Journal articles on the topic 'Stock market- India'
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1
G. C, Surya Bahadur, Ranjana Kothari, and Rajesh Kumar Thagurathi. "Volatility Spillover Effect in Indian Stock Market." Janapriya Journal of Interdisciplinary Studies 5 (July 21, 2017): 83–101. http://dx.doi.org/10.3126/jjis.v5i0.17842.
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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
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G Nagarakatte, Sangeetha, and Natchimuthu Natchimuthu. "Return and volatility spillover between India, UK, USA and European stock markets: The Brexit impact." Investment Management and Financial Innovations 19, no. 1 (February 8, 2022): 121–34. http://dx.doi.org/10.21511/imfi.19(1).2022.09.
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The 2016 Brexit referendum created potential turmoil in financial markets. The purpose of this study is to examine the impact of the Brexit referendum on the return and volatility spillover between the EU, the UK, and the USA stock markets and the Indian stock market during the pre- and post-Brexit referendum period. The VAR and bivariate GARCH BEKK models were employed. The study results suggest that before the Brexit referendum, Indian stock market returns made no significant return spillover on the other markets. On the contrary, following the referendum, Indian stock returns significantly spilled over to France, Germany, the UK, and the USA stock market returns. The study results also identified a substantial increase in the bidirectional volatility spillover between India-France, India-UK, and India-USA during the post-Brexit referendum period. Therefore, the investors’ opportunity to invest simultaneously in India, UK, EU, and US stock markets for portfolio diversification is limited. India was affected mainly by its own past shocks before the Brexit referendum. However, after the Brexit referendum, Indian markets are getting more and more integrated with other markets. In order to reap the diversification benefits, a prudent investment strategy will need to be developed in the future, especially during times of economic and political uncertainty and market crisis.
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Dayanandan, Ajit, and Jaspreet Kaur Sra. "Accrual management and expected stock returns in India." Journal of Accounting in Emerging Economies 8, no. 4 (November 5, 2018): 426–41. http://dx.doi.org/10.1108/jaee-08-2016-0073.
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Purpose The purpose of this paper is to examine whether the stock market in India is efficient in the semi-strong form. Design/methodology/approach The study uses financial and stock market data of 1,135 listed Indian companies (non-financial) during 2003–2011 collected from Capital IQ to estimate discretionary accruals (DA) using modified Jones model (1995). The study also examines using the widely used Mishkin (1983) test to whether equity market prices accruals in India. The study is conducted for profit/loss-making firms separately as well as for a hedge portfolio of firms based on the lowest to highest accruals. Findings The empirical study of DA of 1,135 listed Indian companies (non-financial) during 2003–2011 shows that the estimated average DA of the corporate sector in India comes to 1 percent of the total assets of these firms. An empirical analysis whether equity market prices DA in India finds no evidence of investors/market pricing DA. Empirical evidence also finds that the results are invariant for profit/loss-making firms as well as portfolio of firms based on the lowest to highest accruals in the Indian context. The empirical evidence shows that the Indian equity market is inefficient with regard to the incorporation of accruals in expected returns of stocks. Research limitations/implications This study builds on the previous literature on accrual pricing in the context of the USA and developed markets. The study extends the empirics to the one of the largest emerging market economy – India. This issue is important not only to investors, but also to policy makers and researchers because the mispricing of accruals could potentially lead to misallocation of capital. The study has implications for stock/firm valuations and cost of equity/capital. Originality/value This is the first study for the pricing of accruals and test of semi-strong efficiency of the Indian stock market.
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Jaiteley, Rudra. "A comparative Study of Chinese and Indian Stock Markets." Journal of Management and Strategy 12, no. 2 (May 18, 2021): 18. http://dx.doi.org/10.5430/jms.v12n2p18.
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Both China and India are developing countries with large population and low revenue. This article mainly makes a comparative analysis of the macro environment of Chinese and Indian stock markets and their perspective features. The aim is to investigate the relationships between Indian stock markets and Chinese stock markets. Using Indian and Chinese stock price daily data over the period 1991 to 2019, we found price and spillovers effect from Indian stock market to Chinese stock market and vice versa.
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Agnihotri, Shalini, and Kanishk Chauhan. "Modeling tail risk in Indian commodity markets using conditional EVT-VaR and their relation to the stock market." Investment Management and Financial Innovations 19, no. 3 (July 7, 2022): 1–12. http://dx.doi.org/10.21511/imfi.19(3).2022.01.
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Investment in commodity markets in India accelerated after 2007; this was accompanied by large price variability, hence, it becomes imperative to measure commodity price risk precisely. It becomes equally important to study the relationship between commodity price variability and the stock market. Hence, this study aims to calculate the tail risk of highly traded Indian commodity futures returns using the conditional EVT-VaR method for risk measurement. Secondly, the linkage between commodity markets and the stock market is also studied using the Delta CoVaR method. Results highlight the following points. There is risk transfer from the extreme increase/decrease in crude oil futures returns to the Nifty Index returns. Both extreme price increase or decrease of crude oil futures driven either by financial or a combination of financial and economic shocks affect the stock market. Zinc and Natural gas futures are not linked to the stock market, which means they can be useful in portfolio diversification. The findings suggest that, in Indian commodity markets, EVT-VaR is a useful tool for measuring risk. Only Crude oil futures shocks affect the stock market, and extreme integration between them becomes more prominent when oil shocks are driven by financial factors. Commodities other than Crude oil are not integrated with stock markets in India.
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Srivastava, Sandeep, Surendra S. Yadav, and P. K. Jain. "Significance of Non-Price Variables in Price Discovery: An Empirical Study of Stock Option Market in India." Vikalpa: The Journal for Decision Makers 33, no. 2 (April 2008): 15–24. http://dx.doi.org/10.1177/0256090920080202.
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The efficiency of the financial markets is important as it ensures increased productive efficiency and economic growth through better capital allocation. Price discovery is the central aspect of financial markets. The relatively efficient price signals also facilitate the participation of uninformed investors to make suitable portfolio choices. Derivative instruments like option contracts enhance informational efficiency of the underlying's market through better price discovery as these securities are expected to increase the flow of information in the market. Besides, they facilitate hedging of risk. In India, exchange-trade derivates are of recent origin in the stock market. This study investigates the significance of net open interest and trading volume in stock option and stock index option market to predict the underlying stock prices⁄index level. In the study, only 15 stock option contracts (having maturity of one-month) and Nifty options for the entire period, i.e., November 10, 2001 to November 2, 2004, have been analysed. The analysis could not be carried out for all the stocks in option segment because of the fact that the options were not traded or the trading range and volumes were too thin to justify any analysis. The major findings of the study are as follows: Net open interest of stock option is one of the significant variables in the determination of the future spot price of the underlying stock. Open interest-based predictors are statistically more significant than the volume-based predictors in the Indian context too as is the case for the US market. The trading behaviour of Indian investors is found to be different from their counterparts in the developed world. This difference can be attributed to: the nascent state of derivatives market in India extremely limited participation of institutional investors in the Indian stock derivative market because of regulatory restrictions; as such investors are allowed to use derivative securities mainly for hedging and arbitrage purposes only. The findings would definitely help the regulatory bodies in policy-making and further strengthening the efforts to promote the derivative market in India. There are many areas which are still unexplored and can be addressed by the future studies by using the intraday data and a larger sample for the stock options.
