scholarly journals Return and Volatility Spillover across stock markets of China and its Major Trading Partners: Evidence from Shanghai Stock Exchange Crash

2018 ◽  
Vol 10 (3) ◽  
pp. 1-20 ◽  
Author(s):  
Muhammad Owais Qarni ◽  
Saqib Gulzar
2017 ◽  
Vol 5 ◽  
pp. 83-101 ◽  
Author(s):  
Surya Bahadur G. C ◽  
Ranjana Kothari ◽  
Rajesh Kumar Thagurathi

The study aims to empirically examine the transmission of volatility from global stock markets to Indian stock market. The study is based on time series data comprising of daily closing stock market indices from National Stock Exchange (NSE), India and major foreign stock exchange of the three countries one each from America, Europe and Asia making the highest portfolio investment in Indian stock market. The study period covers 11 years from 1st January, 2005 to 31st December, 2015 comprising a total of 2731 observations. The Indian stock index used is CNX Nifty 50 and the foreign indices are S & P 500 from USA, FTSE 100 from UK, and Nikkei 225 from Japan. The results reveal that the Indian stock market return is co-integrated with market returns of US, UK and Japanese stock markets. Therefore, the return and hence volatility of Indian stock market is associated with global markets which depicts that it is getting integrated with global financial markets. The results provide empirical evidence for volatility transmission or volatility spillover in the Indian stock market from global markets. There exists inbound volatility transmission from US market to Indian stock market. The Indian and UK stock market have bi-directional volatility transmission. However, there exists presence of only outbound volatility transmission from Indian stock market to Japanese stock market. The volatility transmission from global markets to India is rapid with the spillover effect existing for up to three days only.Janapriya Journal of Interdisciplinary Studies, Vol. 5 (December 2016), page: 83-101


2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Shahid Rasheed ◽  
Umar Saood ◽  
Waqar Alam

This study aims to examine the momentum effect presence in selected stocks of Pakistan stock market using data from Jan 2007 to Dec 2016. This study constructed the strategies includes docile, equal weighted and full rebalancing techniques. Data was extracted from the PSX – 100 index ranging from 2007 to 2016. STATA coding ASM software was used for calculating momentum portfolios, finally top 25 stocks were considered as a winner stocks and bottom 25 stocks were taken as a loser stocks. In conclusion, the results of the study found a strong momentum effect in Pakistan stock exchange PSX 100- index. As by results it has been observed that a substantial profit can earn by the investors or brokers in constructing a portfolio with a short formation period of three months and hold for 3, 6 and 12 months. There is hardly a study is present on the same topic on Pakistan Stock Exchange as preceding studies were only conducted on individual stock markets before merger of stock markets in Pakistan while this study leads the explanation of momentum phenomenon in new dimension i.e. Pakistan Stock Exchange. Keywords: Momentum, Portfolio, Winner Stocks, Loser Stocks


Author(s):  
Paritosh Chandra Sinha

Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioral finance perspectives. In particular, it develops a new theory of herding behavior and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or time-stamp, trade-volume, and trade-price of ten sample scripts listed for their trading in both markets - the Bombay Stock Exchange (BSE) and the National stock Exchange (NSE). The study contributes to the literature with original findings. It shows that investors in the two Indian stock markets show crowd of positive and negative herding as well significantly and there is huge noise along with information in the markets equilibrium pricing mechanism.


2017 ◽  
Vol 44 ◽  
pp. 13-26 ◽  
Author(s):  
Hong Miao ◽  
Sanjay Ramchander ◽  
Tianyang Wang ◽  
Dongxiao Yang

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