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 ...
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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.
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Add this copy of Machine Learning for Asset Managers to cart. $28.12, new condition, Sold by GreatBookPricesUK5 rated 5.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2020 by Cambridge University Press.
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New. Trade paperback (US). Glued binding. 152 p. Contains: Unspecified, Line drawings, black & white, Tables, black & white. Elements in Quantitative Finance. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
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New. Trade paperback (US). Glued binding. 152 p. Contains: Unspecified, Line drawings, black & white, Tables, black & white. Elements in Quantitative Finance.
Add this copy of Machine Learning for Asset Managers to cart. $73.12, like new condition, Sold by GreatBookPricesUK5 rated 5.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2026 by Cambridge University Press.
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Fine. Contains: Line drawings, black & white, Tables, black & white, Unspecified. Elements in Quantitative Finance . 30 b/w illus. 4 tables. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
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New. Print on demand Trade paperback (US). Glued binding. 152 p. Contains: Unspecified, Line drawings, black & white, Tables, black & white. Elements in Quantitative Finance.
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New. Print on demand Contains: Line drawings, black & white, Tables, black & white, Unspecified. Elements in Quantitative Finance . 30 b/w illus. 4 tables.
Add this copy of Machine Learning for Asset Managers (Elements in to cart. $20.41, good condition, Sold by BooksRun rated 4.0 out of 5 stars, ships from Philadelphia, PA, UNITED STATES, published 2020 by Cambridge University Press.
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Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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