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Yadav, Miklesh Prasad, and Asheesh Pandey. "Volatility Spillover Between Indian and MINT Stock Exchanges: Portfolio Diversification Implication." Indian Economic Journal 67, no. 3-4 (December 2019): 299–311. http://dx.doi.org/10.1177/0019466220947501.
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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.
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Tripathi, Vanita, and Varun Bhandari. "Socially responsible stocks: a boon for investors in India." Journal of Advances in Management Research 12, no. 2 (August 3, 2015): 209–25. http://dx.doi.org/10.1108/jamr-03-2014-0021.
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Purpose – The purpose of this paper is to empirically examine the performance of socially responsible stocks portfolio vis-à-vis portfolios of general companies in the Indian stock market. Design/methodology/approach – The study has used absolute rate of return as well as various risk adjusted measures like Sharpe ratio, Treynor ratio, Jensen’s α, Information ratio, Fama’s decomposition measure and dummy regression model to evaluate the performance of various portfolios. Findings – Socially responsible stocks portfolios are found to have lower relative risk despite having higher systematic risk. Further the authors find that during crisis and post-crisis period, socially responsible stocks portfolio generated significantly higher return as compared to other portfolios in the Indian stock market. Environmental, social and governance (ESG) Index and GREENEX Index provided positive net selectivity returns in all the three sub periods, especially during crisis period. GREENEX and ESG outperformed NIFTY and SENSEX even on net selectivity basis. This indicates that the compromise made with respect to diversification by investing in socially responsible stocks portfolios was well rewarded in terms of higher returns in Indian context. Practical implications – The findings lend support to the case of socially responsible investing (SRI) in India and are relevant for companies, regulators, policy makers and investors at large. Mutual funds and other investment funds should launch schemes which invest in socially responsible stocks so as to provide the benefits of SRI even to small investors in India. Originality/value – The study contributes to the related literature by analysing the performance of socially responsible stocks portfolios in Indian stock market which is one of the emerging markets.
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KALPAKAM, Gopalakrishnan, and Smita RAMAKRISHNA. "Contagion Effects of Covid-19 on Select Stock Market Indices." Eurasian Journal of Business and Economics 15, no. 30 (November 30, 2022): 45–61. http://dx.doi.org/10.17015/ejbe.2022.030.03.
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We examine the impact of the COVID-19 pandemic on the interlinkages between the Indian stock market and some of the largest indices across the world. We compare the co-movements of these stock markets to identify the possibilities for international portfolio diversification. We use the Johansen cointegration technique and Vector Error Correction Mechanism to understand the nature of long-run and short-run cointegration. We also apply the Impulse Response Function to understand the time effects of the shock. The results of the Johansen cointegration test indicate that there is an increased level of cointegration among the stock market indices post the pandemic. Our results of VEC Block Exogeneity Wald Tests indicate that in the preCovid time, there were linkages between the stock markets of India and the U.K., Japan, and Hongkong. However, the post-pandemic results indicate the shock transmission effects from India to two very important European indices, i.e., the U.K. and Euronext stock exchanges, and to the stock market of Japan. We also observe transmission effects from the USA to India post-Covid period.
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Trivedi, Aaditya, Tajinder Pal Singh, and Kaushal Kishore. "Impact of COVID-19 on Stock Markets: An Investigation and Way Forward." International Review of Business and Economics 5, no. 1 (2021): 1–17. http://dx.doi.org/10.56902/irbe.2021.5.1.8.
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This study analyzes the impact of the COVID-19 pandemic on stock markets in different regions of the world. Impact of COVID-19 on the stock market is like a black swan event. To analyze the impact of COVID-19 on the stock market, study includes different indices, ratios, strategies and past events to compare. Study is focused on the stock market of countries such as the United States and India to see effects on developed and developing countries. The trends were found similar worldwide. The United States, which has been a bull market for a long time, is also experiencing a plummeting stock market. In the Dow Jones Index’s first quarter history, this year’s first quarter has marked the worst performance ever. In the year 2020, Indian stock market from 1st January to 23rd March SENSEX has plunged 37.1% and from 1st January to 18th May SENSEX has plunged 27.2%. The study tries to touch upon the past crises and its impact on various stock markets. Sentiments of an investor play a major role in the stock market. A good strategy if used in this type of stock market can help generate profits and remain stable in the volatile situation as well.
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Maheshwari, Supriya, and Raj S. Dhankar. "Market State and Investment Strategies: Evidence from the Indian Stock Market." IIM Kozhikode Society & Management Review 7, no. 2 (July 2018): 154–70. http://dx.doi.org/10.1177/2277975218769501.
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This study contributes to the growing literature on momentum and overreaction effect by investigating the same within the framework of the Indian stock market. Based on the most adopted methodology that employs monthly data, the empirical results derived confirm the existence of momentum and long-term overreaction effect in the Indian stock market. The overall results from the study are consistent with DeBondt and Thaler (1985) and Jegadeesh and Titman (1993) findings for the US stock market. In addition, we tested the profitability of momentum and contrarian strategies under different market states. The results indicated a strong relationship between the state of the market and momentum profitability, wherein strong momentum profits were observed following an ‘up’ market. On the contrary, long-term contrarian strategies were found to be stronger following a ‘down’ market in the Indian stock market. The market-dependent asset pricing model failed to explain excess momentum profits in the Indian stock market. The evidence from the study provides partial support to various behavioural models to explain these effects in the Indian stock market. However, there exists a need to develop a single behavioural model that could explain these anomalies completely in the emerging markets like India.
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Thangamuthu, Mohanasundaram, and Karthikeyan Parthasarathy. "Cointegration and stock market interdependence: Evidence from South Africa, India and the USA." South African Journal of Economic and Management Sciences 18, no. 4 (November 27, 2015): 475–85. http://dx.doi.org/10.4102/sajems.v18i4.1029.
