Ch 1. What is a trading system

What is a Trading System?

Definition and Components

• Trading System:

  • A precise set of rules for market entry and exit.
  • Operates automatically without human intervention.
  • Statistically testable, allowing performance analysis for past and future predictions.

• Trading Strategy:

  • Combines entry/exit rules with money management and portfolio rules.
  • Provides a fully automatic market approach with a starting capital.

Money Management vs. Risk Management

• Money Management:

  • Focuses on position sizing: determining the amount to invest in each trade.
  • Involves deciding how many shares or futures contracts to buy and sell.

• Risk Management:

  • Involves setting initial stop losses or target prices.
  • Different from money management, which is more about investment allocation.

Portfolio Management

• Constructing a Portfolio:
  • Involves creating a mix of systems on uncorrelated price series.
  • Money management is crucial for maximizing portfolio returns relative to risk.
  • Also referred to as portfolio management.

Implementation

• Software Requirements:

  • Must handle programming and testing of the trading system.
  • Needs to execute trades directly in the market without user interference.

• Algorithmic Trading vs. Automated Trading:

  • Algorithmic Trading: Generates trading signals based on predefined rules.
  • Automated Trading: Executes the algorithmic trading signals automatically in the market.
  • Algorithmic trading can exist without automated execution, but automated trading relies on algorithmic signals.

Key Takeaways

• Precision and Automation:

  • Trading systems eliminate discretionary decisions, ensuring consistency.
  • Automation enhances efficiency by executing trades without user intervention.

• Importance of Rules:

  • Clear, well-defined rules are essential for testing and reliable performance.
  • Effective money and risk management strategies are crucial for long-term success.

An Easy Example of a Trading System

Pseudo Code for Trading System

• Entry Rules:

  • Buy 2 contracts at the highest high in the last 20 days.
  • Sell short 2 contracts at the lowest low in the last 20 days.

• Exit and Stop Loss Rules:

  • If market position = 1 (long), then sell at last close - average true range (14) stop.
  • If market position = -1 (short), then buy to cover at last close + average true range (14) stop.

Explanation

• Entry Rule:

  • Defines when to enter the market (buying at the highest high, selling short at the lowest low).

• Stop Loss Rule:

  • Specifies conditions for exiting the market to manage risk (acts as both initial and trailing stop loss).

Trading System vs. Trading Methodology

• Trading System:

  • Precise set of predefined rules.
  • Automated, eliminating discretionary decisions.
  • Statistically testable and based on historical data.

• Trading Methodology:

  • Set of rules applied discretionally.
  • No automation or systematic testing.
  • Relies on judgment and may not always be classifiable ex-ante.

Quantitative Finance and Trading Systems

• Rise of 'Quants':

  • Financial professionals using quantitative methods for trading signals.
  • The term "quantitative finance" implies a scientific, statistical approach.

• Scientific Appeal:

  • Many trading systems are marketed with a scientific image.
  • Complexity is often perceived as a sign of sophistication, but simplicity can be more effective.

Simple Trading Systems

• Effectiveness of Simplicity:

  • Simple systems, such as channel breakouts, indicators, or moving averages, can be highly effective.
  • Proper testing and application reveal their predictive power.

• Role of Management:

  • Success relies heavily on money management, portfolio construction, risk management, and timeframe.
  • A simple but well-managed system can produce favorable equity lines, especially when applied to a diversified portfolio.

Why You Need a Trading System

Evidence from Economic Literature

• Market Performance:

  • Only a small percentage of traders consistently beat the market.
  • Most retail and institutional traders eventually fail.

• Success Factors:

  • Successful discretionary traders often rely on intuition and gut feeling.
  • Predetermined trading strategies and investing methodologies help many successful money managers and traders.

Benefits of a Trading System

• Structured Approach:
  • Provides a systematic way to approach trading, reducing emotional and irrational decisions.
  • Helps traders who are not naturally successful discretionary traders.

