatile markets.
The Aurora Divergence indicator was a cult favorite for spotting price-OBV divergences with its aqua and fuchsia orbs, but traders craved a system to act on those signals with discipline and automation. This strategy delivers, layering advanced filters (z-score, ATR, multi-timeframe, session), dynamic risk controls (kill switches, adaptive stops/TPs), and a real-time dashboard to turn insights into profits. Whether you’re a newbie dipping into futures or a pro hunting reversals, this strat’s got your back with a beginner guide, alerts, and visuals that make trading feel like a sci-fi mission. Let’s dive into every detail and see why this original DAFE creation is a must-have.
Why Traders Need This Strategy
Futures markets are a battlefield—fast-paced, volatile, and riddled with institutional games that can wipe out undisciplined traders. From the April 28, 2025 NQ 1k-point drop to sneaky ES slippage, the stakes are high. Meanwhile, platforms are flooded with unoriginal, low-effort scripts that promise the moon but deliver noise. The Aurora Divergence – Quant Master rises above, offering:
Unmatched Originality: A bespoke system built from the ground up, with custom divergence logic, DAFE visuals, and quant filters that set it apart from copycat clutter.
Automation with Precision: Executes trades on divergence signals, eliminating emotional slip-ups and ensuring consistency, even in chaotic sessions.
Quant-Grade Filters: Z-score, ATR, multi-timeframe, and session checks filter out noise, targeting high-probability reversals.
Robust Risk Management: Daily loss and rolling drawdown kill switches, plus ATR-based stops/TPs, protect your capital like a fortress.
Stunning DAFE Visuals: Aqua/fuchsia orbs, aurora bands, and a glowing dashboard make signals intuitive and charts a work of art.
Community-Driven: Evolved from trader feedback, this strat’s a labor of love, not a recycled knockoff.
Traders need this because it’s a complete, original system that blends accessibility, sophistication, and style. It’s your edge to trade smarter, not harder, in a market full of traps and imitators.
1. Divergence Detection (Core Signal Logic)
The strategy’s core is its ability to detect bullish and bearish divergences between price and On-Balance Volume (OBV), pinpointing reversals with surgical accuracy.
How It Works:
Price Slope: Uses linear regression over a lookback (default: 9 bars) to measure price momentum (priceSlope).
OBV Slope: OBV tracks volume flow (+volume if price rises, -volume if falls), with its slope calculated similarly (obvSlope).
Bullish Divergence: Price slope negative (falling), OBV slope positive (rising), and price above 50-bar SMA (trend_ma).
Bearish Divergence: Price slope positive (rising), OBV slope negative (falling), and price below 50-bar SMA.
Smoothing: Requires two consecutive divergence bars (bullDiv2, bearDiv2) to confirm signals, reducing false positives.
Strength: Divergence intensity (divStrength = |priceSlope * obvSlope| * sensitivity) is normalized (0–1, divStrengthNorm) for visuals.
Why It’s Brilliant:
- Divergences catch hidden momentum shifts, often exploited by institutions, giving you an edge on reversals.
- The 50-bar SMA filter aligns signals with the broader trend, avoiding choppy markets.
- Adjustable lookback (min: 3) and sensitivity (default: 1.0) let you tune for different instruments or timeframes.
2. Filters for Precision
Four advanced filters ensure signals are high-probability and market-aligned, cutting through the noise of volatile futures.
Z-Score Filter:
Logic: Calculates z-score ((close - SMA) / stdev) over a lookback (default: 50 bars). Blocks entries if |z-score| > threshold (default: 1.5) unless disabled (useZFilter = false).
Impact: Avoids trades during extreme price moves (e.g., blow-off tops), keeping you in statistically safe zones.
ATR Percentile Volatility Filter:
Logic: Tracks 14-bar ATR in a 100-bar window (default). Requires current ATR > 80th percentile (percATR) to trade (tradeOk).
Impact: Ensures sufficient volatility for meaningful moves, filtering out low-volume chop.
Multi-Timeframe (HTF) Trend Filter:
Logic: Uses a 50-bar SMA on a higher timeframe (default: 60min). Longs require price > HTF MA (bullTrendOK), shorts < HTF MA (bearTrendOK).
Impact: Aligns trades with the bigger trend, reducing counter-trend losses.
US Session Filter:
Logic: Restricts trading to 9:30am–4:00pm ET (default: enabled, useSession = true) using America/New_York timezone.
Impact: Focuses on high-liquidity hours, avoiding overnight spreads and erratic moves.
Evolution:
- These filters create a robust signal pipeline, ensuring trades are timed for optimal conditions.
- Customizable inputs (e.g., zThreshold, atrPercentile) let traders adapt to their style without compromising quality.
3. Risk Management
The strategy’s risk controls are a masterclass in balancing aggression and safety, protecting capital in volatile markets.
Daily Loss Kill Switch:
Logic: Tracks daily loss (dayStartEquity - strategy.equity). Halts trading if loss ≥ $300 (default) and enabled (killSwitch = true, killSwitchActive).
Impact: Caps daily downside, crucial during events like April 27, 2025 ES slippage.
Rolling Drawdown Kill Switch:
Logic: Monitors drawdown (rollingPeak - strategy.equity) over 100 bars (default). Stops trading if > $1000 (rollingKill).
Impact: Prevents prolonged losing streaks, preserving capital for better setups.
Dynamic Stop-Loss and Take-Profit:
Logic: Stops = entry ± ATR * multiplier (default: 1.0x, stopDist). TPs = entry ± ATR * 1.5x (profitDist). Longs: stop below, TP above; shorts: vice versa.
Impact: Adapts to volatility, keeping stops tight but realistic, with TPs targeting 1.5:1 reward/risk.
Max Bars in Trade:
Logic: Closes trades after 8 bars (default) if not already exited.
Impact: Frees capital from stagnant trades, maintaining efficiency.
Kill Switch Buffer Dashboard:
Logic: Shows smallest buffer ($300 - daily loss or $1000 - rolling DD). Displays 0 (red) if kill switch active, else buffer (green).
Impact: Real-time risk visibility, letting traders adjust dynamically.
Why It’s Brilliant:
- Kill switches and ATR-based exits create a safety net, rare in generic scripts.
- Customizable risk inputs (maxDailyLoss, dynamicStopMult) suit different account sizes.
- Buffer metric empowers disciplined trading, a DAFE signature.
4. Trade Entry and Exit Logic
The entry/exit rules are precise, filtered, and adaptive, ensuring trades are deliberate and profitable.
Entry Conditions:
Long Entry: bullDiv2, cooldown passed (canSignal), ATR filter passed (tradeOk), in US session (inSession), no kill switches (not killSwitchActive, not rollingKill), z-score OK (zOk), HTF trend bullish (bullTrendOK), no existing long (lastDirection != 1, position_size <= 0). Closes shorts first.
Short Entry: Same, but for bearDiv2, bearTrendOK, no long (lastDirection != -1, position_size >= 0). Closes longs first.
Adaptive Cooldown: Default 2 bars (cooldownBars). Doubles (up to 10) after a losing trade, resets after wins (dynamicCooldown).
Exit Conditions:
Stop-Loss/Take-Profit: Set per trade (ATR-based). Exits on stop/TP hits.
Other Exits: Closes if maxBarsInTrade reached, ATR filter fails, or kill switch activates.
Position Management: Ensures no conflicting positions, closing opposites before new entries.
Built To Be Reliable and Consistent:
- Multi-filtered entries minimize false signals, a stark contrast to basic scripts.
- Adaptive cooldown prevents overtrading, especially after losses.
- Clean position handling ensures smooth execution, even in fast markets.
5. DAFE Visuals
The visuals are a DAFE hallmark, blending function with clean flair to make signals intuitive and charts stunning.
Aurora Bands:
Display: Bands around price during divergences (bullish: below low, bearish: above high), sized by ATR * bandwidth (default: 0.5).
Colors: Aqua (bullish), fuchsia (bearish), with transparency tied to divStrengthNorm.
Purpose: Highlights divergence zones with a glowing, futuristic vibe.
Divergence Orbs:
Display: Large/small circles (aqua below for bullish, fuchsia above for bearish) when bullDiv2/bearDiv2 and canSignal. Labels show strength (0–1).
Purpose: Pinpoints entries with eye-catching clarity.
Gradient Background:
Display: Green (bullish), red (bearish), or gray (neutral), 90–95% transparent.
Purpose: Sets the market mood without clutter.
Strategy Plots:
- Stop/TP Lines: Red (stops), green (TPs) for active trades.
- HTF MA: Yellow line for trend context.
- Z-Score: Blue step-line (if enabled).
- Kill Switch Warning: Red background flash when active.
What Makes This Next-Level?:
- Visuals make complex signals (divergences, filters) instantly clear, even for beginners.
- DAFE’s unique aesthetic (orbs, bands) sets it apart from generic scripts, reinforcing originality.
- Functional plots (stops, TPs) enhance trade management.
6. Metrics Dashboard
The top-right dashboard (2x8 table) is your command center, delivering real-time insights.
Metrics:
Daily Loss ($): Current loss vs. day’s start, red if > $300.
Rolling DD ($): Drawdown vs. 100-bar peak, red if > $1000.
ATR Threshold: Current percATR, green if ATR exceeds, red if not.
Z-Score: Current value, green if within threshold, red if not.
