Empirical Asset Pricing

Empirical Asset Pricing
Author: Wayne Ferson
Publisher: MIT Press
Total Pages: 497
Release: 2019-03-12
Genre: Business & Economics
ISBN: 0262039370

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An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Noise Trading, Transaction Costs, and the Relationship of Stock Returns and Trading Volume

Noise Trading, Transaction Costs, and the Relationship of Stock Returns and Trading Volume
Author: Mr.Charles Frederick Kramer
Publisher: International Monetary Fund
Total Pages: 36
Release: 1994-10-01
Genre: Business & Economics
ISBN: 1451854870

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The relationship of stock returns and trading volume is the focus of much recent interest. I examine an economic model of a rational trader who operates in a market with transactions costs and noise trading. The level of trading affects the rational trader’s marginal cost of transacting; as a result, trading volume is a source of risk. This engenders an equilibrium relationship between returns and volume. The model also provides a simple way to scrutinize this relationship empirically. Empirical evidence supports the implications of the model.

A Productivity Augmented Capital Asset Pricing Approach to Anomaly Resolution

A Productivity Augmented Capital Asset Pricing Approach to Anomaly Resolution
Author: David J. Moore
Publisher:
Total Pages: 39
Release: 2010
Genre:
ISBN:

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Linear asset pricing models such as CAPM and the Fama-French 3-factor model rely on a linear approximation of marginal utility growth to discount expected returns. Unconditional estimations of these models are unable to explain the abnormal returns associated with simple strategies based on prior-return portfolios (momentum); and conditional estimations have not yet been applied to momentum strategies. This study demonstrates that conditional estimation of these models can explain the abnormal returns associated with momentum strategies when using a macroeconomic theory-derived and productivity-based marginal utility growth proxy as an instrument. Robustness tests show the productivity-augmented CAPM is also capable of explaining the size and value (book-to-market) anomalies. In addition to anomaly resolution, the results and methodology have practical applications in cost of capital estimation, executive compensation, and fraud detection.

Asset Pricing Models with and Without Consumption Data

Asset Pricing Models with and Without Consumption Data
Author: Gikas A. Hardouvelis
Publisher:
Total Pages:
Release: 2018
Genre:
ISBN:

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This paper evaluates the ability of the empirical model of asset pricing of Campbell(1993a,b) to explain the time-series and cross-sectional variation of expected returns ofportfolios of stocks. In Campbell's model, an alternative risk-return relationship is derivedby substituting consumption out of the linearized first-order condition of the representativeagent. We compare this methodology to models that use actual consumption data, such asthe model of Epstein and Zin, 1989, 1991, and the standard consumption-based CAPM.Although we find that Campbell's model fits the data slightly better than models whichexplicitly price consumption risk, and provides reasonable estimates of the representativeagent's preference parameters, the parameter restrictions of the Campbell model, as well asits over-identifying orthogonality conditions, are generally rejected. The parameter restrictionsof the Campbell model, and the over-identifying conditions, are marginally not rejectedwhen the empirical model is augmented to account for the "size effect"

Machine Learning in Asset Pricing

Machine Learning in Asset Pricing
Author: Stefan Nagel
Publisher: Princeton University Press
Total Pages: 156
Release: 2021-05-11
Genre: Business & Economics
ISBN: 0691218706

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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.

Market Segmentation and Noise Trader Risk

Market Segmentation and Noise Trader Risk
Author: Vihang R. Errunza
Publisher:
Total Pages: 14
Release: 2000
Genre:
ISBN:

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A simple asset pricing model is developed to take into account two important characteristics in global investments: market segmentation and noise trader risk. Our results show the removal of international investment barriers and cross-border listings have not led to a fully integrated international capital market. We also show that different degree of investor rationality across borders induces an additional component of risk premium which is related to the quot;noise spill-over effectquot.

Asset Pricing: A Structural Theory And Its Applications

Asset Pricing: A Structural Theory And Its Applications
Author: Bing Cheng
Publisher: World Scientific
Total Pages: 91
Release: 2008-07-21
Genre: Business & Economics
ISBN: 9814476277

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Modern asset pricing models play a central role in finance and economic theory and applications. This book introduces a structural theory to evaluate these asset pricing models and throws light on the existence of Equity Premium Puzzle. Based on the structural theory, some algebraic (valuation-preserving) operations are developed in asset spaces and pricing kernel spaces. This has a very important implication leading to practical guidance in portfolio management and asset allocation in the global financial industry. The book also covers topics, such as the role of over-confidence in asset pricing modeling, relationship of the portfolio insurance with option and consumption-based asset pricing models, etc.

Inefficient Markets

Inefficient Markets
Author: Andrei Shleifer
Publisher: OUP Oxford
Total Pages: 225
Release: 2000-03-09
Genre: Business & Economics
ISBN: 0191606898

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The efficient markets hypothesis has been the central proposition in finance for nearly thirty years. It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies. This book describes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In actual financial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents and empirically evaluates models of such inefficient markets. Behavioral finance models both explain the available financial data better than does the efficient markets hypothesis and generate new empirical predictions. These models can account for such anomalies as the superior performance of value stocks, the closed end fund puzzle, the high returns on stocks included in market indices, the persistence of stock price bubbles, and even the collapse of several well-known hedge funds in 1998. By summarizing and expanding the research in behavioral finance, the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets.