TITLE:
Forecasting the S&P 500 Index with Circuit Breakers
AUTHORS:
Arie Harel, Giora Harpaz
KEYWORDS:
Circuit Breakers, Bayesian Investors, Forecasting Stock Index Levels
JOURNAL NAME:
Theoretical Economics Letters,
Vol.10 No.6,
December
3,
2020
ABSTRACT: The purpose of this paper is to develop a Bayesian
model of the S&P 500 stock index in the presence of a circuit breaker rule
that would be useful to traders who wish to update positions when information
is limited because of a market trading halt. We assume that the market index is
distributed by a Poisson process with an unknown parameter. First, using a
conjugate Gamma prior probability distribution, we can revise the distribution
of the prior distribution, to get an updated Gamma posterior distribution.
Second, we calculate the market index’s truncated posterior and predictive
distributions in the presence of circuit breakers. Third, our predicted index’s
values (during the activation of the circuit breakers that results in a fifteen-minute trading halt) are demonstrated by
numerical examples. Thus, investors would be able to adjust, their long/short
positions, when market information is temporarily unavailable.