Posts by Guetaquant

@Guetaquant

Mahdi Goodarzi

Quantitative Engineer & Algorithmic Trading Systems Developer | Founder @ Gueta ...
Bogotá, Colombia guetaquant.com Joined September 2026
1.3k Points • 37 Badges • 12 Connections • 12 Followers • 17 Following

Posts by Guetaquant

Guetaquant • • in Articles • 2 min read
Two questions dominate Colombian search around Deriv: does it accept Colombian pesos COP? and what are synthetic indices, mathematically? This post answers both with verifiable mechanics — no signals, no account handling, no return claims. !Guía ...
Guetaquant • • in Articles • 3 min read
Two stocks can rise together for years and still be untradeable as a pair. Correlation measures co-movement; pairs trading needs cointegration — a stationary, mean-reverting spread. This post builds the standard test pipeline in Python and shows wher...
Guetaquant • • in Articles • 4 min read
When algorithmic traders design risk models, they rigorously calculate Kelly fractions, Value at Risk VaR, and dynamic ATR trailing stops. Yet, one catastrophic risk is almost universally ignored in retail algorithm architecture: counterparty custody...
Guetaquant • • in Articles • 1 min read
Most quantitative trading models fail when transitioned from historical backtest to live execution not because the mathematical alpha was flawed, but because the backtesting engine assumed frictionless, zero-latency execution. In a simulation, your ...
Guetaquant • • in Articles • 4 min read
Your backtest equity curve is merely one historical trajectory out of millions of equally probable alternatives. The total profit of your trading system is invariant to order: 100 closed trades will yield the exact same ending dollar return whether ...
Guetaquant • • in Articles • 3 min read
Static stop-losses break across volatility regimes. A fixed 20-pip stop that is conservative on EUR/USD during Asia session is noise-level on XAU/USD during New York open. In cTrader Automate C#, the robust pattern is a dedicated risk engine: signal ...
Guetaquant • • in Articles • 2 min read
Almost all literature on algorithmic position sizing stops at the standard formula: lots = balance riskpercent / stopdistance tickvalueperlot That part is straightforward. The subtle failure does not live in the equation itself: it hides in the ...
Guetaquant • • in Articles • 3 min read
Why Perfect Backtests Fail: Walk-Forward Optimization and Deflated Sharpe in Python Every quantitative trader and algorithmic developer knows this pattern: you design an intraday or swing strategy, optimize parameters in MetaTrader, TradingView, or...
Guetaquant • • in Articles • 2 min read
Overview: Pine Script v6 & Institutional Risk Architecture TradingView's Pine Script v6 introduced critical architectural upgrades for quantitative developers. Moving beyond basic visual scripts, v6 provides strict type enforcement, built-in tensor...
Guetaquant • • in Articles • 1 min read
Algorithmic Risk Management in MT5: Dynamic Position Sizing & MQL5 Architecture Most retail trading failures stem from static lot sizing. Trading a fixed 1.0 lot on EUR/USD creates vastly different dollar drawdowns compared to 1.0 lot on Gold XAU/U...
chevron_left