文章基本信息

标题：Conviction Function? A New Decision Paradigm for Personal Financial Risk Management in the Face of Large Exogenous Shocks
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作者：Michael Cohen ; Munirul Nabin ; Sukanto Bhattacharya 等
期刊名称：Theoretical Economics Letters
印刷版ISSN：2162-2078
电子版ISSN：2162-2086
出版年度：2018
卷号：08
期号：05
页码：918-934
DOI：10.4236/tel.2018.85065
语种：English
出版社：Scientific Research Publishing
摘要：This paper contributes to the limited-information literature on savings in a stochastic environment. In particular, it contributes techniques and concepts to the question of state verification (or filtering), by including learning about aggregate income shocks, based on signals. As a seminal contribution to the extant literature, a “conviction function” is introduced, which takes into account histories of past prediction errors in determining how rational agents internalize such information in taking personal investment decisions. For purpose of a more transparent illustration, a numerical rendition of the posited model is provided for five consecutive time periods. We also perform a series of Monte Carlo simulations to demonstrate how the posited approach could potentially outperform traditional forward-looking models in the presence of sudden large extraneous shocks reminiscent of the recent Global Financial Crisis.
关键词：Financial Risk;Stochastic Optimization;Conviction Function;Bayesian Learning;Large Shocks