Profit Factor Without Drawdown Duration Is Incomplete

Under adversarial review, fix the estimand as “investability incorporating time spent underwater, not merely gross profits divided by gross losses.” Do not substitute net profit, win rate, or a visually smooth curve for that target. Declare the horizon, account currency, included frictions, and operating-stop boundary before calculation. Any post-result change creates a new hypothesis and version, preventing the question from being selected after the answer is known.

Reconstruct the observation unit as “equity high-water-mark intervals and drawdown episodes” before treating rows as independent evidence. Report raw rows, parent trades, decisions, event clusters, and the denominator used for each average or standard error. Recompute maximum depth, longest underwater duration, Kaplan-Meier recovery survival, recovery hazard, and capital-lockup days under more than one defensible aggregation rule so that a larger export is not mistaken for a larger information set.

Preserve the hash of the TradingView export and the symbol, timeframe, session, timezone, order-processing settings, costs, account currency, and Pine version. For drawdown depth and underwater duration, longest recovery time, right-censored unrecovered episodes, capital lock-up, and investor abandonment risk directly affects reproducibility. Keep immutable source, normalized, and analysis layers separate, with every join, deletion, imputation, and conversion recorded in a transformation ledger.

The export identifies only what can be rebuilt from recorded time, price, quantity, and P&L. capital withdrawals, investor redemptions, margin calls, and mandate stop rules requires additional evidence. Mark each causal link as observed, bounded by assumption, or externally unverified. This prevents longest recovery time, right-censored unrecovered episodes, capital lock-up, and investor abandonment risk from being presented as a confirmed fact when the available data support only an interval or conditional conclusion.

Do not adopt the platform summary as ground truth. Independently convert each peak-to-recovery interval into a drawdown episode and retain the final unrecovered episode as right-censored rather than deleting it. Reconcile total and row-level differences by sign, date, symbol, and order type. If discrepancies concentrate in the exact state associated with drawdown depth and underwater duration, treat that concentration as a primary finding rather than dismissing it as rounding.

Report maximum depth, longest underwater duration, Kaplan-Meier recovery survival, recovery hazard, and capital-lockup days with intervals or resampling distributions, not point estimates alone. Match the uncertainty method to sample size, skewness, heavy tails, censoring, and selection history. If normal, quantile, and dependence-aware methods disagree on the sign, classify the edge as unidentified and show the minimum detectable effect and lower decision bound.

Do not narrow uncertainty with an IID shuffle alone. Resample time blocks that do not break drawdown episodes or regime persistence using several fixed block lengths and stationary bootstrap. Preserve random seed, repetition count, wrap rule, and missing-data treatment. For each block specification, report the distribution of maximum depth, longest underwater duration, Kaplan-Meier recovery survival, recovery hazard, and capital-lockup days, the rejection-side tail mass, and the rate at which the verdict changes sign.

Interrogate the mechanism “longest recovery time, right-censored unrecovered episodes, capital lock-up, and investor abandonment risk” with lower quantiles, expected shortfall, influence, cluster length, and boundary-hitting measures. Historical maximum loss is not a loss cap. Define several absorbing or operating boundaries—capital, margin, mandate drawdown, and recovery time—and record which boundary fails first under each stress.

A flat commission deduction is not an execution model for drawdown depth and underwater duration. Allocate spread, slippage, financing, borrow, roll, conversion, rounding, and rejected orders to the relevant unit. Recompute maximum depth, longest underwater duration, Kaplan-Meier recovery survival, recovery hazard, and capital-lockup days under base, upper-quantile, and crisis states while preserving the possibility that costs and losses worsen together.

Count the complete population of periods, symbols, timeframes, parameters, exits, filters, and metrics that were tried. Do not detach the attractive result for drawdown depth and underwater duration from rejected candidates, interim changes, or repeated validation reviews. Where appropriate, use PBO, SPA, and a Deflated Sharpe Ratio, and treat an unrecorded trial count as a material audit limitation.

Test whether drawdown depth and underwater duration is concentrated in one trend, volatility, liquidity, rate, or session state. Define regimes prospectively or on training data only. Report statewise maximum depth, longest underwater duration, Kaplan-Meier recovery survival, recovery hazard, and capital-lockup days, occupancy, transition probabilities, and costs, then reweight the mixture to adverse but realistic future compositions.

