波动性预测与商业周期:来自欧洲货币联盟的证据

Daniel Schwake
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引用次数: 0

摘要

使用递归建模方法和来自欧元区的数据,下面的论文分析了逆周期,股票价格波动被认为是相对于经济状况的表现。它进一步检验了这种相互依赖是否可用于波动率预测。本文的重要贡献是将样本内分析扩展到样本外分析。我们提供了强有力的结果,极大地挑战了在事前和事后基础上股票价格波动与经济状况之间直接和明确联系的理论。与gjr - garch模型对隐含波动率和历史波动率的预测能力相比,本文的结果实际上剥夺了宏观经济信息和金融信息对股价波动率的预测能力。这强调了已经包含在市场价格中的信息负荷,并符合有效市场假说。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Volatility Forecasting and the Business Cycle: Evidence from the European Monetary Union
Using a recursive modeling approach and data from the Euro area, the following paper analyzes the counter-cyclicity, stock price volatility is believed to demonstrate with respect to the state of the economy. It further tests whether such interdependence is exploitable for volatility forecasting. The sound contribution of this paper is the extension of the in-sample to an out-of-sample analysis. We deliver robust results that greatly challenge the theory of straight and clear-cut link between stock price variability and the state of the economy on an ex ante and ex post basis. Compared with the forecasting ability of an GJR-GARCH-Model, of the implied and historical volatility, the prediction power of macroeconomic and financial information on stock price volatility is practically deprived by the results presented. These underline the information load already incorporated in market prices and stand in line with the efficient-market hypothesis.
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