Challenges and Considerations

• Execution Issues:

  • Physical courage and decisiveness are still required to follow trading signals.
  • "Trading systems work, system traders do not"
  • Missing good trades regularly can be disastrous

• Research and Confidence:

  • Significant research and statistical work are necessary to develop, implement, test, and evaluate a trading system.
  • Confidence in the system is crucial, especially during drawdown periods.

• Similar Drawbacks:

  • Systematic trading also faces issues like insufficient starting capital, need for portfolio diversification, and full-time dedication.

Trading is Not Rational

• Emotional Influence:

  • Fear and greed impact prices in ways that are difficult for the human mind to predict.
  • Some discretionary traders succeed with gut feeling but can't always explain their decisions.

• Need for Counterintuitive Tools:

  • Mechanical trading systems often use signals that seem illogical but are statistically sound.
  • Discarding widely held beliefs and the feel-good approach is necessary.

Practical Implications

• Mechanical Trading:

  • Requires discarding conventional financial beliefs.
  • Often involves counterintuitive actions, such as buying at the highest high.
  • Can feel uncomfortable but is driven by statistical evidence.

• Violence Against Yourself:

  • Mechanical trading forces traders to act against their natural inclinations.
  • This disciplined approach is essential for profitability unless you are naturally adept at intuitive trading.

Key Takeaways

• Structured Systems:

  • Trading systems offer a structured, systematic approach that can help traders who struggle with discretionary methods.

• Embrace Discipline:

  • Success with a trading system requires discipline, extensive research, and the ability to follow signals without hesitation.

• Counterintuitive Strategies:

  • Effective systems often involve actions that feel uncomfortable or counterintuitive but are statistically validated.

The Science of Trading Systems

Objective vs. Subjective Technical Analysis

• Objective Technical Analysis:

  • Well-defined, repeatable procedures.
  • Issues unambiguous signals.
  • Can be implemented as computerized algorithms.
  • Allows for back-testing on historical data.
  • Results can be evaluated quantitatively.

• Subjective Technical Analysis:

  • Not well-defined.
  • Requires an analyst's interpretation.
  • Cannot be computerized or back-tested.
  • Impossible to confirm or deny efficacy objectively.
  • Viewed negatively by academia and serious market practitioners.

Scientific Approach to Technical Analysis

• Empirical Basis:

  • Scientific knowledge is based on observations of reality.
  • Technical analysis uses statistical inference to generalize from historical data and predict future trends.

• Quantitative Methods:

  • Like statistics, technical analysis is quantitative.
  • Predicts future through functional relationships among variables.
  • Rules in technical analysis are akin to functional relationships in statistics, with attached probabilities.

Hypothetic-Deductive Method

• Stages of the Hypothetic-Deductive Method:

  1. Observation:
     • Continuous observation of market activity.
     • Identify relationships among variables (e.g., daily volume and closing price).
  2. Hypothesis:
     • An innovative hypothesis is formed based on observed relationships.
     • The hypothesis is believed to apply to the majority of the data, not just the sample.
  3. Prediction:
     • If the hypothesis is true, a prediction can be made about new observations.
  4. Verification:
     • Test the prediction against new observations to see if it holds true.
  5. Conclusion:
     • Use statistical inference tools (e.g., confidence intervals, hypothesis tests) to determine the validity of the hypothesis.

• Comparison to Applied Sciences:

  • This method is similar to scientific appraisal methods used in fields like chemistry and biology.

Key Takeaways

• Objective Analysis:

  • Preferred due to its clarity and ability to be tested and evaluated quantitatively.
  • Subjective analysis is less reliable and lacks scientific validation.

• Scientific Methodology:

  • The hypothetic-deductive method provides a structured approach to developing and validating trading systems.
  • Involves observation, hypothesis formation, prediction, verification, and conclusion.

• Quantitative Approach:

  • Aligns technical analysis with statistical methods.
  • Enhances the reliability and predictability of trading systems.