How TradingPal Builds Its Historical Trading Records

From an Eligible Trade to an Account Result

Imagine ten setups reach their entry prices on the same day, but an account has room for only two. Counting all ten tells you how the setups performed. The account’s return depends on the two positions it actually took, their size and when their capital became available again.

TradingPal uses separate calculations for those questions. The historical engines below supply the trade records and account simulations. Paper and live measurement then compare those assumptions with actual fills.

• Support and resistance: tests the named Buy at Support and Short at Resistance rules on weekly and monthly charts.
• Chart patterns: tests wedges, pennants and triangles with defined entries, safety exits and final exits.
• Autopilot: replays eligible pattern trades through one account with position and cash limits.
• Paper and live accounts: record actual positions, fills, costs and outcomes for comparison with the simulations.

Checks on the Historical Decisions

Each stage needs a rule that can be applied consistently. The introductory backtesting guide explains how hindsight and repeated tuning can distort a result; these are the checks used here.

• Information timing: simulated decisions use information available at that point. Later pattern confirmation can still affect which trades enter the published sample, as explained in the pattern section.
• Possible fills: an entry must fall within the candle’s traded range. A gap past the trigger uses the worse opening price.
• Fixed trade rules: the entry, safety exit, target and trailing rule stay fixed within a test. Research variants are evaluated as separate rules.
• Recorded exclusions: impossible fills, duplicate positions and capacity skips have explicit reasons.
• Separate samples: trade statistics describe qualifying resolved setups; account statistics describe the positions the limited account could hold.
• Reserved-data evaluation: research under a fixed protocol checks rules on stocks or periods held apart from development. That procedure is distinct from chronological replay and does not apply to every published statistic.

Support and Resistance Setup Records

The support-and-resistance record belongs to the complete named setups. It includes the line, surrounding price context, entry, safety exit and target. Results for these rules cannot be assigned to every nearby line on a chart.

At each historical decision date, the calculation reconstructs the automatic lines for that window and checks whether the full setup qualifies. A weekly setup and a monthly setup use their respective chart intervals.

For filters evaluated on reserved data, candidate rules are specified before testing them on separate stocks or periods. The support and resistance guide introduces the chart concepts used in the trade rules.

• Chart reconstruction: use the historical window available for the decision.
• Setup qualification: check the complete support or resistance rule.
• Entry and exit: use the defined entry region and safety-exit conditions for that interval. Stops are close-confirmed; the weekly book requires two qualifying closes.
• Completed record: retain entry, safety exit, target, final exit, holding time and result in R.
• Account simulation: replay those trades with the same capital limits used for setup-card accounts.

Chart-Pattern Trade Records

A pattern trade begins only after the shape could be established on an earlier daily candle. The simulation then checks whether a later candle reaches the entry trigger beyond the boundary. This prevents a shape first identified after a move from receiving an entry at the start of that move.

Later confirmation is a separate limitation. The detector can use prices after the initial crossing to reject immediate failures, so the published sample contains patterns that ultimately passed those checks. It does not establish that each confirmed pattern was already known at the first crossing.

• Entry: use the first eligible reach of the trigger, with a worse opening fill if price gaps through it.
• Range check: reject a planned fill outside the candle’s range or an entry already beyond the target.
• Two exits in one candle: follow the engine’s specified ordering when a daily candle could contain both target and stop events. Daily prices cannot reveal the full intraday sequence.
• Exit policy: fix the structural safety exit at entry. Some bullish patterns switch to a 10-day moving-average exit after reaching the measured-move target.
• Duplicates: remove overlapping same-symbol, same-direction trades from ranking statistics; the account holds at most one position per symbol.

The Account Behind a Setup-Card Return

Setup-card accounts use the most recent 20-year window. They report the completed setup statistics separately from the return of positions the account could take. In the ten-signal example, all eligible completed signals contribute to the relevant trade statistics, while available cash and positions determine the account’s holdings.

Planned risk is measured from entry to the safety exit. The R-multiple guide shows how that distance determines position size.

• Plan about 1% of current equity at risk per trade before caps reduce the size.
• Hold at most 16 positions, with one per symbol.
• Commit at most 20% of equity to one name.
• Limit total entry notional to 95% of equity, leaving roughly 5% uncommitted and using no leverage.
• Record signals skipped because of the account limits.

The Autopilot Portfolio Simulation

Autopilot starts with stored historical pattern trades and moves through the calendar. It must choose among eligible signals while respecting available cash and a 16-position limit. Capital becomes available again when a position closes.

Candidate rankings use trades completed before the decision date, blending a stock’s own history with its pattern-family history. The displayed ranking does not establish the order in which prices reach their triggers. Daily data cannot identify the exact order of same-day crossings, so the account tests multiple allocation orders as described below.

The live selector also limits a position to 1% of the stock’s median dollar volume. The current public simulation does not model that additional liquidity cap, which can create differences in accepted trades and position size.

