An Empirical Study Of The Fama And French Three Factor Model

By using the methodology of the Cointegration test to focus on the long run relationship and conditional volatility by GARCH model to focus on risk relationship, the results suggest that i) the value premium is related to the changes of fundamental risk; ii) there is an asymmetric effect on the price of the value stock and growth stock under different business conditions; iii) and the three risk factors are driven by a similar source of macroeconomic activity change, but the interactive relationship between these three risk factors is essential in explaining the rates of return, thus, they should be used together. Overall, the results in this thesis support the view that the Fama and French three-factor model is a strong model in explaining rates of return, and that the value premium is generated from systemic risk and should be used in the equilibrium asset pricing model. The finding is useful for academics and practitioners alike.

This research compares the performances of the Fama-French three-factor and Carhart four-factor models on the Indonesian stock market. It employs ordinary least square (OLS) with monthly time-series data from July 2005 to June 2015. The results document that the Carhart four-factor model performs better than Fama-French three-factor model in explaining the portfolio excess returns in Indonesia. The momentum factor displays a weak effect on the portfolio excess returns. The results are robust to the equally-weighted method.

A comprehensive guide to financial econometrics Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed. Svetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale University’s School of Management. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm The Intertek Group. Teo Jasic, PhD, (Frankfurt, Germany) is a senior manager with a leading international management consultancy firm in Frankfurt.

The thesis tests performances of Capital Asset Pricing Model and Fama-French Three-Factor Model. Through an empirical study on the US stocks from January 2000 to August 2017, the thesis demonstrates that Fama-French Three-Factor model performs better than Capital Asset Pricing Model.

Winner of the prestigious Paul A. Samuelson Award for scholarly writing on lifelong financial security, John Cochrane's Asset Pricing now appears in a revised edition that unifies and brings the science of asset pricing up to date for advanced students and professionals. Cochrane traces the pricing of all assets back to a single idea--price equals expected discounted payoff--that captures the macro-economic risks underlying each security's value. By using a single, stochastic discount factor rather than a separate set of tricks for each asset class, Cochrane builds a unified account of modern asset pricing. He presents applications to stocks, bonds, and options. Each model--consumption based, CAPM, multifactor, term structure, and option pricing--is derived as a different specification of the discounted factor. The discount factor framework also leads to a state-space geometry for mean-variance frontiers and asset pricing models. It puts payoffs in different states of nature on the axes rather than mean and variance of return, leading to a new and conveniently linear geometrical representation of asset pricing ideas. Cochrane approaches empirical work with the Generalized Method of Moments, which studies sample average prices and discounted payoffs to determine whether price does equal expected discounted payoff. He translates between the discount factor, GMM, and state-space language and the beta, mean-variance, and regression language common in empirical work and earlier theory. The book also includes a review of recent empirical work on return predictability, value and other puzzles in the cross section, and equity premium puzzles and their resolution. Written to be a summary for academics and professionals as well as a textbook, this book condenses and advances recent scholarship in financial economics.

In the epic conclusion to the Fallen Kings Cycle, set in the world of The Chronicles of the Necromancer, war has come to the Winter Kingdoms. Summoner-King Tris Drayke takes what remains of his army north for a war he is ill-prepared to fight, as reports from spies confirm Tris's worst fear. A new threat rises across the sea: a dark summoner who intends to make the most of the Winter Kingdoms' weakness. In Isencroft, Kiara's father is assassinated, and she has no choice except to return and claim the crown. But she must leave behind her husband and their infant son to face the dark power that threatens her rule. The Dread will rise. Kings will fall. The Chronicles of the Necromancer The Summoner The Blood King Dark Haven Dark Lady’s Chosen Fallen Kings Cycle The Sworn The Drea

This empirical study is conducted to apply the Fama French three-factor model in the Australian context using the most recent daily data for the period of 5 years from July 2009 to May 2015. The focus of this study is on various approaches of portfolio formation adopted in previous empirical studies in Australia and overseas. Three scenarios are constructed to assess the robustness of the estimated coefficients from the model. The approach proposed by Fama and Macbeth (1973) - the two-stage cross-sectional regression technique is adopted in this paper. The findings from this study under various scenarios and various approaches to portfolio formations across portfolios are mixed. This study finds that only book-to-market factor is priced in Australia. However, there is a negative relationship between this factor and a return of a stock which is in contrast with an expectation of the Fama French three-factor model. As such, a claim from a recent study in Australia that for the first time, Fama French three-factor model produces a consistent outcome is simply exaggerated. It can be argued that this new finding is an outcome of another “data mining” which is generally labelled for the findings from the Fama French three-factor model.

This book proposes new methods to build optimal portfolios and to analyze market liquidity and volatility under market microstructure effects, as well as new financial risk measures using parametric and non-parametric techniques. In particular, it investigates the market microstructure of foreign exchange and futures markets.

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

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.