Kwiz Quants Blog

Research and engineering insights on systematic forex trading: strategy validation, backtesting methodology, MT5 automation, position sizing, and the production infrastructure behind institutional-grade quantitative trading.

African Retail Forex: The Quant Gap Data Science Can Fix

Quantitative Finance

Kwiz Quants

thought-leadership

Kenya’s retail forex traders compete against institutional algorithms without any systematic edge. Data science can close that gap. Here’s where to start.

Apr 23, 2026

Kwiz Computing Technologies

Backtesting Without Lookahead Bias: Combinatorial Purged Cross-Validation

Quantitative Finance

Machine Learning

Backtesting

Why standard cross-validation fails on financial time series and how Combinatorial Purged Cross-Validation (CPCV) provides reliable backtest estimates.

Mar 1, 2026

Kwizera Jean

The Deflated Sharpe Ratio: Why Most Backtests Lie

Quantitative Finance

Statistical Testing

Kwiz Quants

Understanding and implementing the Deflated Sharpe Ratio in R — the statistical framework that separates genuine trading edge from data mining artifacts.

Feb 15, 2026

Kwizera Jean

Why We Build Systematic Trading Infrastructure in R

Quantitative Finance

Kwiz Quants

R is our primary language for quantitative finance. Here’s why we chose it for Kwiz Quants and how we make it production-ready.

Jan 10, 2026

Kwiz Computing Technologies

Categories

Kwiz Quants Blog

African Retail Forex: The Quant Gap Data Science Can Fix

Backtesting Without Lookahead Bias: Combinatorial Purged Cross-Validation

The Deflated Sharpe Ratio: Why Most Backtests Lie

Why We Build Systematic Trading Infrastructure in R