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Trading strategy validation glossary
Last reviewed: 16 September 2026·Tradelyze
35 pages on working out whether a backtested trading strategy is real or an artifact of the optimizer. They are ordered as a path, not an A–Z list: start at the top if backtesting is new to you, or jump to the section that matches the number you are stuck on.
Written for traders who already have a strategy and a TradingView backtest, and now need to work out whether the numbers mean anything. Every page answers the questions people actually search for, states where each threshold and figure came from, and says plainly when a widely repeated number has no primary source. Where the evidence is contested, the pages say so rather than picking a side.
Start here
What a backtest proves, how to check one, and what a validation run actually does.
- Backtesting What a backtest is, what it can and cannot show, and why it almost always looks better than live trading.
- How to validate a trading strategy Eight checks in order — from reproducing the backtest to forward testing — before you risk money or a challenge fee.
- How Tradelyze validates a strategy What Tradelyze does to a Pine Script strategy, how to read each results card, and what it does not check.
- Is your backtest too good to be true? Ten warning signs that a Strategy Tester result is inflated, and where on the report to spot each one.
- Backtest vs live trading Why results drop when real money is involved, which backtest assumptions break first, and where forward testing fits.
- What to do when a strategy fails validation What to change after a failed check, and why re-optimizing until it passes makes the overfitting worse.
What the numbers mean
The statistics every backtest report leads with, and what each one leaves out.
- Win rate and expectancy Why the share of winning trades says almost nothing on its own, and what average profit per trade adds.
- Profit factor Gross profit divided by gross loss: what counts as good, and why a high reading on few trades misleads.
- Maximum drawdown The largest peak-to-trough fall in equity, the gain needed to recover it, and how long drawdowns last.
- Sharpe ratio Return per unit of volatility: how to annualize it, what counts as good, and which Sharpe a report is showing.
- Losing streaks How long a losing run to expect at your win rate, and how to tell a normal streak from a broken strategy.
- Risk of ruin The chance of reaching a loss you cannot come back from, by classic formula and by Monte Carlo.
Testing on data the optimizer never saw
Where an optimized backtest stops being evidence, and what to run instead.
- In-sample vs out-of-sample Which part of your history the settings were tuned on, which part they were not, and why results drop on the second.
- Strategy optimization How searching many parameter settings and keeping the best is also how a backtest gets overfitted.
- Walk-forward analysis Repeated train-then-test windows: rolling versus anchored, what split to use, and how many windows a result needs.
- Walk-forward efficiency Out-of-sample return divided by in-sample return — how to calculate it, and what counts as a pass.
Statistical robustness
Separating a genuine edge from a result that happened to look good once.
- Monte Carlo simulation Replaying the same trades in many different orders to show how deep the drawdown could have been.
- Robustness score What a single 0–100 score is built from, and what folding several stress tests into one number hides.
- Overfitting and sample size How many trades a backtest needs before it supports any conclusion, and how to spot curve fitting.
TradingView specifics
Getting a trustworthy result out of the Strategy Tester, and out of your Pine Script.
- How to backtest on TradingView Running the Strategy Tester step by step: adding a strategy, setting properties and dates, reading the report.
- TradingView strategy report explained What each number in the Strategy Tester report means, and what it quietly assumes about your fills.
- TradingView strategy properties What commission, slippage, pyramiding and order size do to a backtest, and why a zero-cost run flatters itself.
- TradingView backtest accuracy Why a re-run backtest's trades differ from your TradingView export, and what a match rate is telling you.
- Pine Script repainting and look-ahead bias How a script can peek at future bars or recalculate on history, and how to test your own script for it.
- Exporting TradingView trades and price data The trade list, OHLCV data, chart timezone and extra timeframes a validation run needs from you.
Prop firm challenges
Turning a funding program's rules into things a backtest can actually check.
- How prop firm challenges work Phases, profit targets, loss limits and minimum trading days, in plain English.
- Prop firm rules and backtest metrics Which backtest numbers predict a breach of each challenge rule, and which rules a backtest cannot test.
- Daily loss limit How the daily cap is measured and when it resets, and which backtest statistic predicts a breach.
- Trailing drawdown How a loss floor that follows your account's peak differs from a static one, with worked examples.
- Prop firm consistency rule How the best-day cap is calculated, what happens if you exceed it, and how to check a backtest against it.
- Position sizing for prop firm challenges Turning a firm's loss limits into a contract count, using your backtest's worst day and Monte Carlo worst case.
- Custom prop firm rules Turning your own firm's published rules into a Tradelyze rule set, and what that check leaves out.
Reference
Definitions, short answers, and how these pages are written.
- Backtesting terms A to Z Short definitions of backtesting, optimization, prop firm and statistics terms, each linked to its full page.
- Backtesting and prop firm FAQ Eighty-seven short answers on sample size, overfitting, optimization, walk-forward testing, TradingView and prop firms.
- Editorial policy and methodology Who operates Tradelyze, how these pages choose sources, label unsourced numbers, date reviews and handle corrections.