Three Essays On Statistical Inference For Stock Return Predictions And Capital Asset Pricing Models

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Three Essays on Statistical Inference for Stock Return Predictions and Capital Asset Pricing Models

Author : Sungju Chun
Publisher :
ISBN 13 :
Total Pages : 270 pages
Book Rating : 4.:/5 (81 download)

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Book Synopsis Three Essays on Statistical Inference for Stock Return Predictions and Capital Asset Pricing Models by : Sungju Chun

Download or read book Three Essays on Statistical Inference for Stock Return Predictions and Capital Asset Pricing Models written by Sungju Chun and published by . This book was released on 2012 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: In this dissertation, I focus on econometric issues arising in the fields of Financial Economics. In the first chapter, I study return predictability in international equity markets focusing on the effects of the bias and spurious regression problems for statistical inference. The slope coefficient estimator in predictive regressions for stock returns is biased in the presence of a lagged stochastic regressor. Spurious regression may also occur if the underlying expected return is highly persistent. I consider the effect of these biases in the presence of data mining for the predictive variables. I find that the two biases can reinforce or offset each other, depending on the parameters of the model. I present a new bias expression valid with an unobserved true expected returns and re-evaluate return predictability in international equity markets adjusting for data mining associated with both effects. The second chapter studies tests for structural changes in the trend function of a univariate time series that are robust to whether the noise component is stationary (I (0)) or contains an autoregressive unit root (I (1)). The tests of interest are the robust procedures recently proposed by Perron and Yabu (2009) and Harvey, Leybourne and Taylor (2009), both of which attain the same limit distribution under I (0) and I (1) errors. We compare their finite sample size and power under different data-generating processes for the noise components. We apply the tests to a large historical panel of real exchange rates with respect to the U.S. dollar for 19 countries and document simultaneous shifts in level and trend for many series. The third chapter studies the sampling interval effect in estimating capital asset pricing models. In past empirical studies, the beta coefficient estimates are documented to be sensitive to the sampling interval used for returns. We provide a theoretical framework to explain this sampling interval effect. We show that it can be attributable to the existence of transitory components in stock prices, and provide empirical evidence supporting its presence.

Essays in Statistical Learning and Asset Pricing

Author : Guanhao Feng
Publisher :
ISBN 13 : 9780355234206
Total Pages : 109 pages
Book Rating : 4.2/5 (342 download)

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Book Synopsis Essays in Statistical Learning and Asset Pricing by : Guanhao Feng

Download or read book Essays in Statistical Learning and Asset Pricing written by Guanhao Feng and published by . This book was released on 2017 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: I have written three essays in the interdisciplinary area of statistical learning and asset pricing. The first essay focuses on Bayesian regularization on stock return predictability and its sensitivity analysis. The second essay studies a dynamic discrete model for intra-game odds to reveal the market expectation for the game outcomes. The last essay evaluates risk factor importance through taming the factor zoo in a high-dimensional setting.

Empirical Asset Pricing

Author : Wayne Ferson
Publisher : MIT Press
ISBN 13 : 0262039370
Total Pages : 497 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Empirical Asset Pricing by : Wayne Ferson

Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Essays on the Cross-sectional and Time-series Behavior of Stock Returns

Author : Vinod Chandrashekaran
Publisher :
ISBN 13 :
Total Pages : 256 pages
Book Rating : 4.:/5 (33 download)

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Book Synopsis Essays on the Cross-sectional and Time-series Behavior of Stock Returns by : Vinod Chandrashekaran

Download or read book Essays on the Cross-sectional and Time-series Behavior of Stock Returns written by Vinod Chandrashekaran and published by . This book was released on 1994 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Essays on Predicting and Explaining the Cross Section of Stock Returns

Author : Xun Zhong
Publisher :
ISBN 13 :
Total Pages : 181 pages
Book Rating : 4.:/5 (128 download)

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Book Synopsis Essays on Predicting and Explaining the Cross Section of Stock Returns by : Xun Zhong

