Forecasting the direction of the US stock market with dynamic binary probit models

Forecasting the direction of the US stock market with dynamic binary probit models

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Article ID: iaor20112058
Volume: 27
Issue: 2
Start Page Number: 561
End Page Number: 578
Publication Date: Apr 2011
Journal: International Journal of Forecasting
Authors:
Keywords: maximum likelihood estimation, stock market
Abstract:

Several empirical studies have documented that the signs of excess stock returns are, to some extent, predictable. In this paper, we consider the predictive ability of the binary dependent dynamic probit model in predicting the direction of monthly excess stock returns. The recession forecast obtained from the model for a binary recession indicator appears to be the most useful predictive variable, and once it is employed, the sign of the excess return is predictable in‐sample. The new dynamic ‘error correction’ probit model proposed in the paper yields better out‐of‐sample sign forecasts, with the resulting average trading returns being higher than those of either the buy‐and‐hold strategy or trading rules based on ARMAX models.

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