Signal: “Bullish Div” (aqua), “Bearish Div” (fuchsia), or “None” (gray).
Action: “Consider Buying”/“Consider Selling” (signal color) or “Wait” (gray).
Kill Switch Buffer ($): Smallest buffer to kill switch, green if > 0, red if 0.
Why This Is Important?:
- Consolidates critical data, making decisions effortless.
- Color-coded metrics guide beginners (e.g., green action = go).
- Buffer metric adds transparency, rare in off-the-shelf scripts.
7. Beginner Guide
Beginner Guide: Middle-right table (shown once on chart load), explains aqua orbs (bullish, buy) and fuchsia orbs (bearish, sell).
Key Features:
Futures-Optimized: Tailored for MNQ, NQ, MES, ES with point-value adjustments.
Highly Customizable: Inputs for lookback, sensitivity, filters, and risk settings.
Real-Time Insights: Dashboard and visuals update every bar.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
User-Friendly: Guide, visuals, and dashboard make it accessible yet powerful.
Original Design: DAFE’s unique logic and visuals stand out from generic scripts.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Configure Inputs: Adjust instrument, filters, or risk (defaults optimized for MNQ).
Monitor Dashboard: Watch signals, actions, and risk metrics (top-right).
Backtest: Run in strategy tester to evaluate performance.
Live Trade: Connect to a broker (e.g., Tradovate) for automation. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Use bar replay (e.g., April 28, 2025 NQ drop) to test volatility handling.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Backtest results may not reflect live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Aurora Divergence – Quant Master isn’t just a strategy—it’s a movement. Crafted with originality and driven by community passion, it rises above the flood of generic scripts to deliver a system that’s as powerful as it is beautiful. With its quant-grade logic, DAFE visuals, and robust risk controls, it empowers traders to tackle futures with confidence and style. Join the DAFE crew, light up your charts, and let’s outsmart the markets together!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Is it Time for a Pullback? Check Bars Since MA TestAn old market adage declares that “prices never move in a straight line.” Dips occur even in bullish markets. But how can traders know when prices may be due for a pullback?
Today’s script tries to answer that question by asking how many bars have passed since a stock, index or other symbol has tested a given moving average. Long periods of time without touching a line such as the 50-day simple moving average, for example, could prompt traders to be more patient.
Bars Since MA Test counts how many bars have passed since prices touched or crossed the MA in question. The resulting value is plotted in a simple histogram. Users can set the MA length and type. By default, it uses the 50-day simple moving average (SMA).
The chart above applies Bars Since MA Test to the S&P 500. It shows that the index has gone 129 bars without testing its 50-day SMA. That’s the longest since a 146-bar stretch between July 2006 and February 2007.
Other longer runs include January-August 1995 (156 bars), November 1960-June 1961 (144 bars) and April-November 1958 (158 bars).
Given the small number of comparable readings, could traders suspect the current advance is getting long in the tooth?
TradeStation has, for decades, advanced the trading industry, providing access to stocks, options and futures. If you're born to trade, we could be for you. See our Overview for more.
Past performance, whether actual or indicated by historical tests of strategies, is no guarantee of future performance or success. There is a possibility that you may sustain a loss equal to or greater than your entire investment regardless of which asset class you trade (equities, options or futures); therefore, you should not invest or risk money that you cannot afford to lose. Online trading is not suitable for all investors. View the document titled Characteristics and Risks of Standardized Options at www.TradeStation.com . Before trading any asset class, customers must read the relevant risk disclosure statements on www.TradeStation.com . System access and trade placement and execution may be delayed or fail due to market volatility and volume, quote delays, system and software errors, Internet traffic, outages and other factors.
Securities and futures trading is offered to self-directed customers by TradeStation Securities, Inc., a broker-dealer registered with the Securities and Exchange Commission and a futures commission merchant licensed with the Commodity Futures Trading Commission). TradeStation Securities is a member of the Financial Industry Regulatory Authority, the National Futures Association, and a number of exchanges.
TradeStation Securities, Inc. and TradeStation Technologies, Inc. are each wholly owned subsidiaries of TradeStation Group, Inc., both operating, and providing products and services, under the TradeStation brand and trademark. When applying for, or purchasing, accounts, subscriptions, products and services, it is important that you know which company you will be dealing with. Visit www.TradeStation.com for further important information explaining what this means.
Breakdown or Buyable Dip? Pullback Depth Can HelpAs a common adage says, “the market doesn’t move in a straight line.” But when prices have fallen, it’s not always clear whether buying makes sense. That’s where today’s script may help.
Most traditional indicators judge movement based on price. That’s obviously important, but time can also be helpful. After all, there’s a big difference between probing a low from 2-3 weeks ago versus a low from months or even years in the past.
Pullback Depth clearly illustrates this by answering the question: “Today’s low is the lowest in how many bars?”
The resulting integer is plotted in a simple histogram. Values are always negative because bars with higher absolute values (meaning more negative, or further below zero) are potentially more bearish.
The study also has a maximum lookback period to avoid overwhelming the study with too many bars. Its default setting of 125 bars includes enough history to illustrate the trend.
The stock market’s recent run has seen only shallow pullbacks. Most dips have probed 1-2 weeks in the past, while Friday’s selloff only turned back the clock a month.
Consider two other previous moments.
First, the great bull run of 1995 saw only shallow pullbacks. (None exceeded 50 days.):
In contrast, early 2022 saw the S&P 500 test levels more than 100 candles into the past. It soon fell into an official “bear market:”
TradeStation has, for decades, advanced the trading industry, providing access to stocks, options and futures. If you're born to trade, we could be for you. See our Overview for more.
Past performance, whether actual or indicated by historical tests of strategies, is no guarantee of future performance or success. There is a possibility that you may sustain a loss equal to or greater than your entire investment regardless of which asset class you trade (equities, options or futures); therefore, you should not invest or risk money that you cannot afford to lose. Online trading is not suitable for all investors. View the document titled Characteristics and Risks of Standardized Options at www.TradeStation.com . Before trading any asset class, customers must read the relevant risk disclosure statements on www.TradeStation.com . System access and trade placement and execution may be delayed or fail due to market volatility and volume, quote delays, system and software errors, Internet traffic, outages and other factors.
Securities and futures trading is offered to self-directed customers by TradeStation Securities, Inc., a broker-dealer registered with the Securities and Exchange Commission and a futures commission merchant licensed with the Commodity Futures Trading Commission). TradeStation Securities is a member of the Financial Industry Regulatory Authority, the National Futures Association, and a number of exchanges.
TradeStation Securities, Inc. and TradeStation Technologies, Inc. are each wholly owned subsidiaries of TradeStation Group, Inc., both operating, and providing products and services, under the TradeStation brand and trademark. When applying for, or purchasing, accounts, subscriptions, products and services, it is important that you know which company you will be dealing with. Visit www.TradeStation.com for further important information explaining what this means.
Binomial Option Pricing ModelA binomial option pricing model is an option pricing model that calculates an option's price using binomial trees. The BOPM method of calculating option prices is different from the Black-Scholes Model because it provides more flexibility in the type of options you want to price. The BOPM, unlike the BS model typically used for European style options, allows you to price options which have the ability to exercise early, such as American or Bermudan options. Although you can use the BOPM for any option style.
This specific model allows you to price both American and European vanilla options.
The way the BOPM calculates option prices is by:
First, dividing up the time until expiry into equal parts called steps. This specific model presented only uses 2 steps. For example, say you have an option with an expiry of 60 days, and your binomial tree has only two steps. Then each step will contain 30 days.
Second, the model will project the expected price of the underlying at the end of each step, called a node. The expected price is calculated by using the underlying's volatility and projecting what the price of the underlying would be if it were to rise and fall. This step is repeated until the terminal node, aka the end of the tree, is reached.
Third, once the terminal node's expected underlying prices are calculated, their expected option prices must be calculated.
Finally, after calculating the terminal option prices, backwards induction must be used to calculate the option prices at the previous nodes, until you reach Node 0, aka the current option price.
In order to use this model:
1st. Enter your option's strike price.
2nd. Enter the risk-free-rate of the currency the option is based in.
3rd. Enter the dividend yield of the underlying if it's a stock, or the foreign risk-free-rate if it's an FX option.
*For example, if you were trading an AAPL stock option, in the risk-free-rate box mentioned in step 2, you would enter the US risk-free-rate because AAPL options are traded in US dollars. In the dividend yield box mentioned in step 3, you would enter the stock's dividend yield, which for AAPL is 0.82.
*If you were, for example, trading an option on the EUR/JPY currency pair, the risk-free-rate mentioned in step 2, would be the Japanese risk-free-rate. Then in the the dividend yield box from step 3, you'd input the Eurozone risk-free-rate.
*If you were trading an options on futures contract, the risk-free-rate mentioned in step 2, would be the risk-free-rate for whatever currency the futures contract is denominated in. For example EUR futures are denominated in USD, so you would input the US risk-free-rate. Meanwhile, something like FTSE futures are denominated in GBP, so you would input the British risk-free-rate. As for the dividend yield box mentioned in step 3, for all options on futures, enter 0.
4th. Pick what type of underlying the option is based on: stock, FX, or futures.
5th. Pick the style of option: American or European.
6th. Pick the type of option: Long Call or Long Put.
7th. Input your time until expiry. You can express this in terms of days, hours, and minutes.
