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The Forward Puzzle: Long-memory Bias, Short-term Expectations

机译:前向难题:长期记忆偏见,短期期望

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The Unbiased Expectations Hypothesis (UEH) says that the forward premium is an unbiased predictor of the exchange rate change. In practice, UEH is always rejected: in the regression of the exchange rate change on the forward premium one gets a non-unity slope. Previous works variously ascribe the forward puzzle to model misspecification, non-stationary forward premium etc. However, no single theory fully succeeds in explaining the puzzle. One objective of this paper is to differentiate the model-misspecification problem from the non-stationary issue. The second objective is to test the competing theory that the slope is not constant across the forward premia. By Specifying the test model with a non-linear relationship between the exchange rate change and the forward premium we find that the model’s predictive power increases and the slope is closer to unity with extreme positive forward premia. To handle the non-stationary forward premium problem, we decompose the forward premium into a long-memory co-movement component and a short-term filtered forward premium. The forward puzzle becomes worse when the slope is related to the long-memory component but significantly weakened in terms of the filtered component, indicating an ”extreme” support for UEH in Huisman et al. (1998). The standard deviations are calculated under the Monte Carlo Method for the overlapping observations.
机译:无偏预期假设(UEH)说,远期保费是汇率变动的无偏预测因子。在实践中,UEH总是被拒绝:在远期溢价的汇率变化回归中,获得非统一斜率。先前的工作将正向谜题归因于模型误导,非平稳的正向溢价等。但是,没有单一的理论能够完全成功地解释该谜题。本文的一个目的是将模型规格不正确问题与非平稳问题区分开来。第二个目标是检验竞争理论,即在正向溢价中斜率不是恒定的。通过将测试模型指定为汇率变化与远期溢价之间具有非线性关系,我们发现该模型的预测能力增加,并且斜率更接近于正向极端溢价。为了处理非平稳的远期保费问题,我们将远期保费分解为长期记忆共同运动成分和短期过滤后的远期保费。当斜率与长记忆成分有关时,前向难题变得更糟,但在滤波成分方面明显减弱,这表明Huisman等人对UEH的“极端”支持。 (1998)。标准偏差是根据蒙特卡罗方法为重叠观测值计算的。

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