PulseGrid Universal Scalper - Adaptive Pulse and Symmetric Spans

Instrument agnostic. Works on any symbol and timeframe supported by TradingView.
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Purpose and scope

PulseGrid is a short timeframe strategy designed to read intrabar structure and recent path so that entries align with actionable momentum and context. The strategy is private. The description below provides all the information needed to understand how it behaves, how it sizes risk, how to tune it responsibly, and how to evaluate results without making unrealistic claims. The design is instrument agnostic. It runs on any asset class that prints open high low close bars on TradingView. That includes commodities such as Gold and WTI, currencies, crypto, equity indices, and single stocks. Performance will always depend on the symbol’s liquidity, spread, slippage, and session structure, which is why the description focuses on principles and safe parameter ranges instead of hard promises.

What the strategy does at a glance

It builds a composite entry signal named Pulse from five normalized bar features that reflect short term pressure and follow through.

It applies regime guards that keep the strategy inactive when the tape is either too quiet, too bursty, or too directionally random.

It optionally uses a directional filter where a fast and a slow exponential average must agree and their gap must be material relative to recent true range.

When a signal is allowed, risk is sized using symmetric spans that come from nearby untraded price distances above and below the market. The strategy sets a single stop and a single take profit from those spans.

Lines for entry, stop, and take profit are drawn on the chart. A compact on chart table shows trade counts, win rate, average R per trade, and profit factor for all trades, longs only, and shorts only.

This combination yields entries that are reactive but not chaotic, and risk lines that respect the market’s recent path instead of generic pip or point targets.

Why the design is original and useful

The core originality is the union of a composite entry that adapts to volatility and a geometry based risk model. The entry uses five different viewpoints on the same bar space instead of relying on a single technical indicator. The risk model uses spans that come from actual untraded distance rather than fixed multipliers of a generic volatility measure. The result is a framework that is simple to read on a chart and simple to evaluate, yet it avoids the traps of curve fitting to one symbol or one month of data. Because everything is normalized locally, the same logic translates across asset classes with only modest tuning.

The Pulse composite in detail

Pulse is a weighted blend of the following normalized features.

Impulse imbalance. The script sums upward and downward impulses over a short window. An upward impulse is the extension of highs relative to the prior bar. A downward impulse is the extension of lows relative to the prior bar. The net imbalance, scaled by the local range, captures whether extension pressure is building or fading.

Wick and close location. Inside each bar, the distance between the close and the extremes carries information about rejection or acceptance. A bar that closes near the high with relatively heavier lower wick suggests upward acceptance. A bar that closes near the low with heavier upper wick suggests downward acceptance. A weight controls the contribution of wick skew versus close location so that users can favor reversal or momentum behaviour.

Shock touches. Within the recent range window, touches that occur very near the top decile or bottom decile are marked. A short sliding window counts recent shocks. Frequent top shocks in a rising context suggest supply tests. Frequent bottom shocks in a declining context suggest demand tests. The count is normalized by window length.

Breakout ledger. The script compares current extremes to lagged extremes and keeps a simple count of recent upside and downside breakouts. The difference behaves as a short term polarity meter.

Curvature. A simple second difference in closing price acts as a curvature term. It is normalized by the recent maximum of absolute one bar returns so that the value remains bounded and comparable to other terms.

Pulse is smoothed over a fraction of the main signal length. Smoothing removes impulse spikes without destroying the quick reaction that scalpers need. The absolute value of smoothed Pulse can be used with an adaptive gate so that only the top percentile of energy for the recent environment is eligible for entries. A small floor prevents accidental entries during very quiet periods.

Regime guards that keep the strategy selective

Three guards must all pass before any entry can occur.

Auction Balance Factor. This is the proportion of closes that land inside a mid band of the prior bar’s high to low range. High values indicate balanced chop where breakouts tend to fail. Low values indicate directional conditions. The strategy requires ABF to sit below a user chosen maximum.

Dispersion via a Gini style measure on absolute returns. Very low dispersion means bars are small and uniform. Very high dispersion means a few outsized bars dominate and slippage risk can be elevated. The strategy allows the user to require the dispersion measure to remain inside a band that reflects healthy activity.

