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Asset Pricing Test Using Alternative Sets of Portfolios: Evidence from India

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  • Sudipta Das

    (Indian Institute of Information Technology)

Abstract

Empirical test of asset-pricing models are typically performed on portfolios based on firm-characteristics such as size and book-to-market ratios etc. However, because of their strong factor structure, the characteristic sorted portfolios do not provide a sufficient test for asset pricing models. In recent, the appropriateness to use characteristics sorted portfolios has been debated. Literature suggests various alternative test portfolios sorted by other attributes to improve the empirical tests. To address this issue, we construct three sets of test portfolios sorted by firm beta, volatility, and clustering method to test various asset pricing models. We examine whether portfolios sorted by the above methods can improve the explanatory power of various alternative asset pricing models. Our test results suggest that for unconditional models, the statistical significance and estimated risk premiums depend on the choice of tests portfolios. The conditional model has more power to explain the variation of average returns than the unconditional model.

Suggested Citation

  • Sudipta Das, 2019. "Asset Pricing Test Using Alternative Sets of Portfolios: Evidence from India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(3), pages 339-354, September.
    • Handle: RePEc:kap:apfinm:v:26:y:2019:i:3:d:10.1007_s10690-018-09268-8
    DOI: 10.1007/s10690-018-09268-8
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    More about this item

    Keywords

    Idiosyncratic volatility; k-Means clustering; Fama–MacBeth regression; Kalman filter;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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