scholarly journals Volatility Spillover Effect in Indian Stock Market

2017 ◽  
Vol 5 ◽  
pp. 83-101 ◽  
Author(s):  
Surya Bahadur G. C ◽  
Ranjana Kothari ◽  
Rajesh Kumar Thagurathi
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Exchange ◽  
Spillover Effect ◽  
Stock Index ◽  
Global Markets ◽  
Series Data ◽  
Volatility Spillover ◽  
Volatility Transmission ◽  
Indian Stock Market

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

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yosuke Kakinuma
Keyword(s):  
Southeast Asia ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Southeast Asian ◽  
Series Data ◽  
Financial Assets ◽  
Volatility Spillover ◽  
Content Type ◽  
Asset Classes

Purpose This study aims to provide empirical evidence on the return and volatility spillover effects between Southeast Asian stock markets, bitcoin and gold in the periods before and during the COVID-19 pandemic. The interdependence among different asset classes, the two leading stock markets in Southeast Asia (Singapore and Thailand), bitcoin and gold, is analyzed for diversification opportunities. Design/methodology/approach The vector autoregressive-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity model is used to capture the return and volatility spillover effects between different financial assets. The data cover the period from October 2013 to May 2021. The full period is divided into two sub-sample periods, the pre-pandemic period and the during-pandemic period, to examine whether the financial turbulence caused by COVID-19 affects the interconnectedness between the assets. Findings The stocks in Southeast Asia, bitcoin and gold become more interdependent during the pandemic. During turbulent times, the contagion effect is inevitable regardless of region and asset class. Furthermore, bitcoin does not provide protection for investors in Southeast Asia. The pricing mechanism and technology behind bitcoin are different from common stocks, yet the results indicate the co-movement of bitcoin and the Singaporean and Thai stocks during the crisis. Finally, risk-averse investors should ensure that gold constitutes a significant proportion of their portfolio, approximately 40%–55%. This strategy provides the most effective hedge against risk. Originality/value The mean return and volatility spillover is analyzed between bitcoin, gold and two preeminent stock markets in Southeast Asia. Most prior studies test the spillover effect between the same asset classes such as equities in different regions or different commodities, currencies and cryptocurrencies. Moreover, the time-series data are divided into two groups based on the structural break caused by the COVID-19 pandemic. The findings of this study offer practical implications for risk management and portfolio diversification. Diversification opportunities are becoming scarce as different financial assets witness increasing integration.

scholarly journals Interdependence and Risk Comparison of Slovak, Hungarian and Polish Stock Markets: Policy and Managerial Implications

2019 ◽  
Vol 69 (2) ◽  
pp. 273-287 ◽  
Author(s):  
Florin Aliu ◽  
Besnik Krasniqi ◽  
Adriana Knapkova ◽  
Fisnik Aliu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Markets ◽  
Stock Exchange ◽  
Weighted Average ◽  
Stock Index ◽  
Risk Level ◽  
Average Return ◽  
Monetary System ◽  
Managerial Implications

Risk captured through the volatility of stock markets stands as the essential concern for financial investors. The financial crisis of 2008 demonstrated that stock markets are highly integrated. Slovakia, Hungary and Poland went through identical centralist economic arrangement, but nowadays operate under diverse stock markets, monetary system and tax structure. The study aims to measure the risk level of the Slovak Stock Market (SAX index), Budapest Stock Exchange (BUX index) and Poland Stock Market (WIG20 index) based on the portfolio diversification model. Results of the study provide information on the diversification benefits generated when SAX, BUX and WIG20 join their stock markets. The study considers that each stock index represents an independent portfolio. Portfolios are built to stand on the available companies that are listed on each stock index from 2007 till 2017. The results of the study show that BUX generates the lowest risk and highest weighted average return. In contrast, SAX is the riskiest portfolio but generates the lowest weighted average return. The results find that the stock prices of BUX have larger positive correlation than the stock prices of SAX. Moreover, the highest diversification benefits are realized when Portfolio SAX joins Portfolio BUX and the lowest diversification benefits are achieved when SAX joins WIG20.