For the drawdown duration case, the same trade set can follow different capital paths under another inception date, order, initial balance, rounding rule, or stop condition. Separate fixed quantity, fixed R, and percentage sizing, then use circular shifts and block orderings to recompute drawdown, recovery, and boundary hits. Equal terminal P&L does not imply equal path risk.

Perturb “drawdown depth, duration, recovery hazard, and right-censored observations” one axis at a time before creating a joint sensitivity surface. Add the negative control “permute sequences with the same gross profit and gross loss to show that profit factor can remain fixed while recovery duration changes materially.” Predefine the grid and crisis rule so that neither the most favorable nor the most damaging cell is selected after inspection. Save the slope, curvature, and exact point where the decision boundary is crossed.

Have a second implementation convert each peak-to-recovery interval into a drawdown episode and retain the final unrecovered episode as right-censored rather than deleting it, then compare critical row-level outputs. Regression fixtures should include empty files, duplicate timestamps, extreme costs, reverse ordering, missing values, and boundary cases. Agreement between implementations is insufficient if they share the same bad input, so separate data construction and review roles where feasible.

Predeclare the decision rule. This case passes only if “the strategy meets both depth limits and predeclared recovery-probability and capital-lockup limits.” Near a boundary, disclose interval width and economic materiality rather than a binary badge. If only one favorable block length, cost state, or implementation passes, classify the result as assumption-sensitive rather than robust.

The evidence ledger must store the input hash, code version, settings, exclusions, “drawdown depth, duration, recovery hazard, and right-censored observations,” block lengths, random seed, repetition count, and every scenario output. Keep exploratory and confirmatory results in separate namespaces and retain failed trials. When new TradingView data arrive, create a new version and track underwater days, unrecovered episodes, recovery probability, and depth-duration area rather than overwriting the old result.

Translate statistical changes into capital consequences. A shift in expectancy, lower quantile, recovery time, or boundary risk caused by drawdown depth and underwater duration should be mapped to trade count, capital, margin, and continuation. A small per-trade difference can compound under high turnover, while a rare loss can be decisive near an absorbing boundary.

Separate hypothesis design, implementation, independent recalculation, and approval where practical. Stop automatically on material reconciliation error, unresolved missing data, non-reproducibility, or a predeclared threshold breach. Audit the chain “aggregate gains and losses → erase time → miss prolonged underwater periods → lock capital → inability to continue,” and monitor underwater days, unrecovered episodes, recovery probability, and depth-duration area prospectively without turning a historical pass into a promise of future profit.

The estimand “investability incorporating time spent underwater, not merely gross profits divided by gross losses” is identified only within the columns present in the TradingView export and the stated assumptions. If capital withdrawals, investor redemptions, margin calls, and mandate stop rules cannot be observed, report bounds rather than a false point estimate.

Past estimates of drawdown depth and underwater duration need not belong to the same population after changes in rules, participants, volatility, costs, or data specifications. Track underwater days, unrecovered episodes, recovery probability, and depth-duration area in rolling and regime-specific windows.

For recovery duration, repeatedly applying the same diagnostic battery and editing until it passes turns verification into another optimizer. Every post-audit change therefore creates a new model version and requires untouched evidence.

Even if the strategy meets both depth limits and predeclared recovery-probability and capital-lockup limits, the analysis does not establish tax, regulatory, behavioral, liquidity, order-size, or systems suitability. Separate statistical diagnosis from live-operating approval.

Deleting observations related to longest recovery time, right-censored unrecovered episodes, capital lock-up, and investor abandonment risk may improve the result. Compare no deletion, conservative imputation, and worst-case imputation, and display how maximum depth, longest underwater duration, Kaplan-Meier recovery survival, recovery hazard, and capital-lockup days changes.

Run the control “permute sequences with the same gross profit and gross loss to show that profit factor can remain fixed while recovery duration changes materially.” If the control performs similarly, suspect processing rules or common market drift before attributing performance to the strategy.

After a provisional pass, log underwater days, unrecovered episodes, recovery probability, and depth-duration area sequentially and stop on persistent departures from the predeclared predictive range. Diagnose implementation drift before reoptimizing history.

Multiple methods can agree because they share the same bad input or the same mechanism “longest recovery time, right-censored unrecovered episodes, capital lock-up, and investor abandonment risk.” Give lower-tail outcomes, failed scenarios, and unresolved mismatches the same visual prominence as favorable results; test count is not proof of correctness.