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Jumps in Rank and Expected Returns. Introducing Varying Cross-sectional Risk

Author

Listed:
  • Santosh Mishra
  • Gloria Gonzalez-Rivera
  • Tae-Hwy Lee

Abstract

Decision theorists claim that an ordinal measure of risk may be sufficient for an agent to make a rational choice under uncertainty. We propose a measure of financial risk, namely the Varying Cross-sectional Risk (VCR), that is based on a ranking of returns. VCR is defined as the probability of a sharp jump over time in the position of an asset return within the cross-sectional return distribution of the assets that constitute the market, which is represented by the Standard and Poor's 500 Index (SP500). We model the joint dynamics of the cross-sectional position and the asset return by analyzing (1) the marginal probability distribution of a sharp jump in the cross-sectional position within the context of a duration model, and (2) the probability distribution of the asset return conditional on a jump, for which we specify different return dynamics depending upon whether or not a jump has taken place. As a result, the marginal probability distribution of returns is a mixture of distributions. The performance of our model is assessed in an out-of-sample exercise. We design a set of trading rules that are evaluated according to their profitability and riskiness. A trading rule based on our VCR model is dominant providing superior mean trading returns and accurate estimation of the Value-at-Risk.

Suggested Citation

  • Santosh Mishra & Gloria Gonzalez-Rivera & Tae-Hwy Lee, 2004. "Jumps in Rank and Expected Returns. Introducing Varying Cross-sectional Risk," Econometric Society 2004 North American Winter Meetings 356, Econometric Society.
  • Handle: RePEc:ecm:nawm04:356
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    File URL: http://repec.org/esNAWM04/up.26903.1049135451.pdf
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    References listed on IDEAS

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    1. Tae-Hwy Lee & Yong Bao & Burak Saltoglu, 2006. "Evaluating predictive performance of value-at-risk models in emerging markets: a reality check," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(2), pages 101-128.
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    More about this item

    Keywords

    Duration; Mixture of distributions; Nonlinearity; Reality check; Trading rule; VaR;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G0 - Financial Economics - - General

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