Test on point-in-time data, with disclosed costs

Backtests run on the Trigr engine over point-in-time market data: every feature is computed only from information available at the bar's close. The result includes equity, monthly returns, trade-level detail, and an audit trail. Trading and builder fees are applied. Optional flat slippage and perpetual funding default off, so the initial result is gross before those two costs and is not a forecast of live execution.

Execution frictions

Trading and builder fees are included in every run. Slippage and funding are separate, opt-in assumptions. When enabled, each appears as a line item with a before/after delta.

Flat slippage

When enabled, the engine applies the positive basis-point value you enter as an adverse adjustment to every entry and exit fill. A missing or zero value is rejected rather than silently enabling a zero-cost model.

• Modeled: your flat bps-per-fill assumption, applied in the unfavorable direction.
• Not modeled: live spread or order-book depth, volume participation, market impact, latency, or volatility-dependent slippage.

There is no automatic house slippage estimate or liquidity-tier price adjustment. Choose a flat assumption that fits the market and order size you are researching.

Funding

When enabled for a perpetual, funding accrues at each ~8h settlement while a position is held and is signed by side. Leave the rate blank to use the service's point-in-time source-venue funding series, or enter your own flat %/8h assumption. Non-perp markets carry no perp funding. Source-venue history is not a quote for the rate another venue would have charged.

Intrabar handling

• Replay, then stop-loss first.If TP and SL both fall inside one bar on a timeframe coarser than 5 minutes, the engine replays that bar on 5-minute candles to find which level was hit first. On 5-minute strategies, when a 5-minute candle is itself ambiguous, or when finer data cannot be loaded within the run's time budget, the SL resolves first (the conservative outcome).
• No fabrication.If a required input is missing for a bar, the engine doesn't invent a value; the signal stays pending rather than firing on guessed data.

Reading the results: DSR, not raw Sharpe

A strategy that's been tuned can post a flattering Sharpe by luck. That is why Trigr measures the Deflated Sharpe Ratio (DSR) and PBO. Both come from an Optimize with ML run; a standard backtest shows them as not yet computed and scores robustness conservatively off the raw Sharpe until you run one:

• Deflated Sharpe Ratio: discounts the Sharpe for the number of trials and the sample size, so it reflects how likely the edge is real rather than a product of search.
• PBO (Probability of Backtest Overfitting): a separate CPCV-grid diagnostic for how often in-sample choices underperform out-of-sample. That grid does not select the saved ML model or its parameters.

Raw Sharpe is still shown, but demoted. DSR and diagnostic PBO add robustness evidence; neither guarantees a live edge.

Recent-period diagnostics are not a frozen holdout

Studio shades the trailing 25% of a normal full-history backtest and compares it with the earlier curve. That is useful for spotting recent degradation, but it becomes part of the research data as soon as you inspect it while choosing or tuning a strategy. Do not describe it as a final out-of-sample test.

An honest final check reserves a later period before research, freezes one winner and all cost assumptions, then evaluates only that unchanged winner on the untouched period. If it fails, do not tune against the same holdout or substitute a runner-up. Normal strategy backtests currently use full available coverage and do not accept arbitrary general date windows, so use explicit anchored, purged walk-forward OOS from ML optimization where applicable or collect new paper-forward data after freezing the winner.

Data coverage

Beta strategy authoring and backtests currently cover 43 certified crypto markets. The broader 53-asset research catalog also lists stocks, indices, commodities, and markets whose history or execution certification is still coming soon. The capability catalog labels the status of every asset explicitly.