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Бэктестинг

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Скоро: 66

Expectancy: the average outcome of a rule
From idea to tested rule
Backtest, paper trading and forward testing
Your first backtest, step by step
Reading a backtest report: metrics that matter
Equity curves and drawdowns: reading the shape
Slippage: the gap between plan and fill
Drawdowns: depth, duration and recovery math
Sample size: how many trades is enough?
Signals, orders and fills: three clocks
Bar replay: rehearse without hindsight
Costs, spreads and slippage in a backtest
Backtest sanity checklist
Overfitting in one picture
In-sample vs out-of-sample
Reading a Monte Carlo fan
Parameter sensitivity: plateaus vs peaks
Walk-forward analysis: testing as time passes
Stress-testing a rule
Benchmarks: choosing the right yardstick
Warm-up periods: why the first values are wrong
Settings and lookbacks: defaults are just defaults
Crypto venues: makers, takers and fee tiers
Sharpe, Sortino and Calmar, side by side
Statistical significance without the jargon
Why an LLM is not a backtest
Confidence intervals for strategy metrics
Recipe: a moving-average trend filter experiment
Recipe: an RSI mean-reversion experiment
Recipe: a channel breakout experiment
Recipe: a multi-timeframe filter experiment
One rule, three places: screen, chart, backtest
Turn a chart pattern into a testable rule
Look-ahead bias: the backtest that read tomorrow
Survivorship bias: the symbols that vanished
Data checks before any backtest
Benchmarks and null strategies: beat something simple
Fill assumptions: close, next open or intrabar?
Regime analysis: when did the rule work?
Backtest autopsy: five ways a great result was wrong
Overfitting simulator: the best of N random rules
Monte Carlo drawdown simulator
What walk-forward efficiency does and doesn't say
Backtest bias quiz: spot the flaw
Multiple testing: why many discoveries fail
The deflated Sharpe ratio, made intuitive
The look-ahead bug our engine refuses to run
Many strategies, one dataset: selection bias
Market impact: why size moves price
VWAP and TWAP as execution benchmarks
Stress scenarios: questions outside the sample
Test a pattern definition separately from outcomes
Cycles and seasonality: patterns in the calendar
Test Fibonacci confluence before believing it
Optimisation and its traps
Point-in-time fundamentals: filing dates matter
Monte Carlo simulation: what could have happened
Turnover budgets and cost-aware design
Price and fundamentals together, without mixing clocks
Capacity: how much a rule can trade
A backtesting protocol checklist
Ablation: prove which part of a rule matters
From screen results to a tested hypothesis
Signal decay: how fast does an edge fade?
Purged and nested validation
Reproducible research: logs, versions, seeds

Бэктестинг

Начинающий

What a backtest can prove, and what it can't