8th. Lastly, input your chart time-frame in term of minutes. For example, if you're using the 1 min time-frame enter 1, 4hr time-frame enter 480, daily time-frame enter 1440.
*Disclaimer, because this particular model only uses 2 steps, it won't work on stocks with high prices (over $100). If you want to use this on stocks with prices greater than $100, you would need to add more steps to the code, shown below. The model in its current form should work for stocks below $100.
Predicted Funding RatesOverview
The Predicted Funding Rates indicator calculates real-time funding rate estimates for perpetual futures contracts on Binance. It uses triangular weighting algorithms on multiple different timeframes to ensure an accurate prediction.
Funding rates are periodic payments between long and short position holders in perpetual futures markets
If positive, longs pay shorts (usually bullish)
If negative, shorts pay longs (usually bearish)
This is a prediction. Actual funding rates depend on the instantaneous premium index, derived from bid/ask impacts of futures. So whilst it may imitate it similarly, it won't be completely accurate.
This only applies currently to Binance funding rates, as HyperLiquid premium data isn't available. Other Exchanges may be added if their premium data is uploaded.
Methods
Method 1: Collects premium 1-minunute data using triangular weighing over 8 hours. This granular method fills in predicted funding for 4h and less recent data
Method 2: Multi-time frame approach. Daily uses 1 hour data in the calculation, 4h + timeframes use 15M data. This dynamic method fills in higher timeframes and parts where there's unavailable premium data on the 1min.
How it works
1) Premium data is collected across multiple timeframes (depending on the timeframe)
2) Triangular weighing is applied to emphasize recent data points linearly
Tri_Weighing = (data *1 + data *2 + data *3 + data *4) / (1+2+3+4)
3) Finally, the funding rate is calculated
FundingRate = Premium + clamp(interest rate - Premium, -0.05, 0.05)
where the interest rate is 0.01% as per Binance
Triangular weighting is calculated on collected premium data, where recent data receives progressively higher weight (1, 2, 3, 4...). This linear weighting scheme provides responsiveness to recent market conditions while maintaining stability, similar to an exponential moving average but with predictable, linear characteristics
A visual representation:
Data points: ──────────────>
Weights: 1 2 3 4 5
Importance: ▂ ▃ ▅ ▆ █
How to use it
For futures traders:
If funding is trending up, the market can be interpreted as being in a bull market
If trending down, the market can be interpreted as being in a bear market
Even used simply, it allows you to gauge roughly how well the market is performing per funding. It can basically be gauged as a sentiment indicator too
For funding rate traders:
If funding is up, it can indicate a long on implied APR values
If funding is down, it can indicate a short on implied APR values
It also includes an underlying APR, which is the annualized funding rate. For Binance, it is current funding * (24/8) * 365
For Position Traders: Monitor predicted funding rates before entering large positions. Extremely high positive rates (>0.05% for 8-hour periods) suggest overleveraged longs and potential reversal risk. Conversely, extreme negative rates indicate shorts dominance
Table:
Funding rate: Gives the predicted funding rate as a percentage
Current premium: Displays the current premium (difference between perpetual futures price and the underlying spot) as a percentage
Funding period: You can choose between 1 hour funding (HyperLiquid usually) and 8 hour funding (Binance)
APR: Underlying annualized funding rate
What makes it original
Whilst some predicted funding scripts exist, some aren't as accurate or have gaps in data. And seeing as funding values are generally missing from TV tickers, this gives traders accessibility to the script when they would have to use other platforms
Notes
Currently only compatible with symbols that have Binance USDT premium indices
Optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off
Actual funding rates may differ
Inputs
Funding Period: Choose between "8 Hour" (standard Binance cycle) or "1 Hour" (divides the 8-hour rate by 8 for granular comparison)
Plot Type: Display as "Funding Rate" (percentage per interval) or "APR" (annualized rate calculated as 8-hour rate × 3 × 365)
Table: Toggle the information table showing current funding rate, premium, funding period, and APR in the top-right corner
Positive Colour: Sets the colour for positive funding rates where longs pay shorts (default: #00ffbb turquoise)
Negative Colour: Sets the colour for negative funding rates where shorts pay longs (default: red)
Table Background: Controls the background colour and transparency of the information table (default: transparent dark blue)
Table Text Colour: Sets the colour for all text labels in the information table (default: white)
Table Text Size: Controls font size with options from Tiny to Huge, with Small as the default balance of readability and space
TimeMapTimeMap is a visual price-reference indicator designed to help traders rapidly visualize how current price levels relate to significant historical closing prices. It overlays your chart with reference lines representing past weekly, monthly, quarterly (3-month), semi-annual (6-month), and annual closing prices. By clearly plotting these historical price references, TimeMap helps traders quickly gauge price position relative to historical market structure, aiding in the identification of trends, support/resistance levels, and potential reversals.
How it Works:
The indicator calculates the precise number of historical bars corresponding to weekly, monthly, quarterly, semi-annual, and annual intervals, dynamically adjusting according to your chart’s timeframe (intraday, daily, weekly, monthly) and chosen market type (Stocks US, Crypto, Forex, or Futures). Historical closing prices from these periods are plotted directly on your chart as horizontal reference lines.
For intraday traders, the script accurately calculates historical offsets considering regular and extended trading sessions (e.g., pre-market and after-hours sessions for US stocks), ensuring correct positioning of historical lines.
User-Configurable Inputs Explained in Detail:
Market Type:
Allows you to specify your trading instrument type, automatically adjusting calculations for:
- Stocks US (default): 390 minutes per regular session (780 minutes if extended hours enabled), 5 trading days/week.
- Crypto: 1440 minutes/day, 7 trading days/week.
- Forex: 1440 minutes/day, 5 trading days/week.
- Futures: 1320 minutes/day, 5 trading days/week.
Show Weekly Close:
When enabled, plots a line at the exact closing price from one week ago. Provides short-term context and helps identify recent price momentum.
Show Monthly Close:
When enabled, plots a line at the exact closing price from one month ago. Helpful for evaluating medium-term price positioning and monthly trend strength.
Show 3-Month Close:
When enabled, plots a line at the exact closing price from three months ago. Useful for assessing quarterly market shifts, intermediate trend changes, and broader market sentiment.
Show 6-Month Close:
When enabled, plots a line at the exact closing price from six months ago. Useful for identifying semi-annual trends, significant price pivots, and longer-term support/resistance levels.
Show 1-Year Close:
When enabled, plots a line at the exact closing price from one year ago. Excellent for assessing long-term market direction and key annual price levels.
Enable Smoothing:
Activates a Simple Moving Average (SMA) smoothing of historical reference lines, reducing volatility and providing clearer visual references. Recommended for traders preferring less volatile reference levels.
Smoothing Length:
Determines the number of bars used in calculating the SMA smoothing of historical lines. Higher values result in smoother but slightly delayed reference lines; lower values offer more immediate yet more volatile levels.
Use Extended Hours (Intraday Only):
When enabled (only applicable for Stocks US), it accounts for pre-market and after-hours trading sessions, providing accurate intraday historical line calculations based on extended sessions (typically 780 minutes/day total).
Important Notes and Compliance:
- This indicator does not provide trading signals, recommendations, or predictions. It serves purely as a visual analytical tool to supplement traders’ existing methods.
- Historical lines plotted are strictly based on past available price data; the indicator never accesses future data or data outside the scope of Pine Script’s standard capabilities.
- The script incorporates built-in logic to avoid runtime errors if insufficient historical data exists for a selected timeframe, ensuring robustness even with limited historical bars.
- TimeMap is original work developed exclusively by Julien Eche (@Julien_Eche). It does not reuse or replicate third-party or existing open-source scripts.
Recommended Best Practices:
- Use TimeMap as a complementary analytical reference, not as a standalone strategy or trade decision-making tool.
- Adapt displayed historical periods and smoothing settings based on your trading style and market approach.
- Default plot colors are optimized for readability on dark-background charts; adjust as necessary according to your preference and chart color scheme.
This script is published open-source to benefit the entire TradingView community and fully complies with all TradingView script publishing rules and guidelines.
Easy CotHow to Use the Commitment of Traders (COT) Report for Market Analysis
The Commitment of Traders (COT) report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that breaks down the open interest in various futures markets. It categorizes traders into three main groups: Commercials, Non-Commercials, and Retail Traders (Non-Reportable positions). Understanding and analyzing the COT report can provide insights into market sentiment and potential reversals, especially in commodity, currency, and stock index futures.
Key Components of the COT Report
Commercials (Hedgers)
These are entities involved in the production or consumption of the underlying asset. For example, oil producers might hedge by selling oil futures to lock in prices, while airlines might buy futures to hedge against rising prices.
Commercials typically act as hedgers, so their positions can indicate the need for protection rather than speculative intent. Because they are less price-sensitive, their positions are usually opposite to the trend near market reversals.
Non-Commercials (Large Speculators)
This group includes hedge funds, asset managers, and large traders who take speculative positions to profit from price movements.
Non-Commercials are often trend-followers, meaning they increase long positions in an uptrend and short positions in a downtrend. When Non-Commercials become extremely bullish or bearish, it may signal a potential market reversal.
Retail Traders (Non-Reportable Positions)
These are smaller individual traders whose positions are too small to be reported individually.
Retail traders tend to be less experienced and are often on the wrong side of major market moves, so extreme positions by retail traders can sometimes signal a market turning point.
