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Journal ArticleDOI

Eigenvalue Ratio Test for the Number of Factors

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TLDR
In this paper, two new estimators for determining the number of factors (r) in static approximate factor models were proposed, based on the well-known fact that the largest eigenvalues of the variance matrix of N response variables grow unboundedly as N increases.
Abstract
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

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BookDOI

Dynamic Factor Models

TL;DR: In this article, the authors present a survey of dynamic factor models (DFMs), a class of models that has received considerable attention in the past decade because of their ability to model simultaneously and consistently data sets in which the number of series exceeds the total number of time series observations.
Journal ArticleDOI

Cross-Sectional Dependence in Panel Data Analysis

TL;DR: In this article, the authors provide an overview of the existing literature on panel data models with error cross-sectional dependence (CSD), and distinguish between weak and strong CSD and link these concepts to the spatial and factor structure approaches.
Journal ArticleDOI

An overview of the estimation of large covariance and precision matrices

TL;DR: In this article, the authors provide a selective review of several recent developments on the estimation of large covariance and precision matrices, focusing on two general approaches: a rank-based method and a factor-model based method.

Large Panel Data Models with Cross-Sectional Dependence: A Surevey

TL;DR: In this paper, the authors provide an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence, including static and dynamic models with weakly exogenous regressors.
Book ChapterDOI

Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics

TL;DR: In this paper, the authors provide an overview of dynamic factor models (DFMs), their estimation, and their uses in empirical macroeconomics, including the use of DFMs for analysis of structural shocks.
References
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Journal ArticleDOI

Common risk factors in the returns on stocks and bonds

TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.
Journal ArticleDOI

Capital asset prices: a theory of market equilibrium under conditions of risk*

TL;DR: In this paper, the authors present a body of positive microeconomic theory dealing with conditions of risk, which can be used to predict the behavior of capital marcets under certain conditions.
Journal ArticleDOI

The scree test for the number of factors

TL;DR: The Scree Test for the Number Of Factors this paper was first proposed in 1966 and has been used extensively in the field of behavioral analysis since then, e.g., in this paper.
Journal ArticleDOI

Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency

TL;DR: In this article, the authors show that strategies that buy stocks that have performed well in the past and sell stocks that had performed poorly in past years generate significant positive returns over 3- to 12-month holding periods.
Book ChapterDOI

The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets

TL;DR: In this article, the problem of selecting optimal security portfolios by risk-averse investors who have the alternative of investing in risk-free securities with a positive return or borrowing at the same rate of interest and who can sell short if they wish is discussed.
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