On Modelling and Forecasting Predictable Components in European Stock Markets

被引:0
|
作者
Khurshid M. Kiani
机构
[1] Gulf University of Science and Technology,College of Business Administration
来源
Computational Economics | 2016年 / 48卷
关键词
Predictable component; State space model; Fat tails; Stable distributions; Stock excess returns; European stock markets; C22; C53; G14;
D O I
暂无
中图分类号
学科分类号
摘要
This study investigates possible existence of predictable components in stock excess returns in eighteen European countries i.e. Austria, Croatia, Denmark, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Netherlands, Norway, Russia, Slovakia, Spain, Sweden, Switzerland, and United Kingdom. The excess return series for these countries are modeled using non Gaussian state space or unobserved component model that encompasses non normality and time varying volatility that might be present in the series. While statistically significant evidence of non-normality and volatility persistence does exist in most series, statistically significant persistent predictable component also prevails in Austria, France, Germany, Iceland, Ireland, Italy, Netherlands, Norway, Spain, Sweden, and Switzerland excess returns. However, the results on possible existence of predictable components in stock excess returns in Croatia, Denmark, Greece, Hungary, Russia, Slovakia, and United Kingdom are in sharp contrast. The efficiently estimated excess returns range between 0.002 % per month for Slovakia to 0.094 % per month for Russia stock excess returns. The characteristic exponent ranges between of 1.632 for Croatia to 1.917 for France showing non-normal behavior in these series although the characteristic exponent of 1.999 shows a normal behavior in Italian and Russian excess return series.
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页码:487 / 502
页数:15
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