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The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index.
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Dash, Mihir, and Rita S. "A Vector Autoregressive Market Model for IT Sector Stocks in India." Asian Journal of Finance & Accounting 13, no. 1 (June 10, 2021): 35. http://dx.doi.org/10.5296/ajfa.v13i1.18589.
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This study proposes a vector autoregressive form for the market model and tests its significance against the market model for information technology (IT) sector stocks in the Indian stock market. The analysis was performed for a sample of nineteen IT sector stocks listed on the National Stock Exchange of India, of which nine stocks were large-cap, six were mid-cap, and four were small-cap. The study period considered was Jan. 1, 2018 – Dec. 31, 2018. The key contribution of the study was the finding that the vector autoregressive model is a better model of stock returns than the market model for IT sector stocks. Thus, IT sector stocks seem to react more to market movements from the previous day than on the day itself. The implication for asset pricing modelling is that systematic risk may be further decomposed into a component corresponding to sensitivity to market movements on the day and a component corresponding to sensitivity to market movements on the previous day. The asset pricing model would be extended to include market risk premia for both of these components of systemic risk. Keywords: market model, vector autoregressive model, IT sector, asset pricing modelling, systematic risk.
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(Pal), Suparna Nandy, and Arup Kr Chattopadhyay. "‘Indian Stock Market Volatility’: A Study of Inter-linkages and Spillover Effects." Journal of Emerging Market Finance 18, no. 2_suppl (June 21, 2019): S183—S212. http://dx.doi.org/10.1177/0972652719846321.
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The article attempts to examine interdependence between Indian stock market and other domestic financial markets, namely, foreign exchange market, bullion market, money market, and also Foreign Institutional Investor (FII) trade and foreign stock markets comprising one regional stock market represented by Nikkei of Japan and other stock market for the rest of the world represented by Standard & Poor’s (S&P) 500 of the USA. Attempts are also made to examine asymmetric volatility spillover, first, between the Indian stock market and other domestic financial markets and second, between the Indian stock market and global stock markets (represented by Nikkei and S&P 500) along with the foreign exchange market. To measure linear interdependence among multiple time series of financial markets multivariate Vector Autoregression (VAR) analysis, Granger causality test, impulse response function and variance decomposition techniques are used. For estima-ting the volatility spillover among the aforesaid markets Dynamic Conditional Correlation-Multivriate-Threshold Autoregressive Condi-tional Heteroscedastic (DCC-MV-TARCH) (1, 1) model is applied on daily data for a quite long period of time from 01 April 1996 to 31 March 2012. The results of multivariate VAR analysis, Granger causality test, variance decomposition analysis and impulse response function estimation establish significant interdependence between domestic stock market and different other financial markets in India and abroad. The results of DCC-MV-TARCH (1, 1) model estimation further show signi- ficant asymmetric volatility spillover between the domestic stock market and the foreign exchange market and also from the domestic stock market to bullion market and changes in gross volume of FII trade. We also find (a) both way asymmetric volatility spillover between the domestic stock market and the Asian stock market and (b) its unidirectional movement from the world stock market to the domestic stock market. The results of the study may help market regulators in setting regulatory policies considering the inter-linkages and pattern of volatility spillovers across different financial markets. JEL Classification: G15, G17
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Kharka, Damber S., M. S. Turan, and K. P. Kaushik. "Stock Market Integration in South Asia." INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 1, no. 2 (July 25, 2012): 8–20. http://dx.doi.org/10.24297/ijmit.v1i2.1442.
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While the topic of stock market integration has been one of the highly researched area in the literature but focus had mostly been on the stock markets of developed economies. Few have focused on analyzing market integration in South Asian region and no inclusion of Bhutanese stock has been found in the literature in any of the earlier studies. The objective of this paper is to analyze market integration between Bhutanese, Indian and other indices in the region. We also analyzed whether other indices in the region are co-integrated with Indian stock market, as Indian market is more proficient in the region and can be believed to have influences on others. We analyzed all indices in the region on one to one basis (using pairwise co-integration test). We used weekly data from January 2006 to December 2011 period from the stock exchanges of (Bhutan, India, Nepal, Bangladesh, and Pakistan). Applying, Dickey-Fuller method, we tested unit root for each stock indices and used Johansen co-integration approach pairwise to test the long-term relationship between stock indices and multivariate approach to test market integration as a whole. We found that all indices are stationary at I(1) and confirmed no long-term relationship between Bhutanese stock with Indian and other regional stock markets. In fact we find no market integration either on one to one basis or for the south Asian market as a whole. Information on market integration should help market players in managing their investments in capital markets in a sustainable manner.
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Kousar, Rehana, Zahid Imran, Qaisar Maqbool Khan, and Haris Khurram. "Impact of Terrorism on Stock Market: A Case of South Asian Stock Markets." Journal of Accounting and Finance in Emerging Economies 5, no. 2 (November 12, 2019): 215–42. http://dx.doi.org/10.26710/jafee.v5i2.852.
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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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Rawlin, Rajveer S., and Satya Surya Narayana Raju Pakalapati. "Forecasting Stock Prices of Select Indian Private Sector Banks – A Time Series Approach." SDMIMD Journal of Management 13, no. 1 (March 1, 2022): 35. http://dx.doi.org/10.18311/sdmimd/2022/29270.
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<p>Forecasting stock markets and individual stocks has been a well-researched area in the world of finance. Fundamental and technical analysis is widely used by investors in analysing stock prices. Researchers have used various methods to predict stock prices such as Hidden Markov models, genetic algorithms and neural networks (Enke, Grauer, and Mehdiyev, 2011; Hassan, Nath, and Kirley 2007). Time series analysis is used in forecasting asset prices (Long et al, 2021; Eita, 2012). Indian private sector banks are among the best-performing stocks on the Indian stock exchanges over the last decade, as they have consistently captured market share from their public sector counterparts. ARIMA is a useful technique to forecast stock and stock index prices (Box and Jenkins, 1970). This study aimed to evaluate the effectiveness of the ARIMA model in forecasting private bank stock prices in India. Forecasted values differed from actual prices, suggesting markets may be efficient and other variables may also prove to be influential in forecasting Indian private bank stock prices.</p>
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Kirkulak Uludag, Berna, and Muzammil Khurshid. "Volatility spillover from the Chinese stock market to E7 and G7 stock markets." Journal of Economic Studies 46, no. 1 (January 7, 2019): 90–105. http://dx.doi.org/10.1108/jes-01-2017-0014.