Download or read book Essays on Predicting and Explaining the Cross Section of Stock Returns written by Xun Zhong and published by . This book was released on 2019 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation consists of three chapters that study various aspects of stock return predictability. In the first chapter, I explore the interplay between the aggregation of information about stock returns and p-hacking. P-hacking refers to the practice of trying out various variables and model specifications until the result appears to be statistically significant, that is, the p-value of the test statistic is below a particular threshold. The standard information aggregation techniques exacerbate p-hacking by increasing the probability of the type I error. I propose an aggregation technique, which is a simple modification of 3PRF/PLS, that has an opposite property: the predictability tests applied to the combined predictor become more conservative in the presence of p-hacking. I quantify the advantages of my approach relative to the standard information aggregation techniques by using simulations. As an illustration, I apply the modified 3PRF/PLS to three sets of return predictors proposed in the literature and find that the forecasting ability of combined predictors in two cases cannot be explained by p-hacking. In the second chapter, I explore whether the stochastic discount factors (SDFs) of five characteristic-based asset pricing models can be explained by a large set of macroeconomic shocks. Characteristic-based factor models are linear models whose risk factors are returns on trading strategies based on firm characteristics. Such models are very popular in finance because of their superior ability to explain the cross-section of expected stock returns, but they are also criticized for their lack of interpretability. Each characteristic-based factor model is uniquely characterized by its SDF. To approximate the SDFs by a comprehensive set of 131 macroeconomic shocks without overfitting, I employ the elastic net regression, which is a machine learning technique. I find that the best combination of macroeconomic shocks can explain only a relatively small part of the variation in the SDFs, and the whole set of macroeconomic shocks approximates the SDFs not better than only few shocks. My findings suggest that behavioral factors and sentiment are important determinants of asset prices. The third chapter investigates whether investors efficiently aggregate analysts' earnings forecasts and whether combinations of the forecasts can predict announcement returns. The traditional consensus forecast of earnings used by academics and practitioners is the simple average of all analysts' earnings forecasts (Naive Consensus). However, this measure ignores that there exists a cross-sectional variation in analysts' forecast accuracy and persistence in such accuracy. I propose a consensus that is an accuracy-weighted average of all analysts' earnings forecasts (Smart Consensus). I find that Smart Consensus is a more accurate predictor of firms' earnings per share (EPS) than Naive Consensus. If investors weight forecasts efficiently according to the analysts' forecast accuracy, the market reaction to earnings announcements should be positively related to the difference between firms' reported earnings and Smart Consensus (Smart Surprise) and should be unrelated to the difference between firms' reported earnings and Naive Consensus (Naive Surprise). However, I find that market reaction to earnings announcements is positively related to both measures. Thus, investors do not aggregate forecasts efficiently. In addition, I find that the market reaction to Smart Surprise is stronger in stocks with higher institutional ownership. A trading strategy based on Expectation Gap, which is the difference between Smart and Naive Consensuses, generates positive risk-adjusted returns in the three-day window around earnings announcements.

Essays on the Specification Testing for Dynamic Asset Pricing Models

Author : Jaeho Yun
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (913 download)

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Book Synopsis Essays on the Specification Testing for Dynamic Asset Pricing Models by : Jaeho Yun

Download or read book Essays on the Specification Testing for Dynamic Asset Pricing Models written by Jaeho Yun and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three essays on the subjects of specification testing on dynamic asset pricing models. In the first essay (with Yongmiao Hong), "A Simulation Test for Continuous-Time Models," we propose a simulation method to implement Hong and Li's (2005) transition density-based test for continuous-time models. The idea is to simulate a sequence of dynamic probability integral transforms, which is the key ingredient of Hong and Li's (2005) test. The proposed procedure is generally applicable whether or not the transition density of a continuous-time model has a closed form and is simple and computationally inexpensive. A Monte Carlo study shows that the proposed simulation test has very similar sizes and powers to the original Hong and Li's (2005) test. Furthermore, the performance of the simulation test is robust to the choice of the number of simulation iterations and the number of discretization steps between adjacent observations. In the second essay (with Yongmiao Hong), "A Specification Test for Stock Return Models," we propose a simulation-based specification testing method applicable to stochastic volatility models, based on Hong and Li (2005) and Johannes et al. (2008). We approximate a dynamic probability integral transform in Hong and Li' s (2005) density forecasting test, via the particle filters proposed by Johannes et al. (2008). With the proposed testing method, we conduct a comprehensive empirical study on some popular stock return models, such as the GARCH and stochastic volatility models, using the S&P 500 index returns. Our empirical analysis shows that all models are misspecified in terms of density forecast. Among models considered, however, the stochastic volatility models perform relatively well in both in- and out-of-sample. We also find that modeling the leverage effect provides a substantial improvement in the log stochastic volatility models. Our value-at-risk performance analysis results also support stochastic volatility models rather than GARCH models. In the third essay (with Yongmiao Hong), "Option Pricing and Density Forecast Performances of the Affine Jump Diffusion Models: the Role of Time-Varying Jump Risk Premia," we investigate out-of-sample option pricing and density forecast performances for the affine jump diffusion (AJD) models, using the S&P 500 stock index and the associated option contracts. In particular, we examine the role of time-varying jump risk premia in the AJD specifications. For comparison purposes, nonlinear asymmetric GARCH models are also considered. To evaluate density forecasting performances, we extend Hong and Li's (2005) specification testing method to be applicable to the famous AJD class of models, whether or not model-implied spot volatilities are available. For either case, we develop (i) the Fourier inversion of the closed-form conditional characteristic function and (ii) the Monte Carlo integration based on the particle filters proposed by Johannes et al. (2008). Our empirical analysis shows strong evidence in favor of time-varying jump risk premia in pricing cross-sectional options over time. However, for density forecasting performances, we could not find an AJD specification that successfully reconcile the dynamics implied by both time-series and options data.

