Evaluating Returns and Backtesting

Overview

This course will advance learners' abilities to construct and backtest strategies. The curriculum emphasizes a deep understanding of key performance metrics—such as annualized returns, volatility, and various risk-adjusted ratios—to critically evaluate the effectiveness of trading strategies. Additionally, learners will enhance their skills in visualizing strategy performance through advanced graphical representations. By mastering the implementation and rigorous evaluation of trading models, students will be well-equipped to optimize strategies and ensure robust performance in the world of capital markets.

Syllabus

Measuring Returns

Understand the foundations for backtesting. Learners will examine formulas and develop tools for calculating and plotting returns.

Measuring Risks

Understand volatility, skewness, kurtosis, and the impacts that these concepts have on developing a trading strategy.

Measuring Risk-Adjusted Returns

Explore drawdowns, how to calculate them, and which ratios should be employed when developing a backtest strategy. Calculations include the Sharpe, Sortino, and Calmar Ratio.

Backtesting a Risk Parity Portfolio

Through Python, learn how to implement Walk-Forward Validation and combine core calculations to develop a robust backtesting strategy.

Project: Evaluating and Backtesting a Dynamic Investment Strategy

Assess and manage investment risk through key calculations such as Volatility, Sharpe Ratio, Sortino Ratio, Calmar Ratio. Learners develop and backtesting a strategy using Walk-Forward Validation.