• Position risk: 0.65% of current equity, sized from the breakout price before the modeled fill adjustment. Setup cards use about 1%.
• Position limits: up to 16 open positions and one per symbol, with no daily or per-family entry cap.
• Capital: at most 20% in one name and 95% gross exposure, with sufficient cash and no leverage.
• Tradability: minimum $5 share price, $2 million in 20-day median dollar volume and a stop width of at least 0.3%.
• Eligibility: only the pattern families and market-side conditions allowed by the configured policy.

Why the Headline Is the Median of 25 Runs

Return to the ten signals competing for two positions. Daily prices tell us which triggers were reached, but may not tell us which was reached first. Taking different pairs can change later cash availability and years of compounded returns.

TradingPal runs 25 reproducible allocation paths using different same-day orderings. Each uses the same historical market prices. The spread shows how sensitive the result is to those allocation choices.

The headline comes from one representative run. These repeated allocations test sensitivity within the existing sample; testing on reserved stocks or periods is a separate procedure.

• Setup cards: select the actual run with the median ending account value.
• Autopilot: select the actual run with the median CAGR.
• Associated statistics: take return, drawdown, Sharpe, capacity measures and the equity curve from that same run.
• Path spread: retain card return quartiles and Autopilot’s 10th-to-90th-percentile CAGR range.

Which Costs Each Record Includes

Execution costs differ across the published records. Check the cost basis before comparing their returns.

Limits on price, liquidity and position size restrict the simulated trades, but they do not account for every expense or fill difference. Paper and live records provide a separate check on actual execution.

• Setup cards: pattern and support-and-resistance records are before brokerage friction.
• Leading public Autopilot record: worsen each entry by 25 basis points, or 0.25%, and convert a deterministic 5% of entries to synthetic −0.25R failed-entry outcomes. The headline uses the median of 25 allocation paths under those assumptions.
• Omitted costs: the published Autopilot simulation does not separately charge commissions, exit slippage, short-borrow fees, taxes or nonlinear market impact. The entry adjustment and failed-entry allowance are modeled assumptions.

Read the Outputs in Groups

Start with trade results, then account growth and losses, and finally the amount of supporting data. The metrics guide provides worked examples. The available fields vary by surface.

• Trades: win rate, profit factor, average and median R, average gain and loss, payoff ratio and dollar expectancy.
• Growth: cumulative return and CAGR, the annual rate connecting the starting and ending values.
• Losses: maximum drawdown on the reported path, resampled drawdown percentiles and the proportion of resampled paths falling below half the starting account.
• Risk-adjusted return: monthly-return Sharpe using a 0% risk-free rate and Probabilistic Sharpe; Autopilot also reports Deflated Sharpe, Sortino and Calmar.
• Activity and sample: trade and symbol counts, holding time, time in market, peak positions, skipped signals, test dates and allocation-path ranges.
• Contributions: monthly results and the contributions of different years and pattern families.
• Execution: actual account returns, exposure, entry slippage and differences between live and modeled signals and outcomes.

Compare Simulated Trades with Actual Execution

The paper and live measurement layer matches real signals to the production pattern model. It compares the prices and results an account received with the simulated trade for the same setup.

A persistent difference in fill costs or trade outcomes can change the expected result. Small samples remain uncertain, so the reports include sample warnings as well as measures of divergence.

• Entry slippage: the difference between actual and modeled entry, measured in basis points. One basis point is one-hundredth of a percentage point.
• Signal matching: identify real signals without matching backtest trades, called “ghosts,” and new backtest signals the live process missed.
• Outcome difference: compare actual and modeled R for the same setup.
• Recent performance: compare rolling live R with modeled expected R, including sample-size flags.
• Risk response: drawdown and divergence checks contribute to reported risk states and can reduce the trading mode.

When the Published Records Update

Pattern and support-and-resistance records update through the nightly process. The table below shows the latest completed published pattern result.

The public Autopilot record is rebuilt after strategy-affecting changes. Opening a page reads the published record; it does not run a new simulation.

Where the Simulation Can Differ from a Real Account

The ten-signal example shows why a collection of attractive trades may produce a different account result. Limited capital and uncertain entry ordering explain part of that gap. The assumptions below account for other differences that remain.

Use these limits when deciding what the record can support. A historical gain describes the stated rules and data; changes in markets, execution or the available stock universe can produce a different result.

• Surviving stocks: the store does not include every failed or delisted company, so the historical universe may be optimistic.
• Later confirmation: the sample includes patterns confirmed after the initial crossing. That limits claims about alerts available at the first crossing.
• Open positions: Autopilot’s historical replay holds open positions at entry value until settlement, so its drawdown can omit deeper losses inside a trade. Live account metrics mark the account daily.
• Compressed prices: daily, weekly and monthly candles hide the sequence of prices inside the interval.
• Incomplete costs: the modeled entry adjustment and failed-entry allowance omit several real expenses and execution effects.
• Changing markets: a rule’s past behavior may weaken under different conditions.
• Different periods: the leading Autopilot record begins in 2016; the since-2000 series is a separate long-history stress exhibit.

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