Machine Learning in Asset Pricing

Author : Stefan Nagel
Publisher : Princeton University Press
ISBN 13 : 0691218706
Total Pages : 156 pages
Book Rating : 4.6/5 (912 download)

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Book Synopsis Machine Learning in Asset Pricing by : Stefan Nagel

Download or read book Machine Learning in Asset Pricing written by Stefan Nagel and published by Princeton University Press. This book was released on 2021-05-11 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Essays on the Predictability and Volatility of Returns in the Stock Market

Author : Ruojun Wu
Publisher :
ISBN 13 :
Total Pages : 137 pages
Book Rating : 4.:/5 (276 download)

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Book Synopsis Essays on the Predictability and Volatility of Returns in the Stock Market by : Ruojun Wu

Download or read book Essays on the Predictability and Volatility of Returns in the Stock Market written by Ruojun Wu and published by . This book was released on 2008 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies the effect of parameter uncertainty on the return predictability and volatility of the stock market. The first two chapters focus on the decomposition of market volatility, and the third chapter studies the return predictability. When facing imperfect information, the investors tend to form a learning scheme that encompasses both historical data and prior beliefs. In the variance decomposition framework, the introducing of learning directly impacts the way that return forecasts are revised and consequently the relative component of market volatility based on these forecasts, namely the price movements from revision on future discount rates and those from future cash flows. According to the empirical study in Chapter 1, the former is not necessarily the major driving force of market volatility, which provides an alternative view on what moves stock prices. Learning is modeled and estimated by Bayesian method. Chapter 2 follows the topic in Chapter 1 and studies the role of persistent state variables in return decomposition in order to provide more robust inference on variance decomposition. In Chapter 3 we propose to utilize theoretical constraints to help predict market returns when in sample data is very noisy and creates model uncertainty for the investors. The constraints are also incorporated by Bayesian method. We show in the out-of-sample forecast experiment that models with theoretical constraints produce better forecasts.

Three Essays on Analysts' Earnings Forecast Dispersion and Stock Returns

Author : Jorida Papakroni
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (862 download)

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Book Synopsis Three Essays on Analysts' Earnings Forecast Dispersion and Stock Returns by : Jorida Papakroni

Download or read book Three Essays on Analysts' Earnings Forecast Dispersion and Stock Returns written by Jorida Papakroni and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Dissertation Abstracts International

Author :
Publisher :
ISBN 13 :
Total Pages : 640 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Dissertation Abstracts International by :

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2004 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstracts of dissertations available on microfilm or as xerographic reproductions.

Predicting Returns and Changes in Real Activity in Emerging and Developed Economies

Author : Jesper Rangvid
Publisher :
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Predicting Returns and Changes in Real Activity in Emerging and Developed Economies by : Jesper Rangvid

Download or read book Predicting Returns and Changes in Real Activity in Emerging and Developed Economies written by Jesper Rangvid and published by . This book was released on 2001 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates predictions of changes in real activity and stock returns in 24 developed and emerging economies. A simple general equilibrium version of an intertemporal capital asset pricing model (I-CAPM) motivates the analysis. The model implies that share prices will be proportional to real activity, i.e. real activity and share prices are driven by the same time-series process. Furthermore, in an efficient market where investors have a desire to smooth out predictable changes in consumption, and consumption is linked to real activity, returns will be predictable when changes in real activity are predictable, i.e. the same instruments that predict changes in real activity can predict returns, and the predictions of returns should be proportional to the predictions of real activity.From the I-CAPM, three empirical questions are derived and tested: (i) are the series for real activity and share prices cointegrated and thus driven by the same common stochastic trend?, (ii) do the same variables predict both changes in real activity and returns?, and (iii) are the predictions of returns proportional to the predictions of changes in real activity? The empirical evidence in support of (i) cointegration and (ii) common predictability is strong, whereas the evidence against (iii) proportional predictions is equally strong. Finally, special attention is paid to the ability of the deviations from the cointegration relations to predict changes in real activity and returns.

