Conviction Function? A New Decision Paradigm for Personal Financial Risk Management in the Face of Large Exogenous Shocks ()
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.
Share and Cite:
Cohen, M. , Nabin, M. , Bhattacharya, S. and Kumar, K. (2018) Conviction Function? A New Decision Paradigm for Personal Financial Risk Management in the Face of Large Exogenous Shocks.
Theoretical Economics Letters,
8, 918-934. doi:
10.4236/tel.2018.85065.