Time Varying Volatility in the Indian Stock Market

Kaur, Harvnder

doi:10.2139/ssrn.501222

Cited by 17 publications

(18 citation statements)

References 33 publications

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“…They demonstrated no correlation between these indices. Kaur (2004) studied the return and volatility spillover between India (Sensex and Nifty) and US (NASDAQ and S&P 500) markets by using EGARCH and TGARCH volatility models. She found the mixed evidence of return and volatility spillover between the US and the Indian markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Price and Volatility Spillovers Across North American, European and Asian Stock Markets: With Special Focus on Indian Stock Market

2009

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This paper investigates interdependence of fifteen world indices including an Indian market index in terms of return and volatility spillover effect. Interdependence of Indian stock market with other fourteen world markets in terms of long run integration, short run dependence (return spillover) and volatility spillover are investigated. These markets are that of are and United States. Long run and short run integration is examined through Johansen cointegration techniques and Granger causality test respectively. Vector autoregressive model (VAR 15) is used to estimate the conditional return spillover among these indices in which all fifteen indices are considered together. The effect of same day return in explaining the return spillover is also modeled using univariate models. Volatility spillover is estimated through AR-GARCH in which residuals from the index return is used as explanatory variable in GARCH equation. Return and volatility spillover between Indian and other markets are modeled through bivariate VAR and multivariate GARCH (BEKK) model respectively. It is found that there is greater regional influence among Asian markets in return and volatility than with European and US. Japanese market, which is first to open, is affected by US and European markets only and affects most of the Asian Markets. Also, high degree of correlation among European indices namely FTSE, CAC and DAX is observed. US market is influenced by both Asian and European markets. Specific to Indian context, it is found that Indian market is not cointegrated with rest of the world except Indonesia. This may provide diversification benefits for potential investors. However, strong short run interdependence is found between Indian markets and most of the other markets. Indian and other markets like US, Japan, Korea, and Canada positively affect each others' conditional returns significantly. Indian market also has significant effect on Malaysia, Pakistan, and Singapore return. This study found that there is significant positive volatility spillover from other markets to Indian market, mainly from Hong Kong, Korea, Japan, and Singapore and US market. Indian market affects negatively the volatility of US and Pakistan. It is interesting to note that Chinese and Pakistan markets are less integrated with other Asian, European and US markets.

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Section: Literature Reviewmentioning

confidence: 99%

Price and Volatility Spillovers Across North American, European and Asian Stock Markets: With Special Focus on Indian Stock Market

2009

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“…In particular, Lee et al (2001) examined volatility in the Chinese stock market, and Olowe (2009) and Kaur (2004) in the Nigerian and Indian ones respectively. Other authors (Bekaert and Harvey, 1997;Aggarwal et al, 1999;Mookerjee and Yu, 1999;Lee et al, 2001;Kaur, 2004;etc. ) have examined time varying-volatility models using daily data for other emerging countries.…”

Section: Introductionmentioning

confidence: 99%

Modelling time-varying volatility in the Indian stock returns: Some empirical evidence

Tripathy¹,

Gil-Alana

2015

Review of Development Finance

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This paper models time-varying volatility in one of the Indian main stock markets, namely, the National Stock Exchange (NSE) located in Mumbai, investigating whether it has been affected by the recent global financial crisis. A Chow test indicates the presence of a structural break. Both symmetric and asymmetric GARCH models suggest that the volatility of NSE returns is persistent and asymmetric and has increased as a result of the crisis. The model under the Generalized Error Distribution appears to be the most suitable one. However, its out-of-sample forecasting performance is relatively poor.

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“…The reason of correlation between these two trading days might be the availability of fresh information at the start of the week which makes the trading system dynamic one relative to the rest of the week. Empirical evidences are available to support the positive Wednesday effect which is documented (10,16,30) 2004 1994-2004 1994-2004 1994-2004 1995-2004 1986-2004 1986-2004 1984-2005 No The literature has supported that the reason for positive Wednesday trading returns might be due to the optimistic attitude of the Indian investors to make their dealings on Wednesday most of the times (2,12,27,30) In Indian capital market, a number of studies have documented the positive Thursday effect (6,8,26). There are some studies which are available to support the positive Friday effect (6,25,31) in the Indian stock market.…”

Section: Introductionmentioning

confidence: 88%

An Examination of Stock Market Anomalies: A Study in the Context of Make in India Movement

Khanna¹

2016

IOSR

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The existence of calendar anomalies is the violation of Efficient Market Hypothesis (EMH). Stock Market anomalies are the patterns that do seem to lead to abnormal returns more often than not, and since some of these patterns are based on information which is publicly visible, market anomalies present a challenge to the semi-strong form of the EMH, indicating that fundamental analysis does have some value for the individual investor. The existence and predictability of stock market anomalies has been a subject of different studies which detects empirical evidences of abnormal yield distribution. The predictable seasonal returns behavior may lead to profitable trading strategies and in turn abnormal returns. The Day-of-the-Week Effect is the most common tested anomaly in India and abroad. In the current research paper, the main focus is to examine the impact of Make in India Movement on stock market anomalies with reference to BSE Sensex. The closing prices for Sensex have been taken for the purpose of analysis. However, the investor must keep in mind that these anomalies can persist or disappear in a certain course of time.

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Time Varying Volatility in the Indian Stock Market

Cited by 17 publications

References 33 publications

Price and Volatility Spillovers Across North American, European and Asian Stock Markets: With Special Focus on Indian Stock Market

Price and Volatility Spillovers Across North American, European and Asian Stock Markets: With Special Focus on Indian Stock Market

Modelling time-varying volatility in the Indian stock returns: Some empirical evidence

An Examination of Stock Market Anomalies: A Study in the Context of Make in India Movement

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