Artificial Intelligence in Asset Management

Author : Söhnke M. Bartram
Publisher : CFA Institute Research Foundation
ISBN 13 : 195292703X
Total Pages : 95 pages
Book Rating : 4.9/5 (529 download)

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Book Synopsis Artificial Intelligence in Asset Management by : Söhnke M. Bartram

Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Handbook of Quantitative Finance and Risk Management

Author : Cheng-Few Lee
Publisher : Springer Science & Business Media
ISBN 13 : 0387771174
Total Pages : 1700 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Handbook of Quantitative Finance and Risk Management by : Cheng-Few Lee

Download or read book Handbook of Quantitative Finance and Risk Management written by Cheng-Few Lee and published by Springer Science & Business Media. This book was released on 2010-06-14 with total page 1700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.

Game-Theoretic Foundations for Probability and Finance

Author : Glenn Shafer
Publisher : John Wiley & Sons
ISBN 13 : 1118547934
Total Pages : 483 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Game-Theoretic Foundations for Probability and Finance by : Glenn Shafer

Download or read book Game-Theoretic Foundations for Probability and Finance written by Glenn Shafer and published by John Wiley & Sons. This book was released on 2019-03-21 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Game-theoretic probability and finance come of age Glenn Shafer and Vladimir Vovk’s Probability and Finance, published in 2001, showed that perfect-information games can be used to define mathematical probability. Based on fifteen years of further research, Game-Theoretic Foundations for Probability and Finance presents a mature view of the foundational role game theory can play. Its account of probability theory opens the way to new methods of prediction and testing and makes many statistical methods more transparent and widely usable. Its contributions to finance theory include purely game-theoretic accounts of Ito’s stochastic calculus, the capital asset pricing model, the equity premium, and portfolio theory. Game-Theoretic Foundations for Probability and Finance is a book of research. It is also a teaching resource. Each chapter is supplemented with carefully designed exercises and notes relating the new theory to its historical context. Praise from early readers “Ever since Kolmogorov's Grundbegriffe, the standard mathematical treatment of probability theory has been measure-theoretic. In this ground-breaking work, Shafer and Vovk give a game-theoretic foundation instead. While being just as rigorous, the game-theoretic approach allows for vast and useful generalizations of classical measure-theoretic results, while also giving rise to new, radical ideas for prediction, statistics and mathematical finance without stochastic assumptions. The authors set out their theory in great detail, resulting in what is definitely one of the most important books on the foundations of probability to have appeared in the last few decades.” – Peter Grünwald, CWI and University of Leiden “Shafer and Vovk have thoroughly re-written their 2001 book on the game-theoretic foundations for probability and for finance. They have included an account of the tremendous growth that has occurred since, in the game-theoretic and pathwise approaches to stochastic analysis and in their applications to continuous-time finance. This new book will undoubtedly spur a better understanding of the foundations of these very important fields, and we should all be grateful to its authors.” – Ioannis Karatzas, Columbia University

American Doctoral Dissertations

Author :
Publisher :
ISBN 13 :
Total Pages : 800 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis American Doctoral Dissertations by :

Download or read book American Doctoral Dissertations written by and published by . This book was released on 1994 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of the Economics of Finance

Author : G. Constantinides
Publisher : Elsevier
ISBN 13 : 9780444513632
Total Pages : 698 pages
Book Rating : 4.5/5 (136 download)

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Book Synopsis Handbook of the Economics of Finance by : G. Constantinides

Download or read book Handbook of the Economics of Finance written by G. Constantinides and published by Elsevier. This book was released on 2003-11-04 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Arbitrage, State Prices and Portfolio Theory / Philip h. Dybvig and Stephen a. Ross / - Intertemporal Asset Pricing Theory / Darrell Duffle / - Tests of Multifactor Pricing Models, Volatility Bounds and Portfolio Performance / Wayne E. Ferson / - Consumption-Based Asset Pricing / John y Campbell / - The Equity Premium in Retrospect / Rainish Mehra and Edward c. Prescott / - Anomalies and Market Efficiency / William Schwert / - Are Financial Assets Priced Locally or Globally? / G. Andrew Karolyi and Rene M. Stuli / - Microstructure and Asset Pricing / David Easley and Maureen O'hara / - A Survey of Behavioral Finance / Nicholas Barberis and Richard Thaler / - Derivatives / Robert E. Whaley / - Fixed-Income Pricing / Qiang Dai and Kenneth J. Singleton.

Financial Modeling Under Non-Gaussian Distributions

Author : Eric Jondeau
Publisher : Springer Science & Business Media
ISBN 13 : 1846286964
Total Pages : 541 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Financial Modeling Under Non-Gaussian Distributions by : Eric Jondeau

Download or read book Financial Modeling Under Non-Gaussian Distributions written by Eric Jondeau and published by Springer Science & Business Media. This book was released on 2007-04-05 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.