Journal ArticleDOI
Using principal component analysis to estimate a high dimensional factor model with high-frequency data
Yacine Ait-Sahalia,Dacheng Xiu +1 more
TLDR
In this article, the covariance matrix of a large portfolio of US equities is well represented by a low rank common structure with sparse residual matrix, and the proposed estimator largely outperforms the sample covariance estimator.About:
This article is published in Journal of Econometrics.The article was published on 2017-12-01. It has received 123 citations till now. The article focuses on the topics: Covariance matrix & Estimator.read more
Citations
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Journal ArticleDOI
Autoencoder asset pricing models
TL;DR: This model retrofits the workhorse unsupervised dimension reduction device from the machine learning literature – autoencoder neural networks – to incorporate information from covariates along with returns themselves, and delivers estimates of nonlinear conditional exposures and the associated latent factors.
Journal ArticleDOI
Principal Component Analysis of High-Frequency Data
Yacine Ait-Sahalia,Dacheng Xiu +1 more
TL;DR: In this article, the authors develop a methodology to conduct principal component analysis at high frequency and construct estimators of realized eigenvalues, eigenvectors, and principal components.
Journal ArticleDOI
Simultaneous multiple change-point and factor analysis for high-dimensional time series
TL;DR: In this paper, the authors proposed the first comprehensive treatment of high-dimensional time series factor models with multiple change-points in their second-order structure, using wavelets to estimate the number and locations of changepoints consistently as well as identifying whether they originate in the common or idiosyncratic components.
Journal ArticleDOI
Estimating Latent Asset-Pricing Factors
TL;DR: In this paper, the authors developed an estimator for latent factors in a large-dimensional panel of financial data that can explain expected excess returns. But their estimator cannot find asset-pricing factors, which cannot be detected with PCA, even if a large amount of data is available.
Journal ArticleDOI
Large-dimensional factor modeling based on high-frequency observations
TL;DR: In this article, the authors developed a statistical theory to estimate an unknown factor structure based on financial high-frequency data and derived an estimator for the number of factors and consistent and asymptotically mixed-normal estimators of the loadings and factors under the assumption of a large number of cross-sectional and highfrequency observations.
References
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Journal ArticleDOI
Common risk factors in the returns on stocks and bonds
Eugene F. Fama,Kenneth R. French +1 more
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
Introduction to Multivariate Statistical Analysis.
William G. Madow,T. W. Anderson +1 more
Journal ArticleDOI
The arbitrage theory of capital asset pricing
TL;DR: Ebsco as mentioned in this paper examines the arbitrage model of capital asset pricing as an alternative to the mean variance pricing model introduced by Sharpe, Lintner and Treynor.
Journal ArticleDOI
An intertemporal capital asset pricing model
TL;DR: In this article, an intertemporal model for the capital market is deduced from portfolio selection behavior by an arbitrary number of investors who aot so as to maximize the expected utility of lifetime consumption and who can trade continuously in time.
Journal ArticleDOI
Economic Forces and the Stock Market
TL;DR: In this paper, the authors test whether innovations in macroeconomic variables are risks that are rewarded in the stock market, and they find that these sources of risk are significantly priced and neither the market portfolio nor aggregate consumption are priced separately.
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