Binary entropy of direction. Over the core window, the proportion of up closes is used to compute a simple entropy. Values near one indicate coin flip behaviour. Values near zero indicate one sided sequences. The guard requires entropy below a ceiling so that random directionality does not produce noise entries.

An optional directional filter asks that a fast and a slow exponential average agree on direction and that their gap, when divided by an average true range, exceed a threshold. This filter can be enabled on symbols that trend cleanly and disabled when the composite entry is already selective enough.

Risk sizing with symmetric spans

Instead of fixed points or a pure ATR multiplier, the strategy sizes stops and targets from a pair of spans. The upward span reflects recent untraded distance above the market. The downward span reflects recent untraded distance below the market. Each span is floored by a fallback that comes from the maximum of a short simple range average and a standard average true range. A tick based floor prevents microscopic stops on instruments with high tick precision. An asymmetry cap prevents one span from becoming many times larger than the other. For long entries the stop is a multiple of the downward span and the target is a multiple of the upward span. For short entries the stop is a multiple of the upward span and the target is a multiple of the downward span. This creates a risk box that is symmetric by construction yet adaptive to recent voids and gaps.

Execution, ties, and housekeeping

Entries evaluate at bar close. Exits are tested from the next bar forward. If both stop and target are hit within the same bar, the outcome can be resolved in a consistent way that favors the stop or the target according to a single user setting. A short cooldown in bars prevents flip flops. Users can restrict entries to specific sessions such as London and New York. The chart renders entry, stop, and target lines for each trade so that every action is visible. The table in the top right shows trade counts, take profit and stop counts, win rate, average R per trade, and profit factor for the whole set and by direction.

Defaults and responsible backtesting

The default properties in the script use a realistic initial capital and commission value. Users should also set slippage in the strategy properties to reflect their broker and symbol. Small timeframe trading is sensitive to friction and the strategy description does not claim immunity to that reality. The strategy is intended to be tested on a dataset that produces a meaningful sample of trades. A sample in the range of a hundred trades or more is preferred because variance in short samples can be large. On thin symbols or periods with little regular trading, users should either change timeframe, change sessions, or use more selective thresholds so that the sample contains only liquid scenarios.

Universal usage across markets

The strategy is universal by design. It will run and produce lines on any open high low close series on TradingView. The composite entry is made of normalized parts. The regime guards use proportions and bounded measures. The spans use untraded distance and range floors measured in the local price scale. This allows the same logic to function on a currency pair, a commodity, an index future, a stock, or a crypto pair. What changes is calibration.

A safe approach for universal use is as follows.

Start with the default signal length and wick weight.

If the chart prints many weak signals, enable the directional filter and raise the normalized gap threshold slightly.

If the chart is too quiet, lower the adaptive percentile or, with adaptive off, lower the fixed pulse threshold by a small amount.

If stops are too tight in quiet regimes, raise the fallback span multiplier or raise the minimum tick floor in ticks.

If you observe long one sided days, lower the maximum entropy slightly so that entries only occur when directionality is genuine rather than alternating.

Because the logic is bounded and local, these simple steps carry over across symbols. That is why the strategy can be used literally on any asset that you can load on a TradingView chart. The code does not depend on a specific tick size or a specific exchange calendar. It will still remain true that symbols with higher spread or fewer regular trading hours demand stricter thresholds and larger floors.

Suggested parameter ranges for common cases

These ranges are guidelines for one to five minute bars. They are not promises of performance. They reflect the balance between having enough signals to learn from and keeping noise controlled.

Signal length between 18 and 34 for liquid commodities and large capitalization equities.

Wick weight between 0.30 and 0.50 depending on whether you want reversal recognition or close momentum.

Adaptive gate percentile between 85 and 93 when adaptive is enabled. Fixed threshold between 0.10 and 0.18 when adaptive is disabled. Use a non zero floor so very quiet periods still require some energy.

Auction Balance Factor maximum near 0.70 for symbols with clear session bursts. Slightly higher if you prefer to include more balanced prints.

Dispersion band with a lower bound near 0.18 and an upper bound near 0.68 for most session instruments. Tighten the band if you want to skip very bursty days or very flat days.