How to Interpret the COT Data
1. Identify Extreme Positions
Extreme Long or Short Positions: When a group reaches a historically extreme level of long or short positions, it often signals a potential reversal. For instance, if Non-Commercials are overwhelmingly long, it may indicate that the uptrend is overextended, and a reversal could be near.
Contrarian Indicator: Since Retail Traders are often on the wrong side, you may look for signals where they are extremely long or short, indicating a possible reversal in the opposite direction.
2. Look for Divergences
Divergence Between Groups: If Non-Commercials (speculators) and Retail Traders are moving in opposite directions, it could indicate that a trend is losing momentum and a reversal is possible.
Commercials vs. Non-Commercials: Commercials are often positioned opposite to Non-Commercials. If there’s a divergence where Non-Commercials are highly bullish, but Commercials are increasingly bearish, it might suggest a coming reversal.
3. Trend Confirmation and Reversal Signals
Trend Confirmation: If both Non-Commercials and Retail Traders are aligned in one direction, it might confirm the trend. However, keep in mind that such alignment may signal the later stages of a trend.
Reversal Signals: Look for signs when Non-Commercials are reaching a peak in one direction while Retail Traders peak in the opposite. Such situations can often indicate that the current trend is close to exhaustion.
Using the COT Report in Trading Strategies
Contrarian Trading Strategy
Extreme Positions as Reversal Signals: Use COT data to identify extreme positions. For instance, if Non-Commercials have a very high long position in a commodity, it might suggest that a bullish trend is overextended and a bearish reversal could be near.
Retail Trader Extremes: If Retail Traders are heavily long or short, consider taking the opposite position once you have additional confirmation signals (e.g., technical indicators).
Following the Trend with Large Speculators
Non-Commercials tend to be trend-followers, so if you see them increasingly long (or short) on an asset, it could be a signal to follow the trend until extreme levels are reached.
Using Divergences for Entry and Exit Points
Entry: If Non-Commercials are long, but Retail Traders are heavily short, consider entering a long position as it may confirm the trend.
Exit: If Non-Commercials begin to reduce their positions while Retail Traders increase theirs, it might be time to consider exiting, as the trend could be losing momentum.
Globex, Extended, Daily, Weekly, Monthly, Yearly Range* Adds Right Side Only Price Line & Labels for Tracking without Extending Both Sides
* Tracks Current, Previous, and Two Previous Globex Sessions/ Futures:
* Tracks Current, Previous, and Two Previous Extended Session/ Stocks:
* Tracks Current, Previous, Two, & Three Previous Day Session/ Equities:
* Tracks Current, Last, Two, Three, Four, & Five Week Session/ Equities:
* Tracks Current, Last, Two, Three, Four, & Five Month Session/ Equities:
* Tracks Current, Last, Two, Three, Four, & Five Year Session/ Equities:
* Allows Custom Range on Globex, Extended, & Daily Sessions
* Allows Custom Range on Weekly, Monthly, & Yearly Sessions
* Lines & Labels Are Not Visible on Chart Scales
* Reversible Text & Background Color
* Lines Extend Accordingly with Range
* Labels show Price & Percent Change
* Background Colors should match Chart Color to avoid Overlapping Text & Labels
* Lines have Offset Extension
* Labels have Offset Extension
* Globex Session is only visible on Futures & if Current Timeframe is Intraday
* Extended Session is only visible on Stocks & if Current Timeframe is Intraday
* Daily, Weekly, Monthly, & Yearly Sessions are visible on All Symbols & All Timeframes
* Globex, Extended, & Regular use their Default Time Sessions but allow Customization
* For Back Testing Default Sessions, switch over on the Menu to Style and Turn On/Off their Background Color; Any Area on the Chart Without Background Color is Regular Session
LibraryCOTLibrary "LibraryCOT"
This library provides tools to help Pine programmers fetch Commitment of Traders (COT) data for futures.
rootToCFTCCode(root)
Accepts a futures root and returns the relevant CFTC code.
Parameters:
root : Root prefix of the future's symbol, e.g. "ZC" for "ZC1!"" or "ZCU2021".
Returns: The part of a COT ticker corresponding to `root`, or "" if no CFTC code exists for the `root`.
currencyToCFTCCode(curr)
Converts a currency string to its corresponding CFTC code.
Parameters:
curr : Currency code, e.g., "USD" for US Dollar.
Returns: The corresponding to the currency, if one exists.
optionsToTicker(includeOptions)
Returns the part of a COT ticker using the `includeOptions` value supplied, which determines whether options data is to be included.
Parameters:
includeOptions : A "bool" value: 'true' if the symbol should include options and 'false' otherwise.
Returns: The part of a COT ticker: "FO" for data that includes options and "F" for data that doesn't.
metricNameAndDirectionToTicker(metricName, metricDirection)
Returns a string corresponding to a metric name and direction, which is one component required to build a valid COT ticker ID.
Parameters:
metricName : One of the metric names listed in this library's chart. Invalid values will cause a runtime error.
metricDirection : Metric direction. Possible values are: "Long", "Short", "Spreading", and "No direction". Valid values vary with metrics. Invalid values will cause a runtime error.
Returns: The part of a COT ticker ID string, e.g., "OI_OLD" for "Open Interest" and "No direction", or "TC_L" for "Traders Commercial" and "Long".
typeToTicker(metricType)
Converts a metric type into one component required to build a valid COT ticker ID. See the "Old and Other Futures" section of the CFTC's Explanatory Notes for details on types.
Parameters:
metricType : Metric type. Accepted values are: "All", "Old", "Other".
Returns: The part of a COT ticker.
convertRootToCOTCode(mode, convertToCOT)
Depending on the `mode`, returns a CFTC code using the chart's symbol or its currency information when `convertToCOT = true`. Otherwise, returns the symbol's root or currency information. If no COT data exists, a runtime error is generated.
Parameters:
mode : A string determining how the function will work. Valid values are:
"Root": the function extracts the futures symbol root (e.g. "ES" in "ESH2020") and looks for its CFTC code.
"Base currency": the function extracts the first currency in a pair (e.g. "EUR" in "EURUSD") and looks for its CFTC code.
"Currency": the function extracts the quote currency ("JPY" for "TSE:9984" or "USDJPY") and looks for its CFTC code.
"Auto": the function tries the first three modes (Root -> Base Currency -> Currency) until a match is found.
convertToCOT : "bool" value that, when `true`, causes the function to return a CFTC code. Otherwise, the root or currency information is returned. Optional. The default is `true`.
Returns: If `convertToCOT` is `true`, the part of a COT ticker ID string. If `convertToCOT` is `false`, the root or currency extracted from the current symbol.
COTTickerid(COTType, CTFCCode, includeOptions, metricName, metricDirection, metricType)
Returns a valid TradingView ticker for the COT symbol with specified parameters.
Parameters:
COTType : A string with the type of the report requested with the ticker, one of the following: "Legacy", "Disaggregated", "Financial".
CTFCCode : The for the asset, e.g., wheat futures (root "ZW") have the code "001602".
includeOptions : A boolean value. 'true' if the symbol should include options and 'false' otherwise.
metricName : One of the metric names listed in this library's chart.
metricDirection : Direction of the metric, one of the following: "Long", "Short", "Spreading", "No direction".
metricType : Type of the metric. Possible values: "All", "Old", and "Other".
Returns: A ticker ID string usable with `request.security()` to fetch the specified Commitment of Traders data.
Dominant Cycle Tuned RsiIntroduction
Adaptive technical indicators are importants in a non stationary market, the ability to adapt to a situation can boost the efficiency of your strategy. A lot of methods have been proposed to make technical indicators "smarters" , from the use of variable smoothing constant for exponential smoothing to artificial intelligence.
The dominant cycle tuned rsi depend on the dominant cycle period of the market, such method allow the rsi to return accurate peaks and valleys levels. This indicator is an estimation of the cycle finder tuned rsi proposed by Lars von Thienen published in Decoding the Hidden Market Rhythm/Fine-tuning technical indicators using the dominant market vibration/2010 using the cycle measurement method described by John F.Ehlers in Cybernetic Analysis for Stocks and Futures .
The following section is for information purpose only, it can be technical so you can skip directly to the The Indicator section.
Frequency Estimation and Maximum Entropy Spectral Analysis
“Looks like rain,” said Tom precipitously.
Tom would have been a great weather forecaster, but market patterns are more complex than weather ones. The ability to measure dominant cycles in a complex signal is hard, also a method able to estimate it really fast add even more challenge to the task. First lets talk about the term dominant cycle , signals can be decomposed in a sum of various sine waves of different frequencies and amplitudes, the dominant cycle is considered to be the frequency of the sine wave with the highest amplitude. In general the highest frequencies are those who form the trend (often called fundamentals) , so detrending is used to eliminate those frequencies in order to keep only mid/mid - highs ones.
A lot of methods have been introduced but not that many target market price, Lars von Thienen proposed a method relying on the following processing chain :
Lars von Thienen Method = Input -> Filtering and Detrending -> Discrete Fourier Transform of the result -> Selection using Bartels statistical test -> Output
Thienen said that his method is better than the one proposed by Elhers. The method from Elhers called MESA was originally developed to interpret seismographic information. This method in short involve the estimation of the phase using low amount of information which divided by 360 return the frequency. At first sight there are no relations with the Maximum entropy spectral estimation proposed by Burg J.P. (1967). Maximum Entropy Spectral Analysis. Proceedings of 37th Meeting, Society of Exploration Geophysics, Oklahoma City.
