| 来源类型 | Working Paper
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| 规范类型 | 报告
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| DOI | 10.3386/w14169
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| 来源ID | Working Paper 14169
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| Efficient Prediction of Excess Returns |
| Jon Faust; Jonathan H. Wright
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| 发表日期 | 2008-07-16
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| 出版年 | 2008
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| 语种 | 英语
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| 摘要 | It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns, valid augmenting variables exist and are likely to yield substantial gains in estimation efficiency and, hence, predictive accuracy. The proposed augmenting variables are ex post measures of an unforecastable component of excess returns: ex post errors from macroeconomic survey forecasts and the surprise components of asset price movements around macroeconomic news announcements. These "surprises" cannot be used directly in forecasting--they are not observed at the time that the forecast is made--but can nonetheless improve forecasting accuracy by reducing parameter estimation uncertainty. We derive formal results about the benefits and limits of this approach and apply it to standard examples of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for standard excess bond return regressions; gains for forecasting excess stock returns are much smaller. |
| 主题 | Econometrics
; Estimation Methods
; Financial Economics
; Financial Markets
|
| URL | https://www.nber.org/papers/w14169
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| 来源智库 | National Bureau of Economic Research (United States)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/571843
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推荐引用方式
GB/T 7714 |
Jon Faust,Jonathan H. Wright. Efficient Prediction of Excess Returns. 2008.
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文件名：
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w14169.pdf
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格式：
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Adobe PDF
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