Deeptest: TradingView Backtest Metrics and Robustness Analysis

Summary

Deeptest is a Pine library for analyzing TradingView strategy backtests. Its described outputs cover trade counts and returns, expectancy, risk-adjusted measures such as Sharpe and Sortino, drawdowns, trade duration, return distribution, risk of ruin, and comparisons with buy-and-hold benchmarks. It also defines structures for rolling-window statistics, drawdown and recovery records, and selected best and worst trades, then presents results in formatted tables and logs.

The library includes methods for Monte Carlo stress analysis and walk-forward evaluation, with outputs designed to compare in-sample and out-of-sample metrics. Configurable thresholds color selected statistics, and constants set defaults such as a risk-free rate and limits on analysis windows and iterations. This is an evaluation toolkit, not a trading strategy or evidence that any strategy works. Metrics depend on the underlying trades, assumptions, sample size, and implementation; the supplied document describes the library but provides no independent validation of its calculations or results.

Key ideas

• The library groups trade-level, risk-adjusted, drawdown, distribution, and benchmark metrics for strategy evaluation.
• Rolling statistics and drawdown records help describe performance variation and recovery behavior over time.
• Monte Carlo and walk-forward components are intended to stress-test results and compare in-sample with out-of-sample performance.
• Configurable thresholds and table rendering make selected statistics easier to inspect.
• The library reports evidence from a backtest but does not establish that a strategy will perform well in live trading.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.