Backtesting and evidence
Study historical research without hiding bias, costs, data limits or uncertain results.
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Monte Carlo Trade Resampling: What the Simulation Can and Cannot Say
Compare shuffled trades with independent and block-bootstrap samples, reproduce a drawdown example, and see exactly what SuperQuant's diagnostic measures.
7 хвилина читання ↗02 / COMPARISON GUIDEBacktesting vs Paper Trading vs Forward Observation
Compare historical backtests, paper trading and prospective observation by the evidence each stage can provide—and the execution evidence each one still lacks.
7 хвилина читання ↗03 / COST WORKSHEETCrypto Backtest Costs: Include Fees, Spread, Slippage and Funding
Build a transparent crypto backtest cost model with separate fee, spread, slippage and funding assumptions, then test whether the conclusion survives higher costs.
9 хвилина читання ↗04 / METRICS GUIDECrypto Backtest Metrics: Sharpe, Sortino and Profit Factor
Calculate Sharpe, Sortino and profit factor from a small fictional sample, then read each beside drawdown, trade count, costs and the test process.
6 хвилина читання ↗05 / METHOD GUIDECrypto Backtest Overfitting: Why the Best Result Can Mislead
Understand how repeated strategy searches fit historical noise, then reduce avoidable overfitting with preregistered rules, chronological tests and honest reporting.
7 хвилина читання ↗06 / PRACTICAL CHECKLISTCrypto Backtesting Data Quality: Check Gaps, Timestamps and Provenance
A practical audit for crypto backtest data: verify the market and time basis, find missing or duplicate candles, align funding and signals, and preserve a reproducible source record.
7 хвилина читання ↗07 / STEP-BY-STEP GUIDECrypto Walk-Forward Testing: Repeated Windows, Changing Rules
Plan sequential crypto training and test windows, predeclare any update schedule, compare every evaluation window, and distinguish walk-forward analysis from one reserved holdout.
7 хвилина читання ↗08 / QUANT TUTORIALBacktesting Perp Strategies: Handling Historical Funding Rates and Open Interest
Avoid common backtest pitfalls: aligning 1-hour and 8-hour funding payments, handling lookahead bias in open interest snapshots, and simulating liquidation slippage.
5 хвилина читання ↗09 / STEP-BY-STEP WORKFLOWHow to Backtest a Crypto Trading Strategy: A Research Workflow
Learn how to backtest a crypto strategy with checked candle data, causal entries, realistic costs, chronological tests and a record of what the result can prove.
8 хвилина читання ↗10 / EVALUATION GUIDEWhale Scorecards: Hit Rates, Survivorship and Why a Ranked List Flatters Itself
How a top-trader scorecard is built from detected entries, what a 24-hour hit rate measures, and why ranking by recent profit can make past results look stronger than what follows.
7 хвилина читання ↗11 / FIELD GUIDEHyperliquid Whale Tracking: What Public Positions Can and Cannot Tell You
Hyperliquid exposes positions by address. Learn what a whale tracker can read from that record, how a top-trader list is chosen, and which conclusions the data cannot support.
8 хвилина читання ↗12 / TIMING GUIDELook-Ahead Bias in Backtesting: Check What Was Knowable
Find look-ahead bias by tracing signal timestamps, candle completion and order timing; separate information available at the decision from later outcomes.
7 хвилина читання ↗13 / RESEARCH CHECKLISTOn-Chain Data in Crypto Trading Research: What Wallet Activity Can and Cannot Prove
Use wallet flows, holder lists and address labels in crypto research without mistaking attribution for identity or applying today's labels to yesterday's data.
7 хвилина читання ↗14 / METHOD GUIDEOut-of-Sample Crypto Testing: Freeze One Rule before the Holdout
Reserve one later crypto data segment before tuning, freeze preprocessing and costs, evaluate once, and retire the holdout if its result changes your crypto research.
7 хвилина читання ↗15 / FIELD GUIDEVerifiable Crypto TA: SHA-256 Pre-Trade Receipts, Out-of-Sample Grading, and Zero Hindsight
Learn why cryptocurrency technical analysis requires cryptographic SHA-256 pre-trade receipts, how out-of-sample grading prevents hindsight bias, and how to verify setups.
5 хвилина читання ↗