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PurposeThe purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.Design/methodology/approachThe authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.FindingsThe findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.Originality/valueTo the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.
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Chellaswamy, Karthigai Prakasam, Natchimuthu N, and Muhammadriyaj Faniband. "Stock Market Reforms and Stock Market Performance." International Journal of Financial Research 12, no. 2 (January 14, 2021): 202. http://dx.doi.org/10.5430/ijfr.v12n2p202.
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This paper analyses the impact of stock market reforms on the stock market performance in India using regression based event-study method. We consider nine stock market reforms introduced from 1998 to 2018. We find that the impact of stock market reforms on Nifty trading volume and Nifty return is different. This paper documents that the impact of the additional volatility measures, T+3 and T+2 settlement cycles, and margin provisions for intra-day crystallized losses reforms show a positive impact on trading volume post-reform. In contrast, internet trading, prohibition of fraudulent and unfair trade practices, delisting of equity shares, substantial acquisition of shares and takeovers listing obligations and disclosure requirements reforms decrease the trading volume post-reform. Our results of Nifty return reveal that the additional volatility measures, the T+2 settlement cycle, the prohibition of fraudulent and unfair trade practices, substantial acquisition of shares and takeovers, listing obligations and disclosure requirements have a significant and positive impact on return post-reform. It is evident that the impact of all nine stock market reforms is insignificant on Nifty return.
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Bagade, Mr Ketan, and Prof Varsha Bhosale. "Artificial Intelligence based Stock Market Prediction Model using Technical Indicators." International Journal of Innovative Technology and Exploring Engineering 11, no. 6 (May 30, 2022): 34–39. http://dx.doi.org/10.35940/ijitee.f9915.0511622.
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The indian stock market is highly volatile and complex by nature. However, notion of stock price predictability is typical, many researchers suggest that the Buy & Sell prices are predictable and investor can make above-average profits using efficient Technical Analysis (TA).Most of the earlier prediction models predict individual stocks and the results are mostly influenced by company’s reputation, news, sentiments and other fundamental issues while stock indices are less affected by these issues. In this work, architecture of project is given.As a part of prediction model the Long Short-Term Memory (LSTM), Support Virtual Machine (SVM) are used to predict future prices Stock Technical Indicators(STIs) are used to generate a buy sell signals. The project will be carried on National Stock Exchange (NSE) Stocks of India.
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Kinslin, D., and V. P. Velmurugan. "The Relationship between Macroeconomic Factors and Stock Market Indices Performances in Indian Stock Market." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 592. http://dx.doi.org/10.14419/ijet.v7i4.36.24206.
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This investigation endeavors in observationally testing the connection between macroeconomic variables and the exhibitions of two noteworthy Indian security advertise lists of BSE-sensex and NSE-clever. The yearly information of a few macroeconomic elements of FIIs net venture, trade rates, oil value, financing costs, swelling rates and gold rates from 1995-96 to 2014-15 are thought about and it attempts to uncover the most impact of these elements on the 'Stock files exhibitions' of the Indian securities exchange. In compatibility of this, the connection investigation and various relapse examination was utilized to contemplate the connection between the two chose security advertise files exhibitions and the six chose macroeconomic elements from the Indian economy. The significant finding is that macroeconomic elements impact securities exchange lists exhibitions in India. It is suggested that the usage of appropriate monetary approaches will be useful to money markets files and it will result in required development in the Indian capital market.
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Sadeghzadeh, Emsen. "Effects of geopolitical risks and political uncertainties on stock markets: Country specific new generation panel data analysis for developing Asian countries." Journal of Process Management and New Technologies 10, no. 1-2 (2022): 82–101. http://dx.doi.org/10.5937/jouproman2201082s.
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In general, there are strong and meaningful relationships between risks and uncertainties, and economic activities. In this context, geopolitical risks (GPR) and global economic and political uncertainties (WUI) can significantly affect financial markets and investor behavior. In this study, the effects of GPR and WUI on stock markets for 10 developing Asian countries were investigated for 2001:M07-2020:M12 period. Cross-section dependency was examined with LM, 𝐿𝑀𝑆 , 𝐶𝐷 and 𝐿𝑀𝐵𝐶 tests, series stationarity with Hadri and Kurozumi (2012) test, cointegration relations with Westerlund (2006) cointegration with multiple structural breaks method, and regression analyzes with Eberhardt and Bond (2009) method. It was determined that high GPR decreases the stock market index in Turkey, Korea, Russia, Indonesia and Malaysia, whereas it increases in India, Thailand and Philippines. It was found that high WUI decreases the stock market index in Korea, China, Indonesia and Thailand, whereas it increases in Turkey, India and Malaysia. On the other hand, while the stock market returns of the change in GPR decreases the stock market returns in Turkey, Korea, Russia, Indonesia and Malaysia, it increases in India, Thailand and Philippines. It has been determined that change in WUI decreases the stock return in Korea, China, Indonesia and Thailand, and it increases in Turkey, India and Malaysia. It was also observed that changes in GPR increases the volatility of the stock markets in India, Thailand and Philippines, and it decreases in Turkey, S. Korea, Russia, Indonesia and Malaysia. While the effects of change in WUI increases stock market volatility in Turkey and Malaysia, it decreases in Korea, China, Indonesia and Thailand. As the results achieved are heterogeneous, investors should avoid a basket trading strategy in these countries. Country-specific causality test was carried out with the Konya (2006) method, and it was observed that there are causal relationships between high WUI and stock market index, high WUI and stock market return in Turkey. Similarly, causal relationships were determined between high WUI and stock market index in India, between change in WUI and stock market index volatility in Philippines, between high GPR and stock market index, change in GPR and stock market return in Hong Kong. Causal relationships for all countries in the panel were examined using the Dumitrescu and Hurlin (2012) method, and causality was only found between high WUI and stock market index.
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Sadeghzadeh Emsen, Hatıra. "EFFECTS OF GEOPOLITICAL RISKS AND POLITICAL UNCERTAINTIES ON STOCK MARKETS: COUNTRY SPECIFIC NEW GENERATION PANEL DATA ANALYSIS FOR DEVELOPING ASIAN COUNTRIES." Journal of process management and new technologies 10, no. 1-2 (June 21, 2022): 82–101. http://dx.doi.org/10.5937/jpmnt10-38252.
