Lesson plan
Alpha Profiling
Alpha profiling is an application of machine learning to optimize the execution of large orders in financial markets by means of algorithmic trading. The purpose is to select an execution schedule that minimizes the expected implementation shortfall, or more generally, ensures compliance with a best execution mandate. Alpha profiling models learn statistically-significant patterns in the execution of orders from a particular trading strategy or portfolio manager and leverages these patterns to associate an optimal execution schedule to new orders. In this sense, it is an application of statistical arbitrage to best execution. For example, a portfolio manager specialized in value investing may have a behavioral bias to place orders to buy while an asset is still declining in value. In this case, a slow or back-loaded execution schedule would provide better execution results than an urgent one. But this same portfolio manager will occasionally place an order after the asset price has already begun to rise in which case it should best be handled with urgency; this example illustrates the fact that Alpha Profiling must combine public information such as market data with private information including as the identity of the portfolio manager and the size and origin of the order, to identify the optimal execution schedule.
Article summary
Alpha profiling is an application of machine learning to optimize the execution of large orders in financial markets by means of algorithmic trading. The purpose is to select an execution schedule that minimizes the expected implementation shortfall, or more generally, ensures compliance with a best execution mandate. Alpha profiling models learn statistically-significant patterns in the execution of orders from a particular trading strategy or portfolio manager and leverages these patterns to associate an optimal execution schedule to new orders. In this sense, it is an application of statistical arbitrage to best execution. For example, a portfolio manager specialized in value investing may have a behavioral bias to place orders to buy while an asset is still declining in value. In this case, a slow or back-loaded execution schedule would provide better execution results than an urgent one. But this same portfolio manager will occasionally place an order after the asset price has already begun to rise in which case it should best be handled with urgency; this example illustrates the fact that Alpha Profiling must combine public information such as market data with private information including as the identity of the portfolio manager and the size and origin of the order, to identify the optimal execution schedule.
Key claims
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.