You may also notice that these methods are plotted in the time domain where more classic method such as : power spectrum, spectrogram or FFT are not. The method from Elhers is the one used to tune our rsi.
The Indicator
Our indicator use the dominant cycle frequency to calculate the period of the rsi thus producing an adaptive rsi . When our adaptive rsi cross under 70, price might start a downtrend, else when our adaptive rsi crossover 30, price might start an uptrend. The alpha parameter is a parameter set to be always lower than 1 and greater than 0. Lower values of alpha minimize the number of detected peaks/valleys while higher ones increase the number of those. 0.07 for alpha seems like a great parameter but it can sometimes need to be changed.
The adaptive indicator can also detect small top/bottoms of small periods
Of course the indicator is subject to failures
At the end it is totally dependent of the dominant cycle estimation, which is still a rough method subject to uncertainty.
Conclusion
Tuning your indicator is a great way to make it adapt to the market, but its also a complex way to do so and i'm not that convinced about the complexity/result ratio. The version using chart background will be published separately.
Feel free to tune your indicators with the estimator from elhers and see if it provide a great enhancement :)
Thanks for reading !
References
for the calculation of the dominant cycle estimator originally from www.davenewberg.com
Decoding the Hidden Market Rhythm (2010) Lars von Thienen
Ehlers , J. F. 2004 . Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading . Wiley
Universal Sentiment Oscillator with Trade RecommendationsUniversal Sentiment Oscillator & Strategy Guide
Summary
This all-in-one indicator is designed to be a comprehensive co-pilot for your trading journey. It moves beyond simple buy/sell signals by analyzing the underlying market sentiment and providing a dynamic, risk-assessed guide of potential trading strategies. Whether you're a novice learning the ropes or an expert seeking confirmation, this tool provides a structured framework for making smarter, more informed decisions in stocks, options, and futures.
How It Works
The core of the indicator is the Sentiment Oscillator, which calculates a score from -5 (Extremely Bearish) to +5 (Extremely Bullish) on every bar. This isn't just a single measurement; it's a weighted aggregate of several key technical conditions:
Trend Analysis: Price position relative to the 20, 50, and 200 EMAs.
Momentum Analysis: The current RSI value.
Hybrid Analysis: The state of the MACD and its signal line.
These factors are intelligently combined and normalized to produce a single, intuitive sentiment score, giving you an at-a-glance understanding of the market's pulse.
Core Features
Dynamic Trade Recommendation Table:
The informational heart of the indicator. This on-chart table provides a list of potential trades perfectly aligned with the current sentiment score.
Risk-Ranked Strategies:
All suggested trades are logically ordered by risk, helping you quickly identify strategies that match your comfort level.
Adjusted Trade Suggestions:
The indicator analyzes sentiment momentum (the score vs. its signal line) to provide proactive, forward-looking trade ideas based on where the market might be heading next.
Customizable Trading Styles:
Tell the indicator if you are a Conservative, Neutral, or Aggressive trader, and the "Adjusted Trade Suggestion" will automatically tailor its recommendations to your personal risk preference.
Context-Aware Futures Mode:
When viewing a futures contract, enable this mode to switch all recommendations from stock/options to futures-specific actions (e.g., "Cautious Long," "Monitor Range").
Predictive Sentiment Cone:
Visualize the potential short-term path of sentiment based on current momentum, helping you anticipate future conditions.
Fully Customizable:
Every parameter—from EMA lengths to trade filters—can be adjusted, allowing you to fine-tune the indicator to your exact specifications.
How to Use This Indicator
This tool is flexible and can be integrated into many trading systems. Here is a powerful, professional approach:
Top-Down Analysis (for Swing or Position Trading):
Establish the Trend: Start on the higher timeframes (Monthly, Weekly, Daily). Use the oscillator's color and score to define the dominant, long-term market sentiment. You only want to look for trades that align with this macro trend.
Refine the Entry: Drop down to the medium timeframes (4-Hour, 1-Hour). Wait for the sentiment on these charts to come into alignment with the higher-timeframe trend. This pullback or consolidation is your "zone of interest."
Pinpoint the Execution: Move to a lower timeframe (e.g., 15-Minute). Use the Adjusted Trade Suggestion and Sentiment Momentum to find a precise entry as momentum begins to shift back in the direction of the primary trend. You can set alerts on the oscillator's zero-line for early warnings of a sentiment shift.
As a Confirmation Tool: If you have an existing trade idea, use the indicator to validate it. Does the sentiment score align with your bullish or bearish thesis? Does the momentum confirm that now is a good time to enter?
As an Idea Generation Tool: Unsure what to trade? Browse different assets and let the indicator's "Primary Trades" and "Adjusted Trade Suggestion" present you with a list of risk-assessed ideas that you can then investigate further.
Disclaimer: This is an analysis tool and should not be considered financial advice. All forms of trading involve substantial risk. You should not trade with money you cannot afford to lose. Always perform your own due diligence and use this indicator as one component of a complete trading plan.
Risk TrackerThis Risk Tracker Pine Script provides traders with a customizable tool for tracking and managing trade risk directly on their chart. The script is designed to accommodate both futures and crypto trades, allowing you to monitor risk and reward parameters, adjust contract sizes, and manage leverage in real-time.
Key Features:
1. Trade Direction and Risk-Reward Ratio:
• Select between Long or Short trade directions.
• Set a custom Risk-Reward Ratio (RRR) to calculate potential profit and loss levels based on your trade setup.
2. Customizable Parameters:
• Input fields for contract size, leverage, margin, and maximum drawdown allow you to adjust the risk settings depending on the market you are trading.
• You can toggle between using a dollar-based or percentage-based risk calculation depending on whether you’re trading futures (USD-based) or crypto.
3. Real-time Stop-Loss and Take-Profit Calculation:
• The script automatically calculates and draws the Stop-Loss (SL) and Take-Profit (TP) levels on the chart based on your entry price and selected risk settings.
• The color of the SL and TP lines is customizable, allowing you to visually distinguish profit and loss levels.
4. Historical Price Levels:
• If there is no active trade, the script scans historical price data to find the last instances when the price hit the predefined stop-loss or take-profit levels, helping you understand past price behavior.
5. Risk Management Table:
• A summary table is displayed on the chart, showing the key metrics of your trade, including:
• Tick value and Dollar value for futures.
• Margin and Leverage for crypto.
• Risk-Reward Ratio, Entry price, Risk and Profit in USD or percentage terms.
• The table dynamically updates based on the current trade status.
6. Extended Chart Visualization:
• Option to extend the SL and TP lines to the left of the chart, allowing you to easily view these levels across multiple timeframes and bars.
This script helps ensure you are always aware of your trade’s risk profile, providing a clear and visual representation of potential profit and loss, both in terms of percentage and dollar value. Ideal for futures and crypto traders who rely on precise risk management to maintain profitability.
LibraryCOT_NZLibrary "LibraryCOT_NZ"
This library provides tools to help Pine programmers fetch Commitment of Traders (COT) data for futures.
rootToCFTCCode(root)
Accepts a futures root and returns the relevant CFTC code.
Parameters:
root (simple string) : Root prefix of the future's symbol, e.g. "ZC" for "ZC1!"" or "ZCU2021".
Returns: The part of a COT ticker corresponding to `root`, or "" if no CFTC code exists for the `root`.
currencyToCFTCCode(currency)
Converts a currency string to its corresponding CFTC code.
Parameters:
currency (simple string)
Returns: The corresponding to the currency, if one exists.
optionsToTicker(includeOptions)
Returns the part of a COT ticker using the `includeOptions` value supplied, which determines whether options data is to be included.
Parameters:
includeOptions (simple bool) : A "bool" value: 'true' if the symbol should include options and 'false' otherwise.
Returns: The part of a COT ticker: "FO" for data that includes options and "F" for data that doesn't.
metricNameAndDirectionToTicker(metricName, metricDirection)
Returns a string corresponding to a metric name and direction, which is one component required to build a valid COT ticker ID.
Parameters:
metricName (simple string) : One of the metric names listed in this library's chart. Invalid values will cause a runtime error.
metricDirection (simple string) : Metric direction. Possible values are: "Long", "Short", "Spreading", and "No direction". Valid values vary with metrics. Invalid values will cause a runtime error.
Returns: The part of a COT ticker ID string, e.g., "OI_OLD" for "Open Interest" and "No direction", or "TC_L" for "Traders Commercial" and "Long".
typeToTicker(metricType)
Converts a metric type into one component required to build a valid COT ticker ID. See the "Old and Other Futures" section of the CFTC's Explanatory Notes for details on types.
Parameters:
metricType (simple string) : Metric type. Accepted values are: "All", "Old", "Other".
Returns: The part of a COT ticker.
convertRootToCOTCode(mode, convertToCOT)
Depending on the `mode`, returns a CFTC code using the chart's symbol or its currency information when `convertToCOT = true`. Otherwise, returns the symbol's root or currency information. If no COT data exists, a runtime error is generated.
Parameters:
mode (simple string) : A string determining how the function will work. Valid values are:
"Root": the function extracts the futures symbol root (e.g. "ES" in "ESH2020") and looks for its CFTC code.
