English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper re-examines the problem of estimating risk premia in linear factorpricing models. Typically, the data used in the empirical literature arecharacterized by weakness of some pricing factors, strong cross-sectionaldependence in the errors, and (moderately) high cross-sectional dimensionality.Using an asymptotic framework where the number of assets/portfolios grows withthe time span of the data while the risk exposures of weak factors arelocal-to-zero, we show that the conventional two-pass estimation proceduredelivers inconsistent estimates of the risk premia. We propose a new estimationprocedure based on sample-splitting instrumental variables regression. Theproposed estimator of risk premia is robust to weak included factors and to thepresence of strong unaccounted cross-sectional error dependence. We derive themany-asset weak factor asymptotic distribution of the proposed estimator, showhow to construct its standard errors, verify its performance in simulations,and revisit some empirical studies.

Factor models with many assets: strong factors, weak factors, and the two-pass procedure