Machine Learning for Asset Managers is popular PDF and ePub book, written by Marcos M. López de Prado in 2020-04-22, it is a fantastic choice for those who relish reading online the Business & Economics genre. Let's immerse ourselves in this engaging Business & Economics book by exploring the summary and details provided below. Remember, Machine Learning for Asset Managers can be Read Online from any device for your convenience.
Machine Learning for Asset Managers Book PDF Summary
Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.
Detail Book of Machine Learning for Asset Managers PDF
- Author : Marcos M. López de Prado
- Release : 22 April 2020
- Publisher : Cambridge University Press
- ISBN : 9781108879729
- Genre : Business & Economics
- Total Page : 152 pages
- Language : English
- PDF File Size : 14,8 Mb
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