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Machine Learning in Asset PricingShipping for this item is FREE, however please allow 6 weeks for shipping, please note once you place the order we are not able to cancel it. Condition: BRAND NEW ISBN: 9780691218700 Format: Trade binding Year: 2021 Publisher: Princeton University Press Description: A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value
Shipping for this item is FREE, however please allow 6 weeks for shipping, please note once you place the order we are not able to cancel it.Condition: BRAND NEW
ISBN: 9780691218700
Format: Trade binding
Year: 2021
Publisher: Princeton University Press
Description:
A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing
Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing.
Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets.
Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.
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Smooth,elegant watch
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Sharp looking watch,looks like a Rolex from a distance
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Great watch
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Great looking. Easy to adjust wrist band. Looks expensive and get many compliments
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Good, inexpensive work watch
Color: all black watch
Bought as a working watch so I don’t wreck my good watches. It’s been working just fine and holding up well while not taking very good care of it. Keeps accurate time. Glass has stayed clear. Black finish looks good and is holding up well. Seems to hold up with steady pounding.
Stop watch buttons are a bit crude and will mess up your time when your hand gets pushed back against it during hard labor. However, I have not babied this watch at all.
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Color: two tone blue
Will need adjustment. Great looking watch
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Color: all black watch
It’s not an ugly watch, but I did not think the watch looked as nice in person This watch lost several minutes over a few months. It is light and feels cheap. However, it was not expensive, it’s comfortable to wear and beauty is in the eye of the beholder.
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Reviewed in the United States on July 15, 2025
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