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Risk Aversion and Portfolio Selection in a Continuous-Time Model

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  • Jianming Xia

Abstract

The comparative statics of the optimal portfolios across individuals is carried out for a continuous-time complete market model, where the risky assets price process follows a joint geometric Brownian motion with time-dependent and deterministic coefficients. It turns out that the indirect utility functions inherit the order of risk aversion (in the Arrow-Pratt sense) from the von Neumann-Morgenstern utility functions, and therefore, a more risk-averse agent would invest less wealth (in absolute value) in the risky assets.

Suggested Citation

  • Jianming Xia, 2008. "Risk Aversion and Portfolio Selection in a Continuous-Time Model," Papers 0805.0618, arXiv.org, revised Dec 2011.
  • Handle: RePEc:arx:papers:0805.0618
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    File URL: http://arxiv.org/pdf/0805.0618
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    Cited by:

    1. Phillip Monin & Thaleia Zariphopoulou, 2014. "On the Optimal Wealth Process in a Log-Normal Market: Applications to Risk Management," Staff Discussion Papers 14-01, Office of Financial Research, US Department of the Treasury.
    2. Dejian Tian & Weidong Tian, 2016. "Comparative statics under κ-ambiguity for log-Brownian asset prices," International Journal of Economic Theory, The International Society for Economic Theory, vol. 12(4), pages 361-378, December.
    3. Sona Kilianova & Daniel Sevcovic, 2013. "Transformation Method for Solving Hamilton-Jacobi-Bellman Equation for Constrained Dynamic Stochastic Optimal Allocation Problem," Papers 1307.3672, arXiv.org, revised Jul 2013.
    4. Tianxiao Wang, 2012. "Risk minimizing of derivatives via dynamic g-expectation and related topics," Papers 1208.2068, arXiv.org.
    5. Černý, Aleš & Melicherčík, Igor, 2020. "Simple explicit formula for near-optimal stochastic lifestyling," European Journal of Operational Research, Elsevier, vol. 284(2), pages 769-778.
    6. Lijun Bo & Yijie Huang & Xiang Yu, 2023. "An extended Merton problem with relaxed benchmark tracking," Papers 2304.10802, arXiv.org, revised Mar 2024.

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