"Base currency": the function extracts the first currency in a pair (e.g. "EUR" in "EURUSD") and looks for its CFTC code.
"Currency": the function extracts the quote currency ("JPY" for "TSE:9984" or "USDJPY") and looks for its CFTC code.
"Auto": the function tries the first three modes (Root -> Base Currency -> Currency) until a match is found.
convertToCOT (simple bool) : "bool" value that, when `true`, causes the function to return a CFTC code. Otherwise, the root or currency information is returned. Optional. The default is `true`.
Returns: If `convertToCOT` is `true`, the part of a COT ticker ID string. If `convertToCOT` is `false`, the root or currency extracted from the current symbol.
COTTickerid(COTType, CFTCCode, includeOptions, metricName, metricDirection, metricType)
Returns a valid TradingView ticker for the COT symbol with specified parameters.
Parameters:
COTType (simple string) : A string with the type of the report requested with the ticker, one of the following: "Legacy", "Disaggregated", "Financial".
CFTCCode (simple string)
includeOptions (simple bool) : A boolean value. 'true' if the symbol should include options and 'false' otherwise.
metricName (simple string) : One of the metric names listed in this library's chart.
metricDirection (simple string) : Direction of the metric, one of the following: "Long", "Short", "Spreading", "No direction".
metricType (simple string) : Type of the metric. Possible values: "All", "Old", and "Other".
Returns: A ticker ID string usable with `request.security()` to fetch the specified Commitment of Traders data.
Weis V5 zigzag jayySomehow, I deleted version 5 of the zigzag script. Same name. I have added some older notes describing how the Weis Wave works.
I have also changed the date restriction that stopped the script from working after Dec 31, 2022.
What you see here is the Weis zigzag wave plotted directly on the price chart. This script is the companion to the Weis cumulative wave volume script.
What is a Weis wave? David Weis has been recognized as a Wyckoff method analyst he has written two books one of which, Trades About to Happen, describes the evolution of the now-popular Weis wave. The method employed by Weis is to identify waves of price action and to compare the strength of the waves on characteristics of wave strength. Chief among the characteristics of strength is the cumulative volume of the wave. There are other markers that Weis uses as well for example how the actual price difference between the start of the Weis wave from start to finish. Weis also uses time, particularly when using a Renko chart
David Weis did a futures io video which is a popular source of information about his method. (Search David Weis and futures.io. I strongly suggest you also read “Trades About to Happen” by David Weis.
This will get you up and running more quickly when studying charts. However, you should choose the Traditional method to be true to David Weis technique as described in his book "Trades About to Happen" and in the Futures IO Webcast featuring David Weis
. The Weis pip zigzag wave shows how far in terms of bar close price a Weis wave has traveled through the duration of a Weis wave. The Weis zigzag wave is used in combination with the Weis cumulative volume wave. The two waves should be set to the same "wave size".
To use this script, you must set the wave size: Using the traditional Weis method simply enter the desired wave size in the box "How should wave size be calculated", in this example I am using a traditional wave size of .25. Each wave for each security and each timeframe requires its own wave size. Although not the traditional method devised by David Weis a more automatic way to set wave size would be to use Average True Range (ATR). Using ATR is not the true Weis method but it does give you similar waves and, importantly, without the hassle described above. Once the Weis wave size is set then the zigzag wave will be shown with volume. Because Weis used the closing price of a wave to define waves a line Bar highs and bar lows are not captured by the Weis Wave. The default script setting is now cumulative volume waves using an ATR of 7 and a multiplication factor of .5.
To display volume in a way that does not crowd out neighbouring volumes Weis displayed volume as a maximum of 3 digits (usually). Consider two Weis Wave volumes 176,895,570 and 2,654,763,889. To display wave volume as three digits it is necessary to take a number such as 176,895,570 and truncate it. 176,895,570 can be represented as 177 X 10 to the power of 6. The number displayed must also be relative to other numbers in the field. If the highest volume on the page is: 2,654,763,889 and with only three numbers available to display the result the value shown must be 265 (265 X 10 to the power of 7). Since 176,895,570 is an order of magnitude smaller than 2,654,763,889 therefore 175,895,570 must be shown as 18 instead of 177. In this way, the relative magnitudes of the two volumes can be understood. All numbers in the field of view must be truncated by the same order of magnitude to make the relative volumes understandable. The script attempts to calculate the order of magnitude value automatically. If you see a red number in the field of view it means the script has failed to do the calculation automatically and you should use the manual method – use the dialogue box “Calculate truncated wave value automatically or manually”. Scroll down from the automatic method and select manual. Once "manual" is selected the values displayed become the power values or multipliers for each wave.
Using the manual method you will select a “Multiplier” in the next dialogue box. Scan the field and select the largest value in the field of view (visible chart) is the multiplier of interest. If you select a lower number than the maximum value will see at least one red “up”. If you are too high you will see at least one red “down”. Scroll in the direction recommended or the values on the screen will be totally incorrect. With volume truncated to the highest order values, the eye can quickly get a feel for relative volumes. It also reduces the crowding and overlapping of values on the screen. You can opt to show the full volume to help get a sense of the magnitude of the true volumes.
How does the script determine if a Weis wave is continuing to grow or not?
The script evaluates the closing price of each new bar relative to the "Weis wave size". Suppose the current bar closes at a new low close, within the current down wave, at $30.00. If the Weis wave size is $0.10 then the algorithm will remember the $30.00 close and compare it to the close of the next bar. If the bar close price does not close equal to or lower than $30.00 or close equal to or higher than $30.10 then the wave is still a down wave with a current low of $30.00. This is true even if the bar low is less than $30.00 or the bar high is greater than 30.10 – only the bar’s closing price matters. If a bar's closing price climbs back up to a close of $30.11 then because the closing price has moved more than $0.10 (the Weis wave size) then that is a wave reversal with a new up-trending wave. In the above example if there was currently a downward trending wave and the bar closes were as follows $30.00, $30.09, $30.01, $30.05, $30.10 The wave direction would continue to stay downward trending until the close of $30.10 was achieved. As such $30.00 would be the low and the following closes $30.09, $30.01, $30.05 would be allocated to the new upward-trending wave. If however There was a series of bar closes like this $30.00, $30.09, $30.01, $30.05, $29.99 since none of the closes was equal to above the 10-cent reversal target of $30.10 but instead, a new Weis wave low was achieved ($29.99). As such the closes of $30.09, $30.01, $30.05 would all be attributed to the continued down-trending wave with a current low of $29.99, even though the closing price for the interim bars was above $30.00. Now that the Weis Wave low is now 429.99 then, in order to reverse this continued downtrend price will need to close at or above $30.09 on subsequent bar closes assuming now new low bar close is achieved. With large wave sizes, wave direction can be in limbo for many bars before a close either renews wave direction or reverses it and confirms wave direction as either a reversal or a continuation. On the zig-zag, a wave line and its volume will not be "printed" until a wave reversal is confirmed.
The wave attribution is similar when using other methods to define wave size. If ATR is used for wave size instead of a traditional wave constant size such as $0.10 or $2 or 2000 pips or ... then the wave size is calculated based on current ATR instead of the Weis wave constant (Traditional selected value).
I have the option to display pseudo-Ord volume. In truth, Ord used more traditional zig-zag pivots of bar highs and lows. Waves using closes as pivots can have some significant differences. This difference can be lessened by using smaller time frames and larger wave sizes.
There are other options such to display the delta price or pip size of a Weis Wave, the number of bars in a wave, and a few other options.
SP500 Session Gap Fade StrategySummary in one paragraph
SPX Session Gap Fade is an intraday gap fade strategy for index futures, designed around regular cash sessions on five minute charts. It helps you participate only when there is a full overnight or pre session gap and a valid intraday session window, instead of trading every open. The original part is the gap distance engine which anchors both stop and optional target to the previous session reference close at a configurable flat time, so every trade’s risk scales with the actual gap size rather than a fixed tick stop.
Scope and intent
• Markets. Primarily index futures such as ES, NQ, YM, and liquid index CFDs that exhibit overnight gaps and regular cash hours.
• Timeframes. Intraday timeframes from one minute to fifteen minutes. Default usage is five minute bars.
• Default demo used in the publication. Symbol CME:ES1! on a five minute chart.
• Purpose. Provide a simple, transparent way to trade opening gaps with a session anchored risk model and forced flat exit so you are not holding into the last part of the session.
• Limits. This is a strategy. Orders are simulated on standard candles only.
Originality and usefulness
• Unique concept or fusion. The core novelty is the combination of a strict “full gap” entry condition with a session anchored reference close and a gap distance based TP and SL engine. The stop and optional target are symmetric multiples of the actual gap distance from the previous session’s flat close, rather than fixed ticks.
• Failure mode it addresses. Fixed sized stops do not scale when gaps are unusually small or unusually large, which can either under risk or over risk the account. The session flat logic also reduces the chance of holding residual positions into late session liquidity and news.
• Testability. All key pieces are explicit in the Inputs: session window, minutes before session end, whether to use gap exits, whether TP or SL are active, and whether to allow candle based closes and forced flat. You can toggle each component and see how it changes entries and exits.
• Portable yardstick. The main unit is the absolute price gap between the entry bar open and the previous session reference close. tp_mult and sl_mult are multiples of that gap, which makes the risk model portable across contracts and volatility regimes.
