Blog
Articles, guides and insights on algorithmic trading, backtesting strategies, quantitative analysis, and data quality.
1–9 of 42 articles

Forex 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.

Multi 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.

Transaction 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.

Six Bar Aggregation Methods Quants Can Calibrate for ML Backtests
Compare six bar aggregation methods for backtesting and machine learning, then calibrate thresholds and validate results with clean intraday data.

Spread Modeling for Backtests: 3 Estimators to Stress Test ML Edge
Compare Roll, Corwin Schultz, and CHL spread estimates; model slippage and impact, then validate ML backtests with walk forward tests and clean minute bars.

MT4 History Center: 5 Safe Fixes Before File Repair
Fix MT4 History Center errors with safe refresh and download steps, .hst file repair, and clean data imports for more reliable, reproducible backtests.

When 1 Minute vs 5 Minute Bars Mislead Quants, Run a Signature Plot
Decide whether 1 minute or 5 minute bars suit your backtest. Follow a research-backed checklist: signature plot, walk forward validation, realistic...

MT4 Max Bars for Quants: Fix Broken Backtests with Clean Import Data
Understand how MT4’s chart and history limits work. Change Max bars, troubleshoot missing data, and import clean datasets to produce reproducible backtests.

Prevent Broken Backtests: Intraday Data Sources Practitioners Must Audit
Intraday data source checklist for practitioners: verify timestamp provenance, bar labels, and spike detection. Test a sample first.