Full textAbstract:
In general, there are strong and meaningful relationships between risks and uncertainties, and economic activities. In this context, geopolitical risks (GPR) and global economic and political uncertainties (WUI) can significantly affect financial markets and investor behavior. In this study, the effects of GPR and WUI on stock markets for 10 developing Asian countries were investigated for 2001:M07-2020:M12 period. Cross-section dependency was examined with LM, and tests, series stationarity with Hadri and Kurozumi (2012) test, cointegration relations with Westerlund (2006) cointegration with multiple structural breaks method, and regression analyzes with Eberhardt and Bond (2009) method. It was determined that high GPR decreases the stock market index in Turkey, Korea, Russia, Indonesia and Malaysia, whereas it increases in India, Thailand and Philippines. It was found that high WUI decreases the stock market index in Korea, China, Indonesia and Thailand, whereas it increases in Turkey, India and Malaysia. On the other hand, while the stock market returns of the change in GPR decreases the stock market returns in Turkey, Korea, Russia, Indonesia and Malaysia, it increases in India, Thailand and Philippines. It has been determined that change in WUI decreases the stock return in Korea, China, Indonesia and Thailand, and it increases in Turkey, India and Malaysia. It was also observed that changes in GPR increases the volatility of the stock markets in India, Thailand and Philippines, and it decreases in Turkey, S. Korea, Russia, Indonesia and Malaysia. While the effects of change in WUI increases stock market volatility in Turkey and Malaysia, it decreases in Korea, China, Indonesia and Thailand. As the results achieved are heterogeneous, investors should avoid a basket trading strategy in these countries. Country-specific causality test was carried out with the Konya (2006) method, and it was observed that there are causal relationships between high WUI and stock market index, high WUI and stock market return in Turkey. Similarly, causal relationships were determined between high WUI and stock market index in India, between change in WUI and stock market index volatility in Philippines, between high GPR and stock market index, change in GPR and stock market return in Hong Kong. Causal relationships for all countries in the panel were examined using the Dumitrescu and Hurlin (2012) method, and causality was only found between high WUI and stock market index.
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Sweeney, Richard J., and Jianhua Zhang. "India and Pakistan Go Nuclear: The Economic Costs for India, Pakistan — and China." Review of Pacific Basin Financial Markets and Policies 02, no. 03 (September 1999): 341–73. http://dx.doi.org/10.1142/s0219091599000199.
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Quantitative estimates show that India's nuclear tests caused important economic damage to India and its neighbors, Pakistan and China. Pakistan's tests caused further economic damage to all three countries. In response to India's tests, India's stock market fell by 7.26 percent, Pakistan's by 10.59 percent and China's by 2.70 percent. In response to Pakistan's tests, India's stock market fell by another 5.57 percent, Pakistan's by 16.82 percent and China's by 3.93 percent. Overall, the two countries' tests caused India's stock market to fall by 12.83 percent, Pakistan's by 27.41 percent and China's by 6.63 percent. Some argue that going nuclear increased India and Pakistan's national security and their international political standing. In the financial markets' opinion, these tests caused major reductions in both countries' economic security, and harmed China's economic security. The tests had no important effects on the Group of Ten countries' stock markets; thus, the tests' economic effects seem for the moment of be confined to southern Asia.
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Seth, Neha, and Laxmidhar Panda. "Time-varying Correlation Between Indian Equity Market and Selected Asian and US Stock Markets." Global Business Review 21, no. 6 (August 7, 2019): 1354–75. http://dx.doi.org/10.1177/0972150919856962.
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The purpose of this article is to examine the dynamic relationship between the Indian stock market and the selected Asian and US stock markets during the post-crisis period. This article uses univariate GARCH (Generalized Autoregressive Conditional Heteroskedasticity) family models on daily observations from March 2009 to December 2015 to evaluate the volatility persistence and leverage effect on Asian developed (Japan, Singapore and Hong Kong) and emerging markets (India, China, Indonesia, Korea, Malaysia and Taiwan) along with the US stock market. AR (Autoregressive) ( 1 )-GARCH (1, 1)-ADCC (Asymmetric DCC) model is employed to find out the dynamic correlation between the Indian equity market and other selected stock markets. The results of the present study give evidence of the leverage effect in conditional volatility but not in conditional correlation, which implies that the rise in conditional volatility is more due to negative shocks than positive ones. On the other hand, dynamic conditional correlation (DCC) does not support any asymmetric effect for the time-varying correlation. The result of average conditional correlation shows the existence of higher diversification opportunities for Indian investors in Malaysian, Chinese and Japanese stock markets (having lower conditional correlation) than in Hong Kong, Indonesian and South Korean markets. The DCC fluctuates more in the cases of India with Singapore, Hong Kong and Indonesia over the sample period. It indicates that the stability of DCC is less reliable and the coefficient of correlation may not be used as a guide for portfolio decisions. But the cases of India with the USA, Japan and China show more stable conditional correlation coefficients. This article investigates the volatility persistence and time-varying relationship among Asian stock markets during the recent period, 2009–2015. The results of this article may be helpful in international portfolio planning and will contribute towards the literature on asymmetric time-varying relationships among Asian markets.
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Veerappa, Beeralaguddada Srinivasa. "Cointegration of Asian Stock Markets: Empirical Evidence from India." GIS Business 11, no. 5 (September 23, 2016): 25–40. http://dx.doi.org/10.26643/gis.v11i5.3412.
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At present stock return is significantly related to other global stock markets. The present paper empirically investigates the short run and long run equilibrium relationship between the stock market of India, Japan Hong Kong, Singapore, Malaysia, China, and Australia monthly data during January 1995 to December 2013. Researcher employs correlation test, multivariate co-integration framework, Vector Auto Regressive error-correction model and Granger causality test with reference to financial up evils in Asia and world viz., Asian crisis (1997/98), financial crisis (2008) Inflation conditions, Natural disasters, financial up evils etc. of long run relationship. Results find that the Indian stock market return is significantly co-integrated with long run and short run situations/causalities in Asian Stock returns.
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Setiawan, Budi, and Muhammad Hidayat. "PENGARUH PASAR MODAL NEGARA G-3 TERHADAP PASAR MODAL ASEAN-5." Jurnal Ilmiah Ekonomi Global Masa Kini 8, no. 3 (January 8, 2018): 11–15. http://dx.doi.org/10.36982/jiegmk.v8i3.348.
