Conviction Function ? A New Decision Paradigm for Personal inancial Risk Management in the Face of Large Exogenous Shocks

Micheal Cohen, Munirul H. Nabin, Sukanto Bhattacharya, Kuldeep Kumar

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Abstract

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.
Original languageEnglish
Pages (from-to)918-934
Number of pages17
JournalTheoretical Economics Letters
Volume8
Issue number5
DOIs
Publication statusPublished - Apr 2018

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Paradigm
Risk management
Exogenous shocks
Income shocks
Prediction error
Savings
Global financial crisis
Forward-looking models
Monte Carlo simulation
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Cite this

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Conviction Function ? A New Decision Paradigm for Personal inancial Risk Management in the Face of Large Exogenous Shocks. / Cohen, Micheal ; Nabin, Munirul H.; Bhattacharya, Sukanto; Kumar, Kuldeep.

In: Theoretical Economics Letters, Vol. 8, No. 5, 04.2018, p. 918-934.

Research output: Contribution to journalArticleResearchpeer-review

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