Seung Ahn

About

Seung Ahn's main research areas are panel data analysis, empirical asset pricing models, and factor models.

Research topics

• Computer Science
• Mathematics
• Econometrics
• Statistics
• Artificial Intelligence
• Applied mathematics

Selected publications

• Eigenvalue Ratio Test for the Number of Factors

  Econometrica · 2013-01-01 · 946 citations

  article1st authorCorresponding

  This paper proposes two new estimators for determining the number of factors (r) in static approximate factor models. We exploit the well-known fact that the r largest eigenvalues of the variance matrix of N response variables grow unboundedly as N increases, while the other eigenvalues remain bounded. The new estimators are obtained simply by maximizing the ratio of two adjacent eigenvalues. Our simulation results provide promising evidence for the two estimators.

  PublisherDOI

• Panel data models with multiple time-varying individual effects

  Journal of Econometrics · 2013-01-09 · 216 citations

  article1st authorCorresponding
  PublisherDOI

• Beta Matrix and Common Factors in Stock Returns

  Journal of Financial and Quantitative Analysis · 2018-03-19 · 33 citations

  article1st authorCorresponding

  We consider the estimation methods for the rank of a beta matrix corresponding to a multifactor model and study which method would be appropriate for data with a large number of assets. Our simulation results indicate that a restricted version of Cragg and Donald’s (1997) Bayesian information criterion estimator is quite reliable for such data. We use this estimator to analyze some selected asset pricing models with U.S. stock returns. Our results indicate that the beta matrix from many models f…

  PublisherDOI

• Major League Baseball Attendance

  Journal of Sports Economics · 2014-05-26 · 25 citations

  article1st authorCorresponding

  Although Major League Baseball has a long history, most studies of attendance have focused on recent years because important explanatory data, such as ticket prices, are often missing for earlier periods. This study fills gaps in the data by analyzing individual team attendance records between 1904 and 2012. If important missing variables are determined using common factors that can influence between-team attendance, the attendance function can be estimated by a panel factor model. Our results i…

  PublisherDOI

• Eigenvalue Ratio Test for the Number of Factors

  SSRN Electronic Journal · 2013-05-01 · 21 citations

  articleOpen access1st authorCorresponding

  This paper proposes two new estimators for determining the number of factors (r) in static approximate factor models. We exploit the well-known fact that the r largest eigenvalues of the variance matrix of N response variables grow unboundedly as N increases, while the other eigenvalues remain bounded. The new estimators are obtained simply by maximizing the ratio of two adjacent eigenvalues. Our simulation results provide promising evidence for the two estimators.

  Publisher

Frequent coauthors

• M. Fabricio Perez

  Wilfrid Laurier University

  13 shared

• Young Hoon Lee

  13 shared

• Peter Schmidt

  Michigan State University

  12 shared

• Christopher Gadarowski

  12 shared

• Alex R. Horenstein

  John von Neumann University

  8 shared

• Hyungsik Roger Moon

  Yonsei University

  8 shared

• Josef C. Brada

  4 shared

• Stephan Dieckmann

  4 shared

Labs

• Econometric ModelingPI

Education

• Ph.D.

  Michigan State University

  1990

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