This element introduces machine learning (ML) tools that can help asset managers discover economic and financial theories.
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Da: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condizione: Fine. Codice articolo mon0004107254
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. In Stock. This item is printed on demand. Codice articolo __1009702424
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Da: Rarewaves.com USA, London, LONDO, Regno Unito
Hardback. Condizione: New. 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. Codice articolo LU-9781009702423
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781009702423
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Da: Chiron Media, Wallingford, Regno Unito
hardcover. Condizione: New. Codice articolo 6666-GRD-9781009702423
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 51931700-n
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condizione: New. 2026. hardcover. . . . . . Codice articolo V9781009702423
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 51931700
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