Trading Systems That Work: Building and Evaluating Effective Trading Systems

Author: Thomas Stridsman | Categories: Trading Systems, Quantitative Trading, Backtesting, Technical Analysis

Executive Summary

"Trading Systems That Work" by Thomas Stridsman, published in 2001 by McGraw-Hill, is a comprehensive guide to designing, building, testing, and evaluating mechanical trading systems for the futures markets. Stridsman takes a rigorous, data-driven approach to system development, challenging many of the conventional assumptions in the trading systems community. The book covers the entire process from evaluating performance measures and handling futures contract data, through developing specific system concepts based on moving averages, oscillators, breakouts, and pattern recognition, to advanced topics including money management and portfolio construction.

The book stands out for its intellectual honesty and its insistence on proper statistical methodology. Stridsman is deeply skeptical of over-optimized systems that look brilliant on historical data but fail in live trading. He emphasizes robustness, simplicity, and the critical importance of proper performance evaluation over raw return maximization. All systems and strategies in the book are presented with complete code (primarily TradeStation EasyLanguage), enabling readers to replicate and test the concepts themselves.

Core Thesis & Arguments

Stridsman's central thesis is that effective trading systems must be built on a foundation of sound performance evaluation, proper data handling, and robust testing methodology -- and that the industry's standard practices in all three areas are seriously flawed. He argues that most traders focus too heavily on total net profit and win rate while neglecting more important measures like drawdown, profit per trade, and the statistical significance of results.

Key arguments include: (1) Standard performance measures (total net profit, percent profitable) are inadequate and often misleading. (2) The choice between continuous, back-adjusted, and ratio-adjusted futures data has profound implications for system results. (3) Simple systems based on well-understood concepts (moving average crossovers, breakouts, oscillator divergences) consistently outperform complex, over-optimized systems. (4) Portfolio diversification across markets is more important than system optimization within a single market. (5) Money management (position sizing) can transform a marginally profitable system into a strongly profitable one.

Chapter-by-Chapter Analysis

Part One: Evaluating Performance

Chapter 1: Performance Measures

Reviews standard metrics: total net profit, maximum intraday drawdown, account size required, return on account, average trade, largest winning/losing trades, profit factor. Establishes the baseline vocabulary.

Chapter 2: Better Measures

Introduces superior evaluation methods: profit per trade, cumulative profit curves, equity tops, flat time, run-ups, and custom drawdown analysis. Argues that these measures provide a much more accurate picture of system viability.

Chapter 3: Futures Contract Data

Critical chapter on data handling. Covers non-adjusted, point-based back-adjusted, and ratio-adjusted data formats and their implications for system testing. Shows how improper data handling can produce completely misleading results.

Part Two: System Concepts

Chapters 4-8: Core System Types

Develops and tests systems based on moving averages (simple, exponential, weighted), momentum oscillators, breakout/channel systems, and pattern-based approaches. Each system type is evaluated across multiple markets with proper out-of-sample testing.

Part Three: Finishing Touches

Chapters 9-12: Advanced Topics

Covers money management and position sizing, portfolio construction and correlation analysis, walk-forward optimization, and Monte Carlo simulation for risk assessment.

Key Concepts & Frameworks

• Robust System Design: Building systems that perform well across multiple markets and time periods, rather than optimizing for a single market's historical data.
• Proper Performance Evaluation: Using drawdown, profit per trade, and statistical significance rather than just total returns and win rate.
• Data Integrity: Understanding how futures contract construction (continuous, back-adjusted, ratio-adjusted) affects system testing results.
• Walk-Forward Optimization: Testing system parameters on in-sample data and validating on out-of-sample data to guard against curve-fitting.
• Portfolio Diversification: Trading systems across multiple uncorrelated markets to reduce drawdowns and improve risk-adjusted returns.

Practical Trading Applications

1. Always evaluate trading systems using multiple performance metrics, not just total profit -- pay particular attention to maximum drawdown, profit per trade, and flat time.
2. Use proper futures contract data construction (ratio-adjusted or point-based back-adjusted) to avoid false signals from artificial price gaps.
3. Prefer simple, robust systems with few parameters over complex, highly optimized systems that are likely over-fitted.
4. Apply walk-forward optimization to validate that system parameters are stable across different time periods.
5. Diversify across multiple uncorrelated markets to reduce portfolio-level drawdowns.
6. Use Monte Carlo simulation to estimate the realistic range of future outcomes rather than relying on a single backtest equity curve.

Critical Assessment

Strengths: The book's emphasis on proper methodology and intellectual honesty is outstanding. The treatment of futures contract data handling is one of the best in the literature. The complete system code provided enables independent verification. The writing, while technical, is clear and well-organized.

Weaknesses: The code is in TradeStation EasyLanguage, which may limit accessibility for traders using other platforms. The book is focused exclusively on futures markets. Some sections are extremely technical and may overwhelm readers without a quantitative background. The systems tested, while educational, may not be competitive with modern quantitative approaches.

Best for: Systematic traders and system developers who want to build a rigorous foundation in trading system design, testing, and evaluation. Particularly valuable for futures traders.

Key Quotes

"Hypothetical performance results have many inherent limitations. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown."

"The simplest systems, properly tested across multiple markets, consistently outperform the most sophisticated over-optimized models."

"A trading system is only as good as the data it is tested on and the methodology used to evaluate it."

Conclusion & Recommendation

"Trading Systems That Work" is an essential reference for anyone serious about systematic trading. Stridsman's insistence on proper methodology, honest performance evaluation, and robust system design provides a much-needed antidote to the over-optimized, curve-fitted systems that dominate the trading systems marketplace. While the specific systems presented may be dated, the principles of system development and evaluation are timeless. The book is required reading for any trader who wants to build systems that work in the real world, not just on historical charts.