Volatility Spillover Between Indian and MINT Stock Exchanges: Portfolio Diversification Implication

2019 ◽  
Vol 67 (3-4) ◽  
pp. 299-311
Author(s):  
Miklesh Prasad Yadav ◽  
Asheesh Pandey
Keyword(s):  
Stock Market ◽  
Spillover Effect ◽  
Stock Exchanges ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Causality Test ◽  
Portfolio Managers ◽  
Vector Auto Regression ◽  
Indian Stock Market ◽  
Auto Regression

We examine the spillover effect from the Indian stock market to Mexico, Indonesia, Nigeria and Turkey (MINT) stock markets in order to check if suitable diversification opportunities are available to global portfolio managers investing in India. We apply Granger causality test, vector auto-regression (VAR) and dynamic conditional correlation (DCC)–MGARCH to investigate the level of integration between India and MINT economies. We observe bidirectional causality between India and Nigeria, unidirectional causality in Mexico and Indonesia, while no causality is found between India and Turkey. Our VAR results suggest that none of the MINT economies impact the return of the Indian stock market; rather returns of the Indian stock market are more affected by their own lagged values. Finally, by applying DCC–MGARCH, we observe that there is no volatility spillover from India to any of the MINT economies. We recommend that portfolio managers investing in the Indian economy may explore MINT economies as possible destinations to diversify their risk. Our study has implications for both academia and portfolio managers.

Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India

2017 ◽  
Vol 19 (1) ◽  
pp. 227-240 ◽  
Author(s):  
Sayantan Bandhu Majumder ◽  
Ranjanendra Narayan Nag
Keyword(s):  
Global Financial Crisis ◽  
Stock Exchange ◽  
Debt Crisis ◽  
Portfolio Allocation ◽  
Volatility Spillover ◽  
Hedging Strategy ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
Daily Data ◽  
Indian Stock Market

The basic thrust of this article is to examine how shocks and volatility are transmitted across sector indices. This article employs the autoregressive asymmetric BEKK-GARCH model. The study is based on daily data from the National Stock Exchange (NSE) of India from January 2004 to January 2014. Volatility spillover was found to be bidirectional among the two pro-cyclical sectors: Finance and IT. But, there was a unidirectional shock and volatility spillover from the non-cyclical FMCG sector to both the pro-cyclical sectors. The FMCG sector has remained almost unaffected by the spillover from the other sectors. Moreover, the evidence of asymmetric spillover has been found to be present in most of the case. Second, correlations between the sectors were found to be higher during the period of global financial crisis. But no such evidence was found in the context of the Euro zone debt crisis. Understanding the dynamics of shocks and volatility transmission is necessary for risk management in general and for optimal portfolio allocation and hedging strategy in particular. To the best of our knowledge, this is the first study on Indian stock market which has analysed the dynamics of shock and volatility transmission across sector indices.

scholarly journals Diffusion Entropy Analysis: Stability of Indian Stock Market

2019 ◽  
Vol 8 (4) ◽  
pp. 9358-9362
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Significant Drop ◽  
Bear Market ◽  
Diffusion Entropy ◽  
The Usa ◽  
The Stability ◽  
Indian Stock Market

The large amount of available data of stock markets becomes very beneficial when it is transformed to valuable information. The analysis of this huge data is essential to extract out the useful information. In the present work, we employ the method of diffusion entropy to study time series of different indexes of Indian stock market. We analyze the stability of Nifty50 index of National Stock Exchange (NSE) India and SENSEX index of Bombay Stock Exchange (BSE), India in the vicinity of global financial crisis of 2008. We also apply the technique of diffusion entropy to analyze the stability of Dow Jones Industrial Average (DJIA) index of USA. We compare the results of Indian Stock market with the USA stock market (DJIA index). We conduct an empirical analysis of the stability of Nifty50, Sensex and DJIA indexes. We find significant drop in the value of diffusion entropy of Nifty50, Sensex and DJIA during the period of crisis. Both Indian and USA stock markets show bull market effects in the pre-crisis and post-crisis periods and bear market effect during the period of crisis. Our findings reveal that diffusion entropy technique can replicate the price fluctuations as well as critical events of the stock market.

