Quantitative
Backtesting methodology, statistics, anti-overfit practice, position sizing, and full system papers.
Regime Detection: Rolling Volatility, Markov Switching, and the Overfitting Trap
Regime detection aims to identify structural shifts in market behavior, typically modeled as transitions between distinct statistical states (high volatility/low correlation, crisis regimes, trending/ranging). Two common methods are
Multiple-Testing Correction for Strategy Research: Why Many Tested Rules Produce a Winner by Chance
When a researcher tests hundreds or thousands of trading strategies against historical data, statistical chance alone guarantees that some will appear to work purely by accident. Multiple-testing correction
Multiple-Testing Correction in Strategy Research
When researchers test many trading rules on historical data, some will appear profitable by pure chance, not signal. Multiple-testing correction adjusts statistical thresholds to account for the number
Transaction-Cost Modelling: Slippage, Spread and Impact Assumptions that Decide Whether a Backtest Survives
Transaction costs in backtesting determine whether a paper strategy remains profitable when deployed to real markets. This paper examines the three primary transaction cost components—bid-ask spread, market impact,
Multiple-Testing Correction in Strategy Research: The Problem of Spurious Findings
Testing many trading rules on historical data will produce apparent winners purely by chance, a problem known as multiple comparisons bias. When one hundred rules are backtested, approximately
Backtesting and the Three Systematic Biases
Backtesting is the practice of applying a trading strategy to historical market data to estimate its past performance and gauge its potential future profitability. While backtesting can identify
Position Sizing: Fixed Fractional, Kelly Criterion, and Why Full Kelly Hurts
**Abstract**: Position sizing determines what fraction of an account's capital to risk on each trade. Fixed fractional and Kelly Criterion represent two distinct mechanical approaches, with Kelly offering
An Anti-Overfit Protocol for Strategy Backtesting on TradingView
A lab for testing NQ intraday strategies in TradingView's Strategy Tester with pre-registered parameters, capped optimization tries, single-read validation, and repaint-proof Pine code.
Auditing Your Own Edge: Results From a Cross-Asset Backtesting Program
What a pre-registered, holdout-protected backtesting program found across stocks, crypto, and intraday strategies, including the audited numbers, the deflation caveats, and the long list of ideas it killed.
A Committee of Agents for Prediction-Market Trading: Design of a Paper-Only Kalshi System
How a whole-exchange Kalshi scanner routes every candidate trade through a five-analyst committee, six parallel sizing books, and a mandatory human review, and why it publishes no performance claims yet.
Quant Core, Human Gate: An AI Investor-Committee for Daily Stock Plans
A daily stock system that pairs a validated quantitative confidence score with an AI 'investor committee' doing catalyst research, and a hard plan-only rule: the system never places an order.