Lecture 19: Implementing Signal-Based Trading Strategy with Linear Regression Model in Python|

Complete Course Material : https://drive.google.com/file/d/1uy6J...
In this video, we delve into the practical application of our linear regression model for SPY trading by implementing a signal-based trading strategy. We compute trading positions based on predicted price changes of SPY, going long if the signal is positive and short if negative. By calculating daily profits and cumulative wealth, we evaluate the performance of this strategy against a passive buy-and-hold strategy. Our results demonstrate the superiority of the signal-based strategy, both in the training and test datasets, with total profits of $170 and $130 respectively over 1000 days. We analyze the consistency of performance using metrics such as Sharpe ratio and maximum drawdown, highlighting the trade-off between returns and risks. Despite the challenges posed by bid-ask spreads and other market complexities, our approach showcases the potential of combining statistical modeling with trading strategies. Join us as we navigate the intersection of data science and finance, unlocking insights into real-world trading dynamics.
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