Do Oil Prices Predict the Conditional Distribution of Aggregate Stock Market Returns? Empirical Evidence From One Hundred Fifty Years of Monthly Data

2017 ◽  
Author(s):  
Nima Nonejad
2020 ◽  
Vol 11 (6) ◽  
pp. 1
Author(s):  
Salem Alshihab ◽  
Nayef AlShammari

This paper examines the impact of fluctuations in the price of oil on Kuwaiti stock market returns for the month-to-month period of 2000 to 2020. The Augmented Dickey-Fuller (ADF) test for stationarity, the error correction model (ECM), and various cointegration test techniques were used to examine the estimated model. In an oil-based economy like Kuwait, the exposure to oil prices seems to affect the performance of the country’s stock market. Our main findings related to the long run showed that the price of oil is cointegrated with stock market returns. Interestingly, our ECM examination confirmed that changes in Kuwaiti stock market returns are only affected by oil price fluctuations in the short run. Further strategies are needed to better stabilize Kuwait’s capital market. This equilibrium can be achieved by pursuing more stability in other macroeconomic factors and providing a solid legal independence for the country’s financial market.


2019 ◽  
pp. 097215091984522
Author(s):  
Kapil Choudhary ◽  
Parminder Singh ◽  
Amit Soni

Empirical evidence indicates that foreign institutional investors (FIIs) play a vital role in financial markets, and being the major players, they demonstrate positive feedback trading behaviour and usually follow one another’s actions. In order to examine this phenomenon, the present study endeavoured to unearth the relationship between foreign institutional investments (FIIs) and returns in the Indian stock market, trading volume and volatility. The return of the Nifty50 index has surrogated market returns, while volatility is represented by conditional volatility computed from Nifty50, from January 1999 to May 2017. The vector autoregression (VAR) results indicate a positive association between herding among FIIs and lagged market returns, while information asymmetry has no impact on herding. On the other hand, previous-day volatility has a significant bearing on the herding measure. Overall, the results portray a significant relationship between herding and stock market returns in India. The results of multivariate regression exhibit that market return was a primary factor for FII herding during the study period under consideration, while trading volume bore no relationship with herding. In case of market volatility, the empirical results are in congruence with the fact that during the period of the volatile market, FIIs prefer to not indulge in herding. Furthermore, the results of three sub-periods, that is, before, during and after the crisis, are similar to the results of the whole study period which indicates that the return is a prime and vital force for herding; on the contrary, market volatility appears to have a negative relationship with herding.


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