Abstract
Is an autoregressive moving average model for the unobserved forward risk premium component always identifiable? Is the signal extraction-based approach always feasible? In this paper, we point out a theoretical framework to shed the light on the statistical problem of model identification. We find out that whenever a model for the unobservable forward risk premium is unidentifiable, we identify a new class of functions that we call: the noise generating functions (Hereafter NGF). These functions circumvent the model identification problem and help us make insights on the noise variances. We demonstrate that a model for the risk premium in the forward exchange rate is not always identifiable and the signal extraction methodology is not always feasible. In addition, our theoretical statements are applied to the empirically evidenced models within the related literature.
Highlights
Do forward risk premia evoke much debate and they are central to the theory in/of international finance
Our paper proposes a synthesis of previously theoretical as well as empirical research and calls attention to a crucial problem, which is identifying an ARMA model for the unobserved forward risk premia
This paper focuses on the statistical problem of model identification for the unobservable forward risk premium component
Summary
Do forward risk premia evoke much debate and they are central to the theory in/of international finance. Diko, Lawford and Limpens (2006) investigated the presence of electricity forward risk premia in a continuous time framework and using an unobserved factor model. Continuous time vs discrete time models, linear vs nonlinear models, parametric vs nonparametric models, observed vs unobserved factor models, and regression-based vs signal extraction-based models have been performed. They adopted nonlinear and nonparametric estimation techniques. Cheung (1993) modeled risk premia in forward exchange rates as unobservables and pointed out a signal extraction modeling strategy. Djeutem (2013) stated that the forward premium puzzle, in a context wherein agents doubt the Published by Sciedu Press
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