Price Signals in Algorithmic Trading

This lecture by the instructor focuses on the use of machine learning techniques in algorithmic trading, specifically in the context of a financial technology company. The lecture covers the importance of price signals in executing orders for clients in futures markets, emphasizing the goal of minimizing slippage. The speaker discusses various algorithms targeting different benchmarks, such as arrival price, average price, and settlement price, showcasing examples of successful trades. Additionally, the lecture delves into the application of machine learning in making short-term price predictions and the significance of using real data to capture passive fill probability and signal significance. The speaker also highlights the challenges faced in applying traditional option pricing models and the success story of using machine learning for smart order routing. The lecture concludes with insights on the complexities of high-frequency trading and the importance of understanding and explaining the models used in algorithmic trading.