Paper: arXiv 2603.09219

Authors: The Anh Pham, Bao Chan Nguyen, Nguyet Nguyen Thi

Abstract

Transitioning a strategy from backtest to live trading is a common failure point for quantitative systems due to parameter overfitting, selection bias, and sensitivity to regime changes. This paper presents the AlgoXpert Alpha Research Framework, a standardized protocol that evaluates strategies across three stages: In Sample (IS), which focuses on stable parameter regions instead of single optima; Walk Forward Analysis (WFA) using rolling windows and purge gaps to reduce information leakage, supported by majority pass and catastrophic veto rules; and Out of Sample (OOS) testing under strict parameter lock with no further tuning. The framework applies a defense in depth structure that includes structural safeguards such as cliff veto, execution controls such as spread and leverage guards, and equity protection mechanisms such as circuit breakers and a kill switch. A case study on USDJPY M5 intraday data demonstrates how to detect overfitting through performance decay and drawdown behavior across chronological stages. A post validation comparison of four alpha variants (v1 to v4) shows rank reversal when the objective changes from maximizing Sharpe to minimizing maximum drawdown, highlighting the trade off between risk adjusted performance and tail risk control.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper provides a highly practical, robust execution and testing framework for algorithmic trading strategies, emphasizing parameter stability, purged walk-forward analysis, and risk guards. While it relies primarily on applied methodology rather than advanced mathematical proofs, its empirical rigor, clear structured protocol, and focus on mitigating backtest overfitting make it a valuable resource for systematic trading workflows.

Research Flowchart

  flowchart TD
    A["Research Goal: Mitigate Overfitting & Selection Bias in FX Quantitative Strategies"] --> B["Data Input: USDJPY M5 Intraday Data"]
    
    subgraph Framework ["AlgoXpert 3-Stage Protocol"]
        B --> C1["Stage 1: In-Sample (IS)<br/>Parameter Region Stability"]
        C1 --> C2["Stage 2: Walk-Forward Analysis (WFA)<br/>Rolling Windows, Purge Gaps, Veto Rules"]
        C2 --> C3["Stage 3: Out-of-Sample (OOS)<br/>Strict Parameter Lock"]
    end

    subgraph Defense ["Defense-in-Depth Safeguards"]
        C3 --> D["Structural Safeguards, Execution Guards & Equity Circuit Breakers"]
    end

    D --> E["Outcome: Detection of Performance Decay & Objective-Based Rank Reversal (Sharpe vs Max DD)"]