Volatility of Indian Stock Market: An Emperical Evidence

2008 ◽  
Vol 4 (4) ◽  
pp. 53-61 ◽  
Author(s):  
Aman Srivastava
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Exchange ◽  
Stock Exchanges ◽  
Garch Models ◽  
Indian Stock Market ◽  
Class Models

The purpose of this paper is to apply the GARCH-class models to two major stock exchanges of Indian stock markets. The study includes main indices of Bombay Stock Exchange (SENSEX) and that of National stock exchange (NIFTY). GARCH-class models have been applied to analyze the characteristics of the volatility of Indian stock market. The findings suggest that both the Indian stock exchanges have significant ARCH effects and it is appropriate to use ARCH/GARCH models to estimate the process and also demonstrated that there are leverage effects in the markets. That means the investors in those markets are not grown well and they will be heavily influenced by information (good or bad) very easily.

scholarly journals Volatility Interactions among India and US Stock Markets

2014 ◽  
Vol 1 (1) ◽  
pp. 107
Author(s):  
Joshi Prashant
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Volatility Spillover ◽  
Volatility Transmission ◽  
The Relationship

The study examines the return and volatility spillover among BSE and DJIA of India and US Stock Markets respectively. It employed GARCH-BEKK model to examine the relationship. The period of study is from January 2, 2012 to April 4, 2014. We find evidences of bidirectional shock and volatility interactions among the stock markets. The results indicate that DJIA exercises more influence on BSE in terms of shocks and volatility transmission. The overall persistence of volatility is highest in US stock market.

scholarly journals Multidimensional Liquidity: Evidences from Indian Stock Market

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Sharad Nath Bhattacharya ◽  
Pramit Sengupta ◽  
Mousumi Bhattacharya ◽  
Basav Roychoudhury
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Stock Markets ◽  
Trading Volume ◽  
Stock Exchange ◽  
Market Liquidity ◽  
Percentage Error ◽  
Efficiency Coefficient ◽  
Learning Tools ◽  
Indian Stock Market

Various dimensions of liquidity including breadth, depth, resiliency, tightness, immediacy are examined using BSE 500 and NIFTY 500 indices from Indian Equity market. Liquidity dynamics of the stock markets were examined using trading volume, trading probability, spread, Market Efficiency coefficient, and turnover rate as they gauge different dimensions of market liquidity. We provide evidences on the order of importance of these liquidity measures in Indian stock market using machine learning tools like Artificial Neural Network (ANN) and Random Forest (RF). Findings reveal that liquidity variables collectively explains the movements of stock markets. Both these machine learning tools performs satisfactorily in terms of mean absolute percentage error. We also evidenced lower level of liquidity in Bombay Stock Exchange (BSE) than National Stock Exchange (NSE) and findings supports the liquidity enhancement program recently initiated by BSE.

scholarly journals Impact of Terrorism on Stock Market: A Case of South Asian Stock Markets

2019 ◽  
Vol 5 (2) ◽  
pp. 215-242
Author(s):  
Rehana Kousar ◽  
Zahid Imran ◽  
Qaisar Maqbool Khan ◽  
Haris Khurram
Keyword(s):  
Sri Lanka ◽  
Stock Market ◽  
South Asia ◽  
Stock Markets ◽  
Stock Exchange ◽  
Spillover Effect ◽  
Market Returns ◽  
Stock Market Returns ◽  
Negative Effect ◽  
The Impact

The purpose of this study is to examine the impact of terrorism on stock markets of South Asia namely, Karachi Stock Exchange 100 index (Pakistan), Bombay Stock Exchange (India), Colombo Stock Exchange (Sri Lanka) and Chittagong Stock Exchange (Bangladesh). Monthly panel data has been used for the period of January 2000 to December 2016. Terrorism events happened during the period of 2000 to 2016 have been incorporated to examine the impact of terrorism on stock market returns of South Asia. DCC GARCH through R software is used to analyze the impact of terrorism on stock market returns and to analyze the spillover effect of terrorism in one country and on the stock markets of other countries of South Asia. The results indicate that terrorism has significant and negative effect on stock market returns of Pakistan, India and Bangladesh but insignificant in Sri Lanka. Results also shows that stock markets return of Pakistan, India, and Bangladesh are significant and positively correlated with each other except the Stock market of Sri Lanka.

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