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The stock market has captured the attention of many practitioners and scholars in the past decade. It has become one of the most vital aspects of a modern market economy. The stock market provides companies with access to capital and gives opportunity for investors to have a slice of company ownership. The present paper investigates the impact of G-3 stock markets (US, Japan and Europe) to ASEAN-5 stock markets (Indonesia, Malaysia, Philippines, Thailand and Singapore). The data coverage is composed of daily closing stock index at G-3 stock markets and ASEAN-5 stock markets over the period from January 4, 2000 to December 31, 2014. The historical stock market data were analyzed by using Structured Equation Model (SEM). The empirical results suggest that the G-3 stock markets have a positive and significant impact on ASEAN-5 stock markets. For further, the researcher could add other Asia stock markets such as Nikkei225 Index (Japan), Hang Seng Index (Hong Kong), Kospi Index (South Korea), and BSE Index (India).Keywords: G-3 Stock Markets, ASEAN-5 Stock Markets, Structured Equation Model, Stock Market Diversification; Contagious Effect.Â
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Bansal, Ved Prakash. "The Effect of Seasonality over Stock Exchanges in India." Journal of Business Management and Information Systems 4, no. 1 (June 30, 2017): 65–72. http://dx.doi.org/10.48001/jbmis.2017.0401008.
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This study investigated to examine stock market seasonality effect in Indian stock market for Bombay Stock Exchange (BSE) 100. The monthly return data of BSE 100 for the period from April, 2001 to March, 2016 was used for analysis. After examining the stationarity of the return series and correlogram, regression equation & ARIMA model is used to find the monthly effect in stock returns in India. The results confirmed the existence of seasonality in stock returns in India.
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Debnath, Pradip, and Hari Mohan Srivastava. "Optimizing Stock Market Returns during Global Pandemic Using Regression in the Context of Indian Stock Market." Journal of Risk and Financial Management 14, no. 8 (August 19, 2021): 386. http://dx.doi.org/10.3390/jrfm14080386.
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Stock markets around the world experienced a massive collapse during the first wave of COVID-19. Roughly in the month of January 2021, the second wave of COVID-19 struck in India, reaching its peak in May, and by the end of May, the active cases started to decline. A third wave is again predicted by the end of 2021, and as such, the COVID-19 pandemic seems to have become a periodic phenomenon over the last couple of years. Therefore, the study of the behavior of the stock market as well as that of the investors becomes very interesting and crucial in this highly volatile and vulnerable market trend. Motivated by these facts, in the present paper, the researcher develops a model for portfolio management, using curve-fitting techniques and shows that this model can encounter the market volatility efficiently in the context of the Indian stock market. The portfolio is designed based on data taken from the National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020. The performance of the portfolio in real-life situation during 1 January 2021 to 21 May 2021 is examined, assuming investments are made according to the proposed model.
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Mondal, Ashoke. "Impact of First Wave of Covid-19 Pandemic on Stock Returns: Evidence from the Indian Stock Market." MUDRA: Journal of Finance and Accounting 9, no. 1 (2022): 114–28. http://dx.doi.org/10.17492/jpi.mudra.v9i1.912207.
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At present, the world is facing challenges resulting from the outbreak of Covid-19 pandemic. The waves of the pandemic have impacted the the Indian economy also in a big way. Due to Covid-19, major stock indices of India have suffered fall in their levels. In India, market capitalisation of ninety per cent of the listed companies have been eroded. In this paper, an attempt has been made to study the responses of the stock market due to the Covid-19 pandemic. For that purpose, event study methodology has been used and the share prices of twenty companies on the BSE SENSEX have been considered. It is concluded that the stock market has reacted negatively after the identification of Covid-19 and even before the declaration of lockdown. After the declaration of lockdown, positive movement of share prices of the selected stocks has been noticed.
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Narula, Samridhi, and Saqib Khan. "Factors Affecting the Indian Stock Market." International Journal For Multidisciplinary Research 04, no. 04 (2022): 353–62. http://dx.doi.org/10.36948/ijfmr.2022.v04i04.038.
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One of the important contributions of this study is that in India, very little/almost no work has been done to understand the factors affecting the stock market prices after the recent recession. The present study examines the relationship between stock prices and a set of macroeconomic variables to examine if there is any specific variable which has the most influence on the stock market of India. The study aims to find out the factors affecting the Indian stock market by using correlation and regression analysis. To investigate the correlation between SENSEX, Consumer Price Index (CPI) which is a proxy of inflation, Foreign Institutional Investment (FII), Exchange Rate, NASDAQ index, Gold prices, Index of Industrial Production (IIP) in India from the period 2018 to 2021. The results show that the highest correlation exists between SENSEX and NASDAQ followed by NASDAQ and Gold prices. Furthermore, SENSEX is positively related to all of the selected variables. To assess the impact of each variable on SENSEX returns, SENSEX is taken as a dependent variable and all other variables are taken as independent variables in the regression analysis. The regression outputs of only NASDAQ and Gold are statistically significant at 5% level. Granger Causality suggests no bidirectional relationship among any of the variables. However, there exists a unidirectional relationship between some of the variables.
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Bhattacharjee, Nayanjyoti, and Anupam De. "A Perspective on Industry Classification and Market Reaction to Corporate News: Evidence from India." Scientific Annals of Economics and Business 65, no. 1 (March 1, 2018): 31–50. http://dx.doi.org/10.2478/saeb-2018-0001.
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Abstract In this paper, we provide a cross-industry perspective on the market reaction to different corporate news in the context of Indian stock market. We have studied the price and volume movements associated with eight broadly defined news categories namely Analyst Calls, Earnings, Earnings Forecasts, Finance, Legal and Regulatory, Management, Operations and Restructuring. We have employed the standard event study methodology on a sample of stocks listed on the National Stock Exchange of India for the purpose of our study. We observe that the market reaction to firm specific corporate news varies according to the type of news across different industry groups. We also observe that the sentiment of the news is a critical factor which influences the market reaction to such news flow across industry groups. We also provide a cross-industry perspective on the relative importance of different corporate news categories after taking into account the sentiment of the news in the context of Indian stock market.
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Palamalai, Srinivasan, and Karthigai Prakasam. "Stock Market Development and Economic Growth in India." International Journal of Finance & Banking Studies (2147-4486) 3, no. 3 (July 21, 2014): 30–46. http://dx.doi.org/10.20525/ijfbs.v3i3.187.
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The link between stock market development and economic activity has always been the subject of considerable debate in the field of economics and it raises empirical question whether stock market development influences economic activity or whether it is a consequence of increased economic activity. This study attempts to investigate the direction of causality between stock market development and economic growth in the Indian context. Using the cointegration and causality tests for the period June 1991 to June 2013, the study confirms a well defined long-run equilibrium relationship between the stock market development indicators and economic growth in India. The empirical results show bidirectional causality between market capitalisation and economic growth and unidirectional causality from turnover ratio to economic growth in the long-run and short-run. By and large, it can be inferred that the stock market development indicators viz. market capitalisation and turnover ratio have a positive influence on economic growth in India.
