'Optimal' Probabilistic Predictions of Financial Returns

29 Pages Posted: 28 Nov 2007

See all articles by Dimitrios D. Thomakos

Dimitrios D. Thomakos

University of Athens, Department of Business Administration

Tao Wang

City University of New York (CUNY) - Department of Economics

Date Written: November 2007

Abstract

We examine the 'relative optimality' of sign predictions for financial returns, extending the work of Christoffersen and Diebold (2006) on volatility dynamics and sign predictability. We show that there is a more general decomposition of financial returns than that implied by the sign decomposition and which depends on the choice of the threshold that defines direction. We then show that the choice of the threshold matters and that a threshold of zero (leading to sign predictions) is not necessarily 'optimal'. We provide explicit conditions that allow for the choice of a threshold that has maximum responsiveness to changes in volatility dynamics and thus leads to 'optimal' probabilistic predictions. Finally, we connect the evolution of volatility to probabilistic predictions and show that the volatility ratio is the crucial variable in this context. Our work strengthens the arguments in favor of accurate volatility measurement and prediction, as volatility dynamics are integrated into the 'optimal' threshold. We provide an empirical illustration of our findings using monthly returns and realized volatility for the S&P 500 index.

Keywords: decomposition, direction, optimal, predictions, returns, sign forecasting, volatility

JEL Classification: C22, C53, G11, G12, G14

Suggested Citation

Thomakos, Dimitrios D. and Wang, Tao, 'Optimal' Probabilistic Predictions of Financial Returns (November 2007). Available at SSRN: https://ssrn.com/abstract=1032944 or http://dx.doi.org/10.2139/ssrn.1032944

Dimitrios D. Thomakos (Contact Author)

University of Athens, Department of Business Administration ( email )

Athens
Greece

HOME PAGE: http://ba.uoa.gr/

Tao Wang

City University of New York (CUNY) - Department of Economics ( email )

65-30 Kissena Blvd
Flushing, NY 11367-1597
United States

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