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Methodology — Overview

This section documents exactly how every number in the API is produced. It is written to be checked against the data: the formulas and conventions below are the ones the exporter and the API actually run, including their limitations.

:::warning Factual historical data — not advice Every figure is backtested / modelled historical performance computed from public market data. Past performance is not indicative of future results. This is factual historical data for professional / institutional use under a global license — not investment advice, not a recommendation, not a forecast, and not an offer. :::

What the dataset is

  • 14 strategies, all trading BTC-PERPETUAL on Deribit — an inverse, BTC-settled contract (PnL and balances accrue in BTC; see Provenance).
  • Backtest window: indicators warm up from 2018-08-14; the published series run to the dataset's generation date (currently 2026-06-24) — about 7.8 years, ~2,871 daily return points per strategy.
  • Source: public Deribit chart history (candles). The exporter is keyless — it authenticates to nothing and reads no credentials.
  • Deliberately diverse: the strategies are built on different, largely independent return drivers — the source of the book's low cross-correlation.
  • Each strategy is sized per-strategy at its own base risk % (book_size = 1) — this is a single-strategy backtest, independent of any live portfolio allocation.

How a figure is produced

For each strategy the exporter re-runs the engine's keyless DRY_RUN backtest bar-by-bar over the public candles, producing a mark-to-market equity curve. Everything else is derived from that curve and the trade list:

  • Returns — last equity per UTC day / ISO week, then period-over-period % change (Metrics).
  • Stats — CAGR, max drawdown, Sharpe, Sortino, time-underwater, win rate, profit factor (Metrics).
  • Correlation — Pearson on the aligned return series across strategies (Correlation).
  • Costs (commission + slippage) are applied inside the backtest, so all figures are net of them (Fees & Slippage).

Verification states

verification_state is our internal validation depth — how many independent ways we confirmed a strategy's numbers in-house:

StateCountMeaning
dual_verified12Results confirmed two independent ways inside our pipeline — two implementations agree within tolerance.
engine_backtested2Validated by the engine's keyless backtest (a single method).

Both are real backtests over the same public candles and the same cost model. This is a separate axis from tv_status, which tracks the external TradingView cross-check (all strategies are currently provisional). The two are complementary, not contradictory — both are published on every strategy and are explained in full at Verification & data confidence.