// Archive
Category: Backtesting
Backtesting frameworks, walk-forward analysis, Monte Carlo, validation discipline.
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The Quant’s Backtesting Reading List for 2026
Tired of overhyped strategies that fail in live trading? We review the essential backtesting books for 2026 that focus on statistical rigor and avoiding the common pitfalls that trap new quants. Learn which texts are essential for both Python and R practitioners.
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GPU Backtesting: RTX 4090 Ti vs. RX 7900 XTX in 2026
For GPU backtesting in 2026, the RTX 4090 Ti is the winner for professionals due to CUDA’s mature ecosystem. The AMD RX 7900 XTX offers a strong price-to-performance alternative for those with custom codebases.
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Algorithmic Trading Review: A Brutal Verdict for 2026
Is algorithmic trading a realistic goal for profit in 2026? We deliver a practitioner’s honest verdict on the hype, the necessary tools, and the cold, hard reality of competing against the quants.
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Why Backtrader Beats Zipline for Production‑Ready Strategies
Zipline may look sleek, but production traders need flexible data feeds, reliable broker links, and scalable architecture. Discover backtrader, Lean, and IBridgePy as proven alternatives.
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Backtest Like a Quant: A No‑Fluff VectorBT Walkthrough
A no‑fluff vectorbt tutorial that walks you through installation, core objects, a minimal strategy, performance tricks, and how to ship the code to production.
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Why Most Quant Trading Software Misses the Real Edge
A practitioner’s look at choosing quant trading software that actually delivers, focusing on data integrity, execution realism, and production‑grade workflows.