Researchers from Feng Chia University Describe Findings in Risk Management (A Mean-preserving Increase In Ambiguity and Portfolio Choices)

2019 JUN 20 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A new study on Risk Management is now available. According to news originating from Taichung, Taiwan, by NewsRx correspondents, research stated, “This article investigates under what conditions an increase in ambiguity reduces demand for an uncertain asset (or raises demand for coinsurance). We find that the comparative statics of ambiguity and of risks have structural similarities under the smooth ambiguity aversion model (Klibanoff, Marinacci, and Mukerji, 2005).”

Financial support for this research came from Ministry of Science and Technology (MOST).

Our news journalists obtained a quote from the research from Feng Chia University, “The determinant condition on ambiguity preferences is analogous to that on risk preferences. However, the comparative statics have fundamental differences under the alpha-maxmin model (Ghirardato, Maccheroni, and Marinacci, ()).”

According to the news editors, the research concluded: “When relative risk aversion is less than 1, only an increase in ambiguity, which broadens support for an investor’s belief in the probability of the return distribution in the manner of a strong increase in risk, can reduce demand for an uncertain asset.”

For more information on this research see: A Mean-preserving Increase In Ambiguity and Portfolio Choices. Journal of Risk & Insurance, 2018;85(4):993-1012. Journal of Risk & Insurance can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Journal of Risk & Insurance - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6975)

The news correspondents report that additional information may be obtained from Y.C. Huang, Feng Chia University, Dept Risk Management & Insurance, Taichung 40724, Taiwan.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/jori.12188. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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