Method overview in plain language
The strategy first defines a trading session using exchange time, for example 08:30 to 15:30 for ES day hours. It also defines a “flat” time a fixed number of minutes before session end. At the flat bar, any open position is closed and the bar’s close price is stored as the reference close for the next session. Inside the session, the strategy looks for a full gap bar relative to the prior bar: a gap down where today’s high is below yesterday’s low, or a gap up where today’s low is above yesterday’s high. A full gap down generates a long entry; a full gap up generates a short entry. If the gap risk engine is enabled and a valid reference close exists, the strategy measures the distance between the entry bar open and that reference close. It then sets a stop and optional target as configurable multiples of that gap distance and manages them with strategy.exit. Additional exits can be triggered by a candle color flip or by the forced flat time.
Base measures
• Range basis. The main unit is the absolute difference between the current entry bar open and the stored reference close from the previous session flat bar. That value is used as a “gap unit” and scaled by tp_mult and sl_mult to build the target and stop.
Components
• Component one: Gap Direction. Detects full gap up or full gap down by comparing the current high and low to the previous bar’s high and low. Gap down signals a long fade, gap up signals a short fade. There is no smoothing; it is a strict structural condition.
• Component two: Session Window. Only allows entries when the current time is within the configured session window. It also defines a flat time before the session end where positions are forced flat and the reference close is updated.
• Component three: Gap Distance Risk Engine. Computes the absolute distance between the entry open and the stored reference close. The stop and optional target are placed as entry ± gap_distance × multiplier so that risk scales with gap size.
• Optional component: Candle Exit. If enabled, a bullish bar closes short positions and a bearish bar closes long positions, which can shorten holding time when price reverses quickly inside the session.
• Session windows. Session logic uses the exchange time of the chart symbol. When changing symbols or venues, verify that the session time string still matches the new instrument’s cash hours.
Fusion rule
All gates are hard conditions rather than weighted scores. A trade can only open if the session window is active and the full gap condition is true. The gap distance engine only activates if a valid reference close exists and use_gap_risk is on. TP and SL are controlled by separate booleans so you can use SL only, TP only, or both. Long and short are symmetric by construction: long trades fade full gap downs, short trades fade full gap ups with mirrored TP and SL logic.
Signal rule
• Long entry. Inside the active session, when the current bar shows a full gap down relative to the previous bar (current high below prior low), the strategy opens a long position. If the gap risk engine is active, it places a gap based stop below the entry and an optional target above it.
• Short entry. Inside the active session, when the current bar shows a full gap up relative to the previous bar (current low above prior high), the strategy opens a short position. If the gap risk engine is active, it places a gap based stop above the entry and an optional target below it.
• Forced flat. At the configured flat time before session end, any open position is closed and the close price of that bar becomes the new reference close for the following session.
• Candle based exit. If enabled, a bearish bar closes longs, and a bullish bar closes shorts, regardless of where TP or SL sit, as long as a position is open.
What you will see on the chart
• Markers on entry bars. Standard strategy entry markers labeled “long” and “short” on the gap bars where trades open.
• Exit markers. Standard exit markers on bars where either the gap stop or target are hit, or where a candle exit or forced flat close occurs. Exit IDs “long_gap” and “short_gap” label gap based exits.
• Reference levels. Horizontal lines for the current long TP, long SL, short TP, and short SL while a position is open and the gap engine is enabled. They update when a new trade opens and disappear when flat.
• Session background. This version does not add background shading for the session; session logic runs internally based on time.
• No on chart table. All decisions are visible through orders and exit levels. Use the Strategy Tester for performance metrics.
Inputs with guidance
Session Settings
• Trading session (sess). Session window in exchange time. Typical value uses the regular cash session for each contract, for example “0830-1530” for ES. Adjust if your broker or symbol uses different hours.
• Minutes before session end to force exit (flat_before_min). Minutes before the session end where positions are forced flat and the reference close is stored. Typical range is 15 to 120. Raising it closes trades earlier in the day; lowering it allows trades later in the session.
Gap Risk
• Enable gap based TP/SL (use_gap_risk). Master switch for the gap distance exit engine. Turning it off keeps entries and forced flat logic but removes automatic TP and SL placement.
• Use TP limit from gap (use_gap_tp). Enables gap based profit targets. Typical values are true for structured exits or false if you want to manage exits manually and only keep a stop.
• Use SL stop from gap (use_gap_sl). Enables gap based stop losses. This should normally remain true so that each trade has a defined initial risk in ticks.
• TP multiplier of gap distance (tp_mult). Multiplier applied to the gap distance for the target. Typical range is 0.5 to 2.0. Raising it places the target further away and reduces hit frequency.
• SL multiplier of gap distance (sl_mult). Multiplier applied to the gap distance for the stop. Typical range is 0.5 to 2.0. Raising it widens the stop and increases risk per trade; lowering it tightens the stop and may increase the number of small losses.
Exit Controls
• Exit with candle logic (use_candle_exit). If true, closes shorts on bullish candles and longs on bearish candles. Useful when you want to react to intraday reversal bars even if TP or SL have not been reached.
• Force flat before session end (use_forced_flat). If true, guarantees you are flat by the configured flat time and updates the reference close. Turn this off only if you understand the impact on overnight risk.
Filters
There is no separate trend or volatility filter in this version. All trades depend on the presence of a full gap bar inside the session. If you need extra filtering such as ATR, volume, or higher timeframe bias, they should be added explicitly and documented in your own fork.
Usage recipes
Intraday conservative gap fade
• Timeframe. Five minute chart on ES regular session.
• Gap risk. use_gap_risk = true, use_gap_tp = true, use_gap_sl = true.
• Multipliers. tp_mult around 0.7 to 1.0 and sl_mult around 1.0.
• Exits. use_candle_exit = false, use_forced_flat = true. Focus on the structured TP and SL around the gap.
Intraday aggressive gap fade
• Timeframe. Five minute chart.
• Gap risk. use_gap_risk = true, use_gap_tp = false, use_gap_sl = true.
• Multipliers. sl_mult around 0.7 to 1.0.
• Exits. use_candle_exit = true, use_forced_flat = true. Entries fade full gaps, stops are tight, and candle color flips flatten trades early.
Higher timeframe gap tests
• Timeframe. Fifteen minute or sixty minute charts on instruments with regular gaps.
• Gap risk. Keep use_gap_risk = true. Consider slightly higher sl_mult if gaps are structurally wider on the higher timeframe.
• Note. Expect fewer trades and be careful with sample size; multi year data is recommended.
Properties visible in this publication
• On average our risk for each position over the last 200 trades is 0.4% with a max intraday loss of 1.5% of the total equity in this case of 100k $ with 1 contract ES. For other assets, recalculations and customizations has to be applied.
• Initial capital. 100 000.
• Base currency. USD.
• Default order size method. Fixed with size 1 contract.
• Pyramiding. 0.
• Commission. Flat 2 USD per order in the Strategy Tester Properties. (2$ buying + 2$selling)
• Slippage. One tick in the Strategy Tester Properties.
• Process orders on close. ON.
Realism and responsible publication
• No performance claims are made. Past results do not guarantee future outcomes.
• Costs use a realistic flat commission and one tick of slippage per trade for ES class futures.
• Default sizing with one contract on a 100 000 reference account targets modest per trade risk. In practice, extreme slippage or gap through events can exceed this, so treat the one and a half percent risk target as a design goal, not a guarantee.
• All orders are simulated on standard candles. Shapes can move while a bar is forming and settle on bar close.
Honest limitations and failure modes
• Economic releases, thin liquidity, and limit conditions can break the assumptions behind the simple gap model and lead to slippage or skipped fills.
• Symbols with very frequent or very large gaps may require adjusted multipliers or alternative risk handling, especially in high volatility regimes.
• Very quiet periods without clean gaps will produce few or no trades. This is expected behavior, not a bug.
• Session windows follow the exchange time of the chart. Always confirm that the configured session matches the symbol.
• When both the stop and target lie inside the same bar’s range, the TradingView engine decides which is hit first based on its internal intrabar assumptions. Without bar magnifier, tie handling is approximate.
Legal
Education and research only. This strategy is not investment advice. You remain responsible for all trading decisions. Always test on historical data and in simulation with realistic costs before considering any live use.
Globex Trap w/ percentage [SLICKRICK]Globex Trap w/ Percentage
Overview
The Globex Trap w/ Percentage indicator is a powerful tool designed to help traders identify high-probability trading opportunities by analyzing price action during the Globex (overnight) session and regular trading hours. By combining Globex session ranges with Supply & Demand zones, this indicator highlights potential "trap" areas where significant price reactions may occur. Additionally, it calculates the Globex session range as a percentage of the daily Average True Range (ATR), providing valuable context for assessing market volatility.
This indicator is ideal for traders in futures markets or other instruments traded during Globex sessions, offering a visual and analytical edge for spotting key price levels and potential reversals or breakouts.
Key Features
Globex Session Tracking:
Visualizes the high and low of the Globex session (default: 3:00 PM to 6:30 AM PST) with customizable time settings.
Displays a semi-transparent box to mark the Globex range, with labels for "Globex High" and "Globex Low."
Calculates the Globex range as a percentage of the daily ATR, displayed as a label for quick reference.
