Mean reversion in international markets: evidence from GARCH and half-life volatility models

被引:12
|
作者
Ahmed, Rizwan Raheem [1 ]
Vveinhardt, Jolita [2 ]
Streimikiene, Dalia [2 ]
Channar, Zahid Ali [3 ]
机构
[1] Indus Univ, Fac Management Sci, Gulshan, Pakistan
[2] Lithuanian Sports Univ, Inst Sport Sci & Innovat, Kaunas, Lithuania
[3] Sindh Madressa Tul Islam Univ, Dept Business Adm, Karachi, Pakistan
来源
关键词
Mean reversion; developed & emerging stock markets; half-life model; ARCH-LM; GARCH (1,1); STOCK MARKETS; VARIANCE; MOMENTUM;
D O I
10.1080/1331677X.2018.1456358
中图分类号
F [经济];
学科分类号
02 ;
摘要
The objective of this research is to examine and compare the mean reversion phenomenon in developed and emerging stock markets. An important aim is to measure and compare the speed of mean reversion and half-life of volatility shocks of emerging and developed markets. For this purpose, we have selected five developed and seven emerging markets, and used daily market indices for the period of 1 January 2000 to 30 June 2016. We employed autoregressive conditional heteroskedasticity - Lagrange multiplier (A.R.C.H.-L.M.), generalised autoregressive conditional heteroskedasticity (G.A.R.C.H.) (1, 1), and half-life volatility shock techniques to carry out this research. The results of the study confirmed the mean-reverting process in developed and emerging markets. The South Korean market has the slowest mean reversion, and thus has the highest comparative volatility over a longer period of time. However, the Pakistan stock exchange exhibited the fastest mean reverting process. It is also concluded that the relative volatilities are higher in emerging markets, whereas the comparative volatilities are higher in developed markets. Therefore, it is further concluded that the mean reversion process is much faster in emerging indices except the South Korean and Chinese markets. The study recommends that if investors want higher returns in a shorter period of time then they should invest in emerging markets.
引用
收藏
页码:1198 / 1217
页数:20
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