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The intertemporal risk-return relation: A bivariate model approach

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  • Jiang, Xiaoquan
  • Lee, Bong-Soo
Abstract
This paper examines the intertemporal risk-return relation using a more sensible empirical specification that is motivated by two concerns: the theoretical risk-return relation is an ex ante relation and the empirical method used to detect the relation should be reliable. We measure both the expected excess return and conditional variance jointly using the common information set based on a bivariate moving average representation of excess returns and variances. As a result, we can detect a significant positive relation between the expected excess return and the conditional variance. We also find that the positive relation is robust.

Suggested Citation

  • Jiang, Xiaoquan & Lee, Bong-Soo, 2014. "The intertemporal risk-return relation: A bivariate model approach," Journal of Financial Markets, Elsevier, vol. 18(C), pages 158-181.
    • Handle: RePEc:eee:finmar:v:18:y:2014:i:c:p:158-181
    DOI: 10.1016/j.finmar.2013.02.002
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    2. Hao Liu & Shihan Shen & Tianyi Wang & Zhuo Huang, 2016. "Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect," China Economic Journal, Taylor & Francis Journals, vol. 9(2), pages 140-153, May.
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    More about this item

    Keywords

    Intertemporal risk-return relation; Bivariate moving average representation;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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