Supply & Demand Zones:
Identifies Supply & Demand zones during regular trading hours (default: 6:00 AM to 8:00 AM PST) with customizable time settings.
Draws semi-transparent boxes to highlight these zones, aiding in the identification of key support and resistance areas.
Trap Area Identification:
Highlights potential trap zones where Globex ranges and Supply & Demand zones overlap, indicating areas where price may reverse or consolidate due to trapped traders.
Customizable Settings:
Adjust Globex and Supply & Demand session times to suit your trading preferences.
Toggle visibility of Globex and Supply & Demand zones independently.
Customize box colors for better chart readability.
Set the lookback period (default: 10 days) to control how many historical zones are displayed.
Configure the ATR length (default: 14) for the percentage calculation.
PST Timezone Default:
All times are based on Pacific Standard Time (PST) by default, ensuring accurate session tracking for users in this timezone or those aligning with U.S. West Coast market hours.
Recommended Usage
Timeframes: Best used on 1-hour charts or lower (e.g., 15-minute, 5-minute) for precise entry and exit points.
Markets: Optimized for futures (e.g., ES, NQ, CL) and other instruments traded during Globex sessions.
Historical Data: Ensure at least 10 days of historical data for optimal visualization of zones.
Strategy Integration: Use the indicator to identify potential reversals or breakouts at Globex highs/lows or Supply & Demand zones. The ATR percentage provides context for whether the Globex range is significant relative to typical daily volatility.
How It Works
Globex Session:
Tracks the high and low prices during the user-defined Globex session (default: 3:00 PM to 6:30 AM PST).
When the session ends, a box is drawn from the start to the end of the session, capturing the high and low prices.
Labels are placed at the midpoint of the session, showing "Globex High," "Globex Low," and the range as a percentage of the daily ATR (e.g., "75.23% of Daily ATR").
Supply & Demand Zones:
Tracks the high and low prices during the user-defined regular trading hours (default: 6:00 AM to 8:00 AM PST).
Draws a box to mark these zones, which often act as key support or resistance levels.
ATR Percentage:
Calculates the Globex range (high minus low) and divides it by the daily ATR to express it as a percentage.
This metric helps traders gauge whether the overnight price movement is significant compared to the instrument’s typical volatility.
Time Handling:
Uses PST (UTC-8) for all time calculations, ensuring accurate session timing for users aligning with this timezone.
Properly handles overnight sessions that cross midnight, ensuring seamless tracking.
Input Settings
Globex Session Settings:
Show Globex Session: Enable/disable Globex session visualization (default: true).
Globex Start/End Time: Set the start and end times for the Globex session (default: 3:00 PM to 6:30 AM PST).
Globex Box Color: Customize the color of the Globex session box (default: semi-transparent gray).
Supply & Demand Zone Settings:
Show Supply & Demand Zone: Enable/disable zone visualization (default: true).
Zone Start/End Time: Set the start and end times for Supply & Demand zones (default: 6:00 AM to 8:00 AM PST).
Zone Box Color: Customize the color of the zone box (default: semi-transparent aqua).
General Settings:
Days to Look Back: Number of historical days to display zones (default: 10).
ATR Length: Period for calculating the daily ATR (default: 14).
Notes
All times are in Pacific Standard Time (PST). Adjust the start and end times if your market operates in a different timezone or if you prefer different session windows.
The indicator is optimized for instruments with active Globex sessions, such as futures. Results may vary for non-24/5 markets.
A typo in the label "Globe Low" (should be "Globex Low") will be corrected in future updates.
Ensure your TradingView chart is set to display sufficient historical data to view the full lookback period.
Why Use This Indicator?
The Globex Trap w/ Percentage indicator provides a unique combination of session-based range analysis, Supply & Demand zone identification, and volatility context via the ATR percentage. Whether you’re a day trader, swing trader, or scalper, this tool helps you:
Pinpoint key price levels where institutional traders may act.
Assess the significance of overnight price movements relative to daily volatility.
Identify potential trap zones for high-probability setups.
Customize the indicator to fit your trading style and market preferences.
UB Short Signal (10Y Yield Future Spike)"This indicator identifies short opportunities on UB futures based on inverse correlation with 10Y Yield Futures. A macro trading tool to be used with additional confirmations."
🎯 Indicator Strategy
This tool generates sell signals for Ultra Bond (UB) futures when:
The Micro 10-Year Yield Future shows an upward spike (> adjustable threshold)
Trading volume is significant (false signal filter)
Inverse correlation is confirmed (UB falls when 10Y rises)
⚙️ Parameters
Spike Threshold: Sensitivity adjustment (e.g., 0.08% for swing trading)
Minimum Volume: Default 100 (optimized for Micro 10Y contracts)
📊 Recent Backtest
06/15/2024: +0.10% spike → UB dropped -0.3% within 15 minutes
06/18/2024: Valid signal post-CPI release
⚠️ Disclaimer
Analytical tool only – not financial advice
Must be combined with proper risk management
Open Interest Auto OverrideWhat does this “Open Interest Auto Override” Indicator
do?
Open Interest data is not supplied by every exchange to TradingView, however it is available on Binance Perpetual Futures. This script helps the crypto trader to identify the equivalent Binance Perpetual Futures Chart that has Open Interest Data available and automatically displays this on the traders chart.
How can a trader use this indicator?
This helps the trader to identify if there is Open Interest Data available in Binance and automatically displays it, making it easier to switch Coins whilst viewing the market.
What is Open Interest and how can I trade using this indicator?
Open Interest (OI) is the number of open futures contracts held by traders in active positions. The higher the value the Higher the number of open positions which indicates an increase in interest by traders in the asset.
If OI is increasing an equal number of longs and short positions are being opened.
If OI Decreases both longs and shorts are exiting the market.
If OI remains unchanged, no new contracts are entering or exiting, or an equal number of positions are being opened as there are being closed.
Open Interest can help traders by giving us a hint that a breakout may occur. If Open Interest is increasing whilst price is consolidating it may indicate that a breakout is imminent. If Open Interest is decreasing whilst price is consolidating it is likely that a false move in the form of a stop hunt may be issued prior to the actual breakout.
Usage of the Indicator:
By default the indicator will automatically use the Equivalent Binance Perpetual Chart for the Data
You can override the symbol manually if you what to view another exchanges data.
GG - LevelsThe GG Levels indicator is a tool designed for day trading U.S. equity futures. It highlights key levels intraday, overnight, intermediate-swing levels that are relevant for intraday futures trading.
Terminology
RTH (Regular Trading Hours): Represents the New York session from 09:30 to 17:00 EST.
ON Session (Overnight Session): Represents the trading activity from 17:00 to 09:29 EST.
IB (Initial Balance): The first hour of the New York session, from 09:30 to 10:30 EST.
Open: The opening price of the RTH session.
YH (Yesterday's High): The highest price during the RTH session of the previous day.
YL (Yesterday's Low): The lowest price during the RTH session of the previous day.
YC (Yesterday's Close): The daily bar close which for futures gets updated to settlement.
IBH (Initial Balance High): The highest price during the IB session.
IBL (Initial Balance Low): The lowest price during the IB session.
ONH (Overnight High): The highest price during the ON session.
ONL (Overnight Low): The lowest price during the ON session.
VWAP (Volume-Weighted Average Price): The volume-weighted average price that resets each day.
Why is RTH Important?
Tracking the RTH session is important because often times the overnight session can be filled with "lies". It is thought that because the overnight session is lower volume price can be pushed or "manipulated" to extremes that would not happen during higher volume times.
Why is the ON Session Important Then?
Just because the ON session can be thought as a "lie" doesn't mean it is relevant to know. For example, if price is stuck inside the ON range then you can think of the market as rotational or range-bound. If price is above the ON range then it can be thought of as bullish. If price is below the ON range then it can be thought as bearish.
What is IB?
IB or initial balance is the first hour of the New York Session. Typically the market sets the tone for the day in the first hour. This tone is similarly a map like the ON session. If we are above the IBH then it is bullish and likely a trend day to the upside. If we are below the IBL then it is bearish and likely a trend day to the downside. If we are in IB then we want to avoid conducting business in the middle of IBH and IBL to avoid getting chopped up in a range bound market.
These levels are not a holy grail
You should use this indicator as guide or map for context about the instrument you are trading. You need to combine your own technical analysis with this indicator. You want as much context confirming your trade thesis in order to enter a trade. Simply buying or selling because we are above or below a level is not recommended in any circumstance. If it were that easy I would not publish this indicator.
Adjustments
In the indicator settings you can adjust the RTH, ON, and IB session-time settings. All of the times entered must be in EST (Eastern Standard Time). You may want to do this to apply the levels to a foreign market.
Examples
PriceCatch-Intraday VolumeHi TV Community,
Greetings to you.
This is a script that may be of use to intra-day traders. Knowing how much volume is getting traded and in which direction can help with decision-making in trading - especially when trading Futures.
So, this script, displays volume, number of candles and trades on intra-day time-frames.
FUTURES CHART
NOTE: The instrument must contain volume information for this script to work.
Number of trades will be accurate on Futures Chart because Volume / lot-size will give number of trades on a specific time-interval. For cash chart, please ignore this value.
Please use this script on Intra-day time-frame only.
Hope this script may be of use to you. All the best.
Comments/queries welcome.
PriceCatch
PS: As always with trading you and you alone are responsible for your actions and the profits/losses resulting from your trading activity.
