Blog
Technical, no-hype writing on algorithmic trading, backtesting methodology and Polymarket market mechanics.
Every article here is written to be checked, not just believed — real methodology, real numbers, no promises about returns. New pieces go up as they're ready; start with the one below on backtesting Polymarket's 5-minute BTC market.
2026-07-23
Win Rate Is Not an Edge
If you read nothing else: the thing worth measuring is not how often you win. It is how far your forecast beats the price, in percentage points of probability, after the exchange takes its cut. Those two numbers can point in opposite directions, and this article is about why.
2026-07-23
Перед запуском первого бота
Торговый бот не принимает решений. Он повторяет ваши — быстро и без колебаний.
2026-07-23
Before Your First Bot
A trading bot does not make decisions. It repeats yours, quickly and without flinching.
2026-07-11
Методы моделирования Монте-Карло в алгоритмической торговле
Моделирование Монте-Карло — один из самых мощных инструментов для оценки устойчивости торговых стратегий и защиты от переобучения. Если бэктестинг показывает, что *произошло*, то Монте-Карло показывает, что *могло бы произойти* при различных правдоподобных сценариях.
2026-07-11
Monte Carlo Simulation Methods in Algorithmic Trading
Monte Carlo Simulation is one of the most powerful tools for evaluating trading strategy robustness and protecting against overfitting. While backtesting shows what *happened*, Monte Carlo shows what *could have happened* under different plausible scenarios.
2026-07-11
Advanced Filtering: How to Make Your Strategy Trade Only in Favorable Conditions
Markets constantly change regimes — trends turn into sideways movement, calm periods explode into high volatility. The purpose of filters is to allow the strategy to trade only when market conditions align with its statistical edge.
2026-07-09
Protection Against Overfitting in Algorithmic Trading Strategies
Overfitting (also known as curve-fitting or over-optimization) remains one of the biggest challenges in algorithmic trading. A strategy that performs exceptionally well on historical data often fails dramatically when deployed live.
2026-07-08
The Evolution of Trading Strategy Development: The Optimizer Competition
Developing an algorithmic trading strategy is a process that requires not only a strong market idea but also meticulous work with parameters. Even a powerful concept often delivers mediocre or losing results in live trading due to poor parameter selection. This issue remains one of the central challenges in algorithmic trading.
2026-07-07
Walk-Forward Optimization (WFO) – Detailed Explanation
Walk-Forward Optimization** is a robust validation technique used in algorithmic trading to test a strategy’s performance in a way that closely simulates real-world trading conditions. It is widely regarded as one of the strongest defenses against overfitting
2026-07-07
Walk-Forward Optimization (WFO) – Detailed Explanation
Walk-Forward Optimization** is a robust validation technique used in algorithmic trading to test a strategy’s performance in a way that closely simulates real-world trading conditions. It is widely regarded as one of the strongest defenses against overfitting
2026-07-07
Factor Modeling in Event Markets: From Random Bets to Systematic Alpha
Factor Modeling in Event Markets: From Random Bets to Systematic Alpha
2026-07-07
Why Your 75%-Win-Rate Polymarket BTC Bot Is Probably Losing Money
A no-hype guide to backtesting Polymarket's 5-minute Bitcoin up/down markets — why win rate misleads, how transaction costs quietly kill most edges, and what actually survives.
2026-07-06
Strategic Regimes: Trend vs. Mean Reversion. How Algorithms Profit in Event Markets
Strategic Regimes: Trend vs. Mean Reversion. How Algorithms Profit in Event Markets
2026-07-05
From the Perfect Backtest to Harsh Reality: How "Stress Testing" on Blind Data Saves Algorithms from Ruin
In this article, we will break down why strategies that work perfectly in the past die in the future, and why ruthless "stress tests" on unseen data are the absolute only way to survive in the market.
2026-07-04
From Crystal Balls to Formulas: Why Trading is About Calculating Probabilities, Not Predicting the Future
Why Trading is About Calculating Probabilities, Not Predicting the Future
2026-07-03
How to Build a Production-Grade Trading Bot for Polymarket CLOB
Production-Grade Trading Bot for Polymarket CLOB
2026-07-02
Understanding CLOB: Why Polymarket’s Order Book Changes Everything
CLOB: Why Polymarket’s Order Book Changes Everything
2026-07-01
The Win Rate Illusion: Why Your 75% Win Rate on Polymarket 5-Minute Markets Is Burning Capital
The Win Rate Illusion: Why Your 75% Win Rate on Polymarket 5-Minute Markets Is Burning Capital