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Khan, Salleh Nawaz, and Mohamad Saad Aslam. "Co-integration of Karachi Stock Exchange with major South Asian Stock Exchanges." International Journal of Accounting and Financial Reporting 4, no. 1 (March 31, 2014): 106. http://dx.doi.org/10.5296/ijafr.v4i1.5454.
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International cross listing have amplified the interest of academics and investors to the subject of co movement among the stock markets of the world . This study investigates the co integration of Pakistan stock exchange (KSE 100 index) with major stock exchanges of south Asia . The results reveals that there is no co integration of Pakistan’s stock market (KSE100 index) with china and Japan stock markets. However there is co integration of Pakistan’s stock market (KSE 100 index) with the stock market of India, Indonesia, Malaysia and Singapore.
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Aggarwal, Dr Mamta, Dr Meera Bamba, and Indu Bansal. "Analysing Volatility Dynamics of India and US Stock Market." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (June 30, 2023): 1821–26. http://dx.doi.org/10.22214/ijraset.2023.53957.
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Abstract: Analysing the risk-return trade-off of financial assets, volatility is a key factor. Volatility promotes market liquidity and demonstrates the effectiveness of the financial system. To have an insights of India And US Market Volatility behaviour, this paper examines the volatility dynamics of India And US Stock market by taking Sensex And S & P 500 daily closing prices for the 2nd January 2003 to 31st December 2019. The authors have two questions to examine about volatility whether India and US stock market volatility shows volatility clustering and volatility persistence or not. ARCH LM test and Ljung Box Q2 statistics were used to check for volatility clustering. And for volatility persistence GARCH (1,1) model is used. The results of the study confirm the presence of volatility clustering in in both India And US stock market. Additionally, Indian stock return volatility shows lower volatility persistence than US. The results of the study are quite useful for the academicians, policy makers and investor community in general
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Ullah, Muhammad Usman Sana, Naveed Ul Haq, Hood Laeeq, and Ammar Aftab Raja. "Financial Contagion and Globalization: Evidence from South Asian Countries." International Business and Accounting Research Journal 2, no. 2 (July 6, 2018): 61. http://dx.doi.org/10.15294/ibarj.v2i2.40.
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This study investigates the contagion and globalization between the South Asian (Pakistan, India, Bangladesh and Sri Lanka) and five largest economies (US, UK, China, Japan and Germany) stock markets. Daily stock returns data from 1st July 1997 to 30th June 2015 consisting of total 4695 observation is analyzed. DCC GARCH is applied to calculate the conditional correlation coefficients to overcome the issue of heteroscedasticity. Null hypothesis of no globalization got rejected eleven times out of twenty while the hypothesis of no contagion got rejected six times. Further analysis of conditional correlation coefficients confirmed the impact of 9/11 attacks, Subprime mortgage crises and Europeans debt crises on the Indian market. Impact of 9/11 attacks also found on Pakistani and Sri Lankan stock exchanges, while Dhaka stock exchange remained independent of all shocks. In sum, the South Asian stock markets remained isolated from the global shocks except India. Isolation of South Asian stock markets from the global shocks is due to their lower integration with the global markets. This study provides some useful recommendations to the investors and policy makers. Results suggests that Indian stock exchange get contagion impact from the major economies, so authorities of India should have to take measure to decouple the market from the global shocks. The markets of Bangladesh, Sri Lanka and Pakistan are not properly integrated with global financial system, so the authorities of these countries should have to take proper steps to liberalize the markets. This paper presents the first empirical study on financial contagion and globalization of South Asian countries.
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Chaudhary, Rashmi, Priti Bakhshi, and Hemendra Gupta. "The performance of the Indian stock market during COVID-19." Investment Management and Financial Innovations 17, no. 3 (September 16, 2020): 133–47. http://dx.doi.org/10.21511/imfi.17(3).2020.11.
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The current empirical study attempts to analyze the impact of COVID-19 on the performance of the Indian stock market concerning two composite indices (BSE 500 and BSE Sensex) and eight sectoral indices of Bombay Stock Exchange (BSE) (Auto, Bankex, Consumer Durables, Capital Goods, Fast Moving Consumer Goods, Health Care, Information Technology, and Realty) of India, and compare the composite indices of India with three global indexes S&amp;P 500, Nikkei 225, and FTSE 100. The daily data from January 2019 to May 2020 have been considered in this study. GLS regression has been applied to assess the impact of COVID-19 on the multiple measures of volatility, namely standard deviation, skewness, and kurtosis of all indices. All indices’ key findings show lower mean daily return than specific, negative returns in the crisis period compared to the pre-crisis period. The standard deviation of all the indices has gone up, the skewness has become negative, and the kurtosis values are exceptionally large. The relation between indices has increased during the crisis period. The Indian stock market depicts roughly the same standard deviation as the global markets but has higher negative skewness and higher positive kurtosis of returns, making the market seem more volatile.
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Hiremath, Gourishankar S., Hari Venkatesh, and Manish Choudhury. "Sports sentiment and behavior of stock prices: a case of T-20 and IPL cricket matches." Review of Behavioral Finance 11, no. 3 (August 12, 2019): 266–76. http://dx.doi.org/10.1108/rbf-04-2018-0043.
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Purpose The purpose of this paper is to examine whether the emotions and sentiments related to the outcome of the sporting event influence the investment making process. Design/methodology/approach This study uses the data on stock prices of firms sponsoring the Indian premier league (IPL) teams and data on Indian stock market. The event-study frameworks along with autoregressive moving average and GMM regression are employed to empirical quantify the impacts of the performance of the IPL teams on the stock market returns of the sponsors’ stocks and response of Indian stock market to the outcome of T-20 international matches. Findings The paper finds that the team winning IPL title in a season has a positive impact on the returns of the sponsors’ stocks of a particular team, whereas loss of team has a negative impact on returns. The outcome of the cricket matches played by team India in the T-20 has a negligible effect on the Indian stock market. Practical implications The finding of the study implies the coexistence of emotions and rationality at different points in time and the relevance of adaptive market hypothesis to explain such time-varying behavior. Originality/value The present investigation is first of its kind to test whether the performance of the IPL cricket team can influence the stock returns of the sponsors. This research shows that sentiment related to sports event such as cricket influences the decision-making process and thus affects underlying stock prices.
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Bhunia, Amalendu, and Devrim Yaman. "Opportunity or Crisis? Volatility and Leverage Effect in the World’s Largest Economies." International Journal of Accounting and Financial Reporting 9, no. 4 (October 11, 2019): 1. http://dx.doi.org/10.5296/ijafr.v9i4.15609.