Entropy maximum near 0.90 so coin flip phases are filtered. Lower the ceiling slightly if the symbol whipsaws frequently.

Stop multiplier near one and take profit multiplier between two and three for a single target approach. Larger target multipliers reduce hit rate and lengthen holding time.

These are safe starting points across commodities, currencies, indices, equities, and crypto. From there, small increments are preferred over dramatic changes.

How to evaluate responsibly

A clean chart and a direct test process help avoid confusion. Use standard candles for signals and exits. If you use a non standard chart type such as Heikin Ashi or Renko, do so only for visualization and not for the strategy’s signal computation, as those chart types can produce unrealistic fills. Turn off other indicators on the published chart unless they are needed to demonstrate a specific property of this strategy. When you post results or discuss outcomes, include the symbol, timeframe, commission and slippage settings, and the session settings used. This makes the context clear and avoids misleading readers.

When you look at results, consider the following.

The distribution of R per trade. A positive average R with a moderate profit factor suggests that exits are sized appropriately for the symbol.

The balance between long and short sides. The HUD table separates the two so you can see if one side carries the edge for that symbol.

The sensitivity to the tie preference. If many bars hit both stop and take profit, the market is chopping inside the risk box and you may need larger floors or stricter regime guards.

The session effect. Session hours matter for many instruments. Align your session filter with where liquidity and volatility concentrate.

Known limitations and honest warnings

PulseGrid is not a guarantee of future profit. It is a systematic way to read short term structure and to size risk in a way that reflects recent path. It assumes that the data feed reflects the exchange reality. It assumes that slippage and spread are non zero and uses explicit commission and user provided slippage to approximate that. It does not place multiple targets. It does not trail stops. It is not a high frequency system and does not attempt to model queue priority or microsecond fills. On illiquid symbols or very short timeframes outside regular hours, signals will be less reliable. Users are responsible for choosing realistic settings and for evaluating whether the symbol’s conditions are suitable.

First use checklist

Load the symbol and timeframe you care about.

If the instrument has clear sessions, turn on the session filter and select realistic London and New York hours or other sessions relevant to the instrument.

Set commission and slippage in the strategy properties to values that match your broker or exchange.

Run the strategy with defaults. Look at the HUD summary and the lines.

Decide whether to enable the directional filter. If you see frequent reversals around the entry line, enable it and raise the normalized gap threshold slightly.

Adjust the adaptive gate. If the chart floods, raise the percentile. If the chart starves, lower it or use a slightly lower fixed threshold.

Adjust the fallback span multiplier and tick floor so that stops are never microscopic.

Review per session performance. If one session underperforms, restrict entries to the better one.

This simple process takes minutes and transfers to any other symbol.

Why this script is private

The source remains private so that the underlying method and its implementation details are not copied or republished. The description here is complete and self contained so that users can understand the purpose, originality, usage, and limitations without needing to inspect the source. Privacy does not change the strategy’s on chart behavior. It only protects the specific coding details.

Guarantee and compliance statements

This description does not contain advertising, solicitations, links, or contact information. It does not make performance promises. It explains how the script is original and how it works. It also warns about limitations and the need for realistic assumptions. The strategy is not investment advice and is not created only for qualified investors. It can be tested and used for educational and research purposes. Users should read TradingView’s documentation on script properties and backtesting. Users should avoid non standard chart types for signal computation because those produce unrealistic results. Users should select realistic account sizes and friction settings. Users should not post claims without showing the settings used.

Closing summary

PulseGrid is a compact framework for short timeframe trading that combines a composite entry built from multiple normalized bar features with a symmetric span model for risk. The entry adapts to volatility. The regime guards keep the strategy inactive when the tape is either too quiet or too erratic. The risk geometry respects recent untraded spans instead of arbitrary distances. The entire design is instrument agnostic. It will run on any symbol that TradingView supports and it will behave consistently across asset classes with modest tuning. Use it with a clean chart, realistic friction, and enough trades to make your evaluation meaningful. Use sessions if the instrument concentrates activity in specific hours. Adjust one control at a time and prefer small increments. The goal is not to find a magic parameter. The goal is to maintain a stable rule set that reads market structure in a way you can trust and audit.