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How risky is a random process?

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  • Shah, Sudhir A.

Abstract

The riskiness of random processes is compared by (a) employing a decision theoretic equivalence between processes and lotteries on path-spaces to identify the riskiness of the former with that of the latter, and (b) using the theory of comparative riskiness of lotteries over vector spaces to compare the riskiness of lotteries on a given path-space. We derive the equivalence used in step (a) and contribute a new criterion to the theory applied in step (b). The validity of the new criterion, which applies second order stochastic dominance to utility distributions, is established by showing its equivalence to the benchmark decision theoretic criterion when comparing the riskiness of lotteries over any vector space. We demonstrate the theory’s tractability via diverse economic applications.

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  • Shah, Sudhir A., 2017. "How risky is a random process?," Journal of Mathematical Economics, Elsevier, vol. 72(C), pages 70-81.
    • Handle: RePEc:eee:mateco:v:72:y:2017:i:c:p:70-81
    DOI: 10.1016/j.jmateco.2017.06.005
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    Cited by:

    1. Sudhir A. Shah, 2024. "Money-metric valuation of assets," Working papers 347, Centre for Development Economics, Delhi School of Economics.
    2. Stelios Arvanitis, 2021. "Stochastic dominance efficient sets and stochastic spanning," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 401-409, June.
    3. Wang, Huiqi & Yuan, Wei & Yuan, George, 2022. "The mechanism for SMEs growth by applying stochastic dynamical approach," Finance Research Letters, Elsevier, vol. 48(C).

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