Notes for Empirical Finance (Presentation Slides)

2020 ◽  
Author(s):  
Rui Dai
Keyword(s):  
Empirical Finance

scholarly journals An Evaluation of Alternative Multiple Testing Methods for Finance Applications*

2020 ◽  
Vol 10 (2) ◽  
pp. 199-248 ◽  
Author(s):  
Campbell R Harvey ◽  
Yan Liu ◽  
Alessio Saretto
Keyword(s):  
Regression Model ◽  
Multiple Testing ◽  
Empirical Finance ◽  
Relative Performance ◽  
Testing Methods ◽  
Multiple Tests ◽  
High Profile ◽  
Simple Regression Model ◽  
Testing Environments ◽  
Simple Regression

Abstract In almost every area of empirical finance, researchers confront multiple tests. One high-profile example is the identification of outperforming investment managers, many of whom beat their benchmarks purely by luck. Multiple testing methods are designed to control for luck. Factor selection is another glaring case in which multiple tests are performed, but numerous other applications do not receive as much attention. One important example is a simple regression model testing five variables. In this case, because five variables are tried, a t-statistic of 2.0 is not enough to establish significance. Our paper provides a guide to various multiple testing methods and details a number of applications. We provide simulation evidence on the relative performance of different methods across a variety of testing environments. The goal of our paper is to provide a menu that researchers can choose from to improve inference in financial economics. (JEL G0, G1, G3, G5, M4, C1)

THE ECONOMETRICS OF FINANCIAL MARKETS

1998 ◽  
Vol 2 (4) ◽  
pp. 559-562 ◽  
Author(s):  
John Y. Campbell ◽  
Andrew W. Lo ◽  
A. Craig MacKinlay ◽  
Robert F. Whitelaw
Keyword(s):  
Quantitative Analysis ◽  
Asset Pricing ◽  
Financial Markets ◽  
Corporate Finance ◽  
Foreign Exchange ◽  
Empirical Finance ◽  
Econometric Methods ◽  
Recent Addition ◽  
Exchange Markets ◽  
Derivatives Markets

This book is an ambitious effort by three well-known and well-respected scholars to fill an acknowledged void in the literature—a text covering the burgeoning field of empirical finance. As the authors note in the preface, there are several excellent books covering financial theory at a level suitable for a Ph.D. class or as a reference for academics and practitioners, but there is little or nothing similar that covers econometric methods and applications. Perhaps the closest existing text is the recent addition to the Wiley Series in Financial and Quantitative Analysis. written by Cuthbertson (1996). The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure. The level of anticipation preceding publication can be partly measured by the fact that at least three reviews (including this one) have appeared since the book arrived. Moreover, in their reviews, both Harvey (1998) and Tiso (1998) comment on the need for such a text, a sentiment that has been echoed by numerous finance academics.

scholarly journals The Fundamental Equation in Tourism Finance

2015 ◽  
Vol 8 (4) ◽  
pp. 369-374 ◽  
Author(s):  
Michael McAleer
Keyword(s):  
Fundamental Equation ◽  
Practical Method ◽  
Financial Econometrics ◽  
Tourism Industry ◽  
Empirical Finance ◽  
Energy Industry ◽  
Tourism Research ◽  
The World ◽  
Tourism Expenditure ◽  
Oil Gas

The purpose of the paper is to present the fundamental equation in tourism finance that connects tourism research to empirical finance and financial econometrics. The energy industry, which includes, oil, gas and bio-energy fuels, together with the tourism industry, are two of the most important industries in the world today in terms of employment and generating income. The primary purpose in attracting domestic and international tourists to a country, region or city is to maximize tourism expenditure. The paper will concentrate on daily tourism expenditure, regardless of whether such data might be readily available. If such data are not available, a practical method is presented to calculate the appropriate data.

Replicating Anomalies

2018 ◽  
Vol 33 (5) ◽  
pp. 2019-2133 ◽  
Author(s):  
Kewei Hou ◽  
Chen Xue ◽  
Lu Zhang
Keyword(s):  
Failure Rate ◽  
Capital Markets ◽  
Empirical Finance ◽  
Single Test ◽  
Significance Level ◽  
Multiple Test ◽  
Oxford University ◽  
Editorial Decision ◽  
Published Paper ◽  
Data Library

Abstract Most anomalies fail to hold up to currently acceptable standards for empirical finance. With microcaps mitigated via NYSE breakpoints and value-weighted returns, 65% of the 452 anomalies in our extensive data library, including 96% of the trading frictions category, cannot clear the single test hurdle of the absolute $t$-value of 1.96. Imposing the higher multiple test hurdle of 2.78 at the 5% significance level raises the failure rate to 82%. Even for replicated anomalies, their economic magnitudes are much smaller than originally reported. In all, capital markets are more efficient than previously recognized. Received June 12, 2017; editorial decision October 29, 2018 by Editor Stijn Van Nieuwerburgh. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

The Present and Future of Empirical Finance

2005 ◽  
Vol 61 (4) ◽  
pp. 15-18
Author(s):  
Clive W.J. Granger
Keyword(s):  
Empirical Finance
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