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Articles, guides et analyses sur le trading algorithmique, les stratégies de backtesting, l'analyse quantitative et la qualité des données.
1–9 of 48 articles
ENParquet vs CSV: Which Format Fits Your Data in 2026
Parquet vs CSV compared on file size, speed, schema, compatibility and backtesting. Learn when each format wins and how to set up Parquet files properly.
ENOut-of-Sample Testing: How to Validate a Trading Strategy
Out-of-sample testing explained for traders: how to split data, how much to hold out, why one holdout fails, and how walk-forward testing fixes it.
ENMonte Carlo Backtesting: How to Stress-Test a Strategy
Monte Carlo backtesting shows whether your strategy's edge is real or just one lucky path. Learn the methods, the pitfalls and the data it depends on.
ENContinuous Futures Data: How to Build and Use It
Continuous futures data explained for backtesting: roll rules, ratio vs. difference back-adjustment, raw vs. adjusted series, and how to check your data.
ENLook Ahead Bias for Quants: Catch Leaks Before Backtest Sign Off
Spot look ahead bias in backtests by checking timestamps, preprocessing, and revised data, then prevent leaks with rolling buffers and an audit checklist.
ENResampling Minute Data in pandas: Catch Thin Buckets Before Backtests
Use pandas to resample minute OHLCV data with aligned buckets, bar_count checks, and logical fills so your backtests use cleaner, reproducible bars.
ENForex Timeframes: Why Minute Charts Need Cleaner Backtest Data
Choose forex chart timeframes by holding period, screen time, and strategy. Learn why minute charts magnify noise and demand clean data for backtesting.
ENMulti Symbol Backtesting: Test 2 Symbols, Then Check Engine Costs
Build safer backtests across multiple symbols with isolated state, synchronized minute bars, and cross engine cost checks that expose false edges.
ENTransaction Costs for Quants: Test 3 Regimes, Watch Engine Risk
Learn how quants can model commissions, spreads, slippage, and market impact, stress test three cost regimes, and account for engine and data risks.