On The Robustness Of The Extended Fama French Three Factor Model

The aim of this paper is to examine the validity of the four-factor asset pricing as a comparison the standard Fama-French three factor model using U.S. monthly stock return data from period January 1963 to December 2010. Monthly stock return are constructed into 25 portfolio while the four-factor model includes the market factor (beta), the size factor (SMB), the book-to-market factor (HML), and the 'momentum' factor (MOM) which represents winners minus losers in terms of returns. Time series regressions following Fama and French (1993) are employed which includes the three-factor model as well as the four-factor model. Results indicated that the four-factor model to some extent have significant capability in explaining the variations in average excess stock return which consistent with Carhart (1997). R2 from the four-factor model is just slightly higher than the three factor model yet it provides indicative for the robustness of the model. Meanwhile, the January seasonals are also able to be absorbed by the risk factors including the market, SMB, HML, and MOM. Since the four-factor model seems capable in explaining the variation of the stock returns then application of this model in emerging markets may provide guidance for investor in understanding the market condition.

We examine the robustness of the Fama-French three-factor model in several bear and bull market periods. Data on bull and bear market periods are from the website of Global Financial Data. The data on the monthly returns of the 25 Fama French portfolios and the explanatory variablesmR, SMB, and HML are taken from the website of Dr. Kenneth French. We test for the significance of the individual regression parameters as well as for the equality of the coefficient vectors in each of the adjacent bear-bull periods. To make sure that our tests are not influenced by heteroskadisticity we use Toyoda's test to test the equality of the coefficient vectors in each of the adjacent bull-bear periods. We find that the model performs equally well in both bear and bull periods. In comparison to earlier bull-bear periods, however, the coefficient of determination decreases significantly in later periods. Furthermore, using cumulative sum of squares of recursive residuals and log likelihood ratio techniques, we find a structural change in the model in the year 2000. We use the Welch test to identify which regression parameters induce this structural change. We find that all the coefficients associated with explanatory variables undergo significant changes; however, the constant term remains insignificant. We conclude that the parameters of the Fama-French three-factor model are generally not influenced by bear and bull market conditions. This finding may make the FF three-factor model more usefulőthe prediction of future bull-bear market period may become redundant in estimating the risk premium. The regime change in the FF three-factor model in the year 2000 indicates that one should use post-1999 data to compute the parameters of the FF three-factor model to estimate the risk premium.

The new M&A bible. Few actions can change the value of a company—and its competitive future—as quickly and dramatically as an acquisition. Yet most companies fail to create shareholder value from these deals, and in many cases they destroy it. It doesn't have to be this way. In The Synergy Solution, Deloitte's Mark Sirower and Jeff Weirens show acquirers how to develop and execute an M&A strategy—end to end—that not only avoids the pitfalls that so many companies fall into but also creates real, long-term shareholder value. This strategy includes how to: Become a prepared "always on" acquirer Test the investment thesis and DCF valuation of a deal Plan for a successful Announcement Day, and properly communicate synergy promises to investors and other stakeholders Realize those promised synergies through integration planning and post-close execution Manage change and build a new, combined organization Sirower and Weirens provide invaluable background to those considering M&A, laying out the issues they have to consider, how to analyze them, and how to plan and execute the deal effectively. They also show those who have already started the process of M&A how to maximize their chances of success. There's an art and a science to getting mergers and acquisitions right, and this powerful book provides the insights and strategies acquirers need to find success at every stage of an often complex and perilous process.

A supplement for junior/senior and graduate level courses in Investments, Behavioral Finance Theory, and related courses. Teach the concepts that expose the inefficiency of capital markets. The New Finance is a comprehensive and organized collection of evidence and arguments that develop a persuasive case for an inefficient, complex and, at times, nearly chaotic stock market. This brief text also shows students how the complexity and uniqueness of investor interactions have important market pricing consequences. The fourth edition includes two new chapters on the real determinants of expected stock returns and the nature of stock volatility that the Financial Crisis of 2008 has exposed.

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.

DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth DIY Financial Advisor is a synopsis of our research findings developed while serving as a consultant and asset manager for family offices. By way of background, a family office is a company, or group of people, who manage the wealth a family has gained over generations. The term 'family office' has an element of cachet, and even mystique, because it is usually associated with the mega-wealthy. However, practically speaking, virtually any family that manages its investments—independent of the size of the investment pool—could be considered a family office. The difference is mainly semantic. DIY Financial Advisor outlines a step-by-step process through which investors can take control of their hard-earned wealth and manage their own family office. Our research indicates that what matters in investing are minimizing psychology traps and managing fees and taxes. These simple concepts apply to all families, not just the ultra-wealthy. But can—or should—we be managing our own wealth? Our natural inclination is to succumb to the challenge of portfolio management and let an 'expert' deal with the problem. For a variety of reasons we discuss in this book, we should resist the gut reaction to hire experts. We suggest that investors maintain direct control, or at least a thorough understanding, of how their hard-earned wealth is managed. Our book is meant to be an educational journey that slowly builds confidence in one's own ability to manage a portfolio. We end our book with a potential solution that could be applicable to a wide-variety of investors, from the ultra-high net worth to middle class individuals, all of whom are focused on similar goals of preserving and growing their capital over time. DIY Financial Advisor is a unique resource. This book is the only comprehensive guide to implementing simple quantitative models that can beat the experts. And it comes at the perfect time, as the investment industry is undergoing a significant shift due in part to the use of automated investment strategies that do not require a financial advisor's involvement. DIY Financial Advisor is an essential text that guides you in making your money work for you—not for someone else!

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.

This study investigates the performance of four-factor asset pricing model using Hong Kong stock returns. Our four-factor model is constructed by adding a momentum facgtor into the Fama and French's (1993) three-factor model. We find that the four-factor model does well in explaining return variation using Hong Kong data. Our results show evidence that all the four factors are significant in the model and intercepts are not significant. In addition, the reasonably high values of adjusted R squared and the insignificance of an additional explanatory variable of residula standard deviation provide supportive evidence to the model. The robustness of the model is also checked for two effects: up- and down-market conditions and seasonal behavior.

The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material,especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.

A timely and authoritative guide to today's hottest new investment vehicles "Finally, a book that covers REITs from A to Z that is understandable to both the layperson and the expert alike. John Mullaney is one of the very few real estate analysts who can simplify this complex new asset class and make the compelling argument that securitized real estate will continue to have a bright future and belongs in everyone's portfolio." --Peter Wheeler, President and COO, Commonwealth Equity Services "REITs: Building Profits with Real Estate Investment Trusts is a well-written and informative book not only on REITs, but real estate in general. It is a must-read for financial advisors who want to help their clients benefit from some of the outstanding investment opportunities which currently exist in the REIT industry." --Ina Fritsch, President, Fritsch Financial Services "This book is an excellent guide through the various sectors in the REIT industry and the leading companies in the business. I would recommend it for any investor interested in learning about the industry and how to select the right real estate investment trusts for their portfolio." --Charles K. Barbo, Chairman and CEO, Shurgard Storage Centers "I firmly believe that investors who manage and choose their own investments should understand the product they are investing in. John Mullaney's book is a great source for such investors to learn about real estate investments, valuing REITs, and making sound investment decisions." --Anne C. Ravetti, Meridian Industrial Trust