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Author: Yoontae Jeon Publisher: ISBN: Category : Languages : en Pages :
Book Description
This dissertation contains three essays on observable covariates in option pricing. In the first essay, I propose firm-specific public news arrival from Factiva database as an observable covariate in equity options market and study how the public news arrival is priced. I first establish the empirical relationship between the firm-specific public news arrival and jumps in individual equity returns. Subsequently, I build a continuous-time stochastic volatility jump diffusion model where news arrivals driving the jump dynamics. When estimated on equity options data for 20 individual firms, the premia placed on jump frequency and size turn out to be consistent with the theories highlighting both positive and negative effects of public news arrival. The second essay, based on a joint work with Peter Christoffersen, Bruno Feunou and Chayawat Ornthanalai, studies how the stock market illiquidity affects the market crash risk. Our empirical approach is to estimate a continuous-time model with stochastic volatility and dynamic crash probability where stock market illiquidity is used as an observable covariate driving the crash probability. While the crash probability is time-varying, its dynamic depends only weakly on return variance once we include market illiquidity as an economic variable in the model. This finding suggests that the relationship between variance and jump risk found in the literature is largely due to their common exposure to market illiquidity. Our study highlights the importance of equity market frictions in index return dynamics and explains why prior studies find that crash risk increases with market uncertainty level. The third essay, based on a joint work with Peter Christoffersen and Bruno Feunou, proposes the realized jump variation measure constructed from the intraday S returns data as an observable covariate that helps pricing of index options. The volatility and jump intensity dynamics in the model are directly driven by model-free empirical measures of diffusive volatility and jump variation. Because the empirical measures are observed in discrete intervals, our option valuation model is cast in discrete time, allowing for straightforward filtering and estimation of the model. When estimated on S index options and returns the new model performs well compared with standard benchmarks.
Author: Yoontae Jeon Publisher: ISBN: Category : Languages : en Pages :
Book Description
This dissertation contains three essays on observable covariates in option pricing. In the first essay, I propose firm-specific public news arrival from Factiva database as an observable covariate in equity options market and study how the public news arrival is priced. I first establish the empirical relationship between the firm-specific public news arrival and jumps in individual equity returns. Subsequently, I build a continuous-time stochastic volatility jump diffusion model where news arrivals driving the jump dynamics. When estimated on equity options data for 20 individual firms, the premia placed on jump frequency and size turn out to be consistent with the theories highlighting both positive and negative effects of public news arrival. The second essay, based on a joint work with Peter Christoffersen, Bruno Feunou and Chayawat Ornthanalai, studies how the stock market illiquidity affects the market crash risk. Our empirical approach is to estimate a continuous-time model with stochastic volatility and dynamic crash probability where stock market illiquidity is used as an observable covariate driving the crash probability. While the crash probability is time-varying, its dynamic depends only weakly on return variance once we include market illiquidity as an economic variable in the model. This finding suggests that the relationship between variance and jump risk found in the literature is largely due to their common exposure to market illiquidity. Our study highlights the importance of equity market frictions in index return dynamics and explains why prior studies find that crash risk increases with market uncertainty level. The third essay, based on a joint work with Peter Christoffersen and Bruno Feunou, proposes the realized jump variation measure constructed from the intraday S returns data as an observable covariate that helps pricing of index options. The volatility and jump intensity dynamics in the model are directly driven by model-free empirical measures of diffusive volatility and jump variation. Because the empirical measures are observed in discrete intervals, our option valuation model is cast in discrete time, allowing for straightforward filtering and estimation of the model. When estimated on S index options and returns the new model performs well compared with standard benchmarks.
Author: Wayne Ferson Publisher: MIT Press ISBN: 0262039370 Category : Business & Economics Languages : en Pages : 497
Book Description
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.
Author: Anol Bhattacherjee Publisher: CreateSpace ISBN: 9781475146127 Category : Science Languages : en Pages : 156
Book Description
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Author: Aswath Damodaran Publisher: John Wiley & Sons ISBN: 1118808932 Category : Business & Economics Languages : en Pages : 663
Book Description
Aswath Damodaran, distinguished author, Professor of Finance, and David Margolis, Teaching Fellow at the NYU Stern School of Business, has delivered the newest edition of Applied Corporate Finance. This readable text provides the practical advice students and practitioners need rather than a sole concentration on debate theory, assumptions, or models. Like no other text of its kind, Applied Corporate Finance, 4th Edition applies corporate finance to real companies. It now contains six real-world core companies to study and follow. Business decisions are classified for students into three groups: investment, financing, and dividend decisions.
Author: Andrew Gelman Publisher: CRC Press ISBN: 1439840954 Category : Mathematics Languages : en Pages : 677
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Author: Yoontae Jeon
Author: Yoontae Jeon
Author: Wayne Ferson
Author: 
Author: David Frederik Schrager
Author: Anol Bhattacherjee
Author: Sung Ju Song
Author: Jacob Boudoukh
Author: Aswath Damodaran
Author: World Bank
Author: Andrew Gelman