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This paper examines the relationship between asset volatility and leverage for the three largest economies (based on purchasing power parity) in the world; US, China, and India. Collectively, these economies represent Int$56,269 billion of economic power, making it important to understand the relationship among these economies that provide valuable investment opportunities for investors. We focus on a volatile period in economic history starting in 1997 when the Asian financial crisis began. Using autoregressive models, we find that Chinese stock markets have the highest volatility among the three stock markets while the US stock market has the highest average returns. The Chinese market is less efficient than the US and Indian stock markets since the impact of new information takes longer to be reflected in stock prices. Our results show that the unconditional correlation among these stock markets is significant and positive although the correlation values are low in magnitude. We also find that past market volatility is a good indicator of future market volatility in our sample. The results show that positive stock market returns result in lower volatility compared to negative stock market returns. These results demonstrate that the largest economies of the world are highly integrated and investors should consider volatility and leverage besides returns when investing in these countries.
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MISHRA, A. K. "THE MARKET REACTION TO STOCK SPLITS — EVIDENCE FROM INDIA." International Journal of Theoretical and Applied Finance 10, no. 02 (March 2007): 251–71. http://dx.doi.org/10.1142/s0219024907004226.
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Stock splits are a relatively new phenomenon in the Indian context. This paper examines the market effect of stock splits on stock price, return, volatility, and trading volume around the split ex-dates for a sample of stock splits undertaken in the Indian stock market over the period 1999–2005. The traditional view of stock splits as cosmetic transactions that simply divide the same pie into more slices is inconsistent with the significant wealth effect associated with the announcement of a stock split. However, the empirical evidence confirms a negative effect on price and return of stock splits. The overall cumulative abnormal returns after the split are negative. These results suggest that stock splits have induced the market to revise its optimistic valuation about future firm performance, rejecting signaling hypothesis to which splits convey positive information to markets. Hence, stock splits have reduced the wealth of the shareholders. The results also show that presence of a positive effect on volatility and trading volume following the split events, thus suggesting that split events enhance liquidity.
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Kumar, Rakesh, and Raj S. Dhankar. "Asymmetric Volatility and Cross Correlations in Stock Returns under Risk and Uncertainty." Vikalpa: The Journal for Decision Makers 34, no. 4 (October 2009): 25–36. http://dx.doi.org/10.1177/0256090920090403.
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Capital market efficiency is a matter of great interest for policy makers and investors in designing investment strategy. If efficient market hypothesis (EMH) holds true, it will prevent the investors to realize extra return by utilizing the inherent information of stocks. They will realize extra returns only by incorporating the extra risky stocks in their portfolios. While empirical tests of EMH and risk-return relationship are plentiful for developed stock markets, the focus on emerging stock markets like India, Pakistan, Sri Lanka, etc., began with the liberalization of financial systems in these markets. With globalization and deregulation, the enormous opportunities of investment in South Asian stock markets have attracted the domestic and foreign institutional investors in general, and to reduce their portfolio risk by diversifying their funds across the markets in particular. The efforts are made in this study to examine the cross-correlation in stock returns of South Asian stock markets, their regional integration, and interdependence on global stock market. The study also examines the important aspects of investment strategy when investment decisions are made under risk and uncertainty. The study uses Bombay stock exchange listed index BSE 100 for India, Colombo stock exchange listed Milanka Price Index for Sri Lanka, Karachi stock exchange listed KSE 100 for Pakistan, Dhaka stock exchange listed DSE-General Index for Bangladesh, and S & P Global 1200 to represent the global market. It carries out a comprehensive analysis, tracing the autocorrelation in stock returns, cross correlations in stock returns under risk and uncertainty, interdependency among the South Asian stock markets, and that with the global stock market. The research methodology applied in the study includes application of Ljung-Box to examine the cross-correlation in stock returns, ARCH and its generalized models for the estimation of conditional and asymmetric volatilities, and Ljung-Box as a diagnostic testing of fitted models, and finally correlation to examine the interdependency of these markets in terms of stock returns and expected volatility. The results bring out the following: L-B statistics suggests the presence of autocorrelation in stock returns in all Asian stock markets; however, for the global market, autocorrelations are significant at 15 lags, and thereafter they are insignificant. The significant autocorrelations in stock returns report volatility clustering in stock returns, reject the EMH, and hold that current stock returns are significantly affected by returns being offered in the past. ARCH and its generalized models significantly explain the conditional volatility in all stock markets in question. The study rejects the relationship between stock returns and expected volatility; however, the relationship is significant with unexpected volatility. It brings out that investors adjust their risk premium for expected variations in stock prices, but they expect extra risk premium for unexpected variations. With their entry into the liberalization phase, South Asian stock markets have reported regional interdependence, and also interdependence with the global stock market.
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Mohanty, Debasis, Amiya Kumar Mohapatra, Sasikanta Tripathy, and Rahul Matta. "Nexus between foreign exchange rate and stock market: evidence from India." Investment Management and Financial Innovations 20, no. 3 (July 31, 2023): 79–90. http://dx.doi.org/10.21511/imfi.20(3).2023.07.
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This study examines the impact of foreign exchange rate fluctuations on various NSE capitalized indices of India. Five exchange rates were chosen based on trading contracts in the currency derivative segment of NSE. These exchange rates are US Dollar-Indian Rupee (USD/INR), Euro-Indian Rupee (EUR/INR), Great Britain Pound-Indian Rupee (GBP/INR), Chinese Yuan-Indian Rupee (CNY/INR) and Japanese Yen-Indian Rupee (JPY/INR), which are used as a regressor in this study. The data of NSE Nifty large-cap 100, Nifty mid-cap 100 and Nifty small-cap from December 1, 2012 to December 1, 2022 was considered for the study. GARCH (1, 1) model was used to analyze the nexus between exchange rate fluctuations and capitalized indices, and it was further validated by DCC GARCH to evaluate the volatility spillover. The result shows that exchange rate fluctuations have a positive effect on stock market volatility along with a varying degree of incidence on small-cap, mid-cap, and large-cap. DCC α has been found to be significant in USD &amp; GBP for small-cap, and GBP &amp; CNY for mid-cap. On the other hand, USD, Euro, CNY and JPY have a significant impact on the large-cap index in the short-run. Further, it is found that there is long-run spillover effect (DCC β) of exchange rates on all capitalized indices of the Indian stock market, and it is highest in in the large-cap case.
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De Sarkar, Partha, Surendra S. Yadav, and D. K. Banwet. "Integration of Indian Capital Markets with Global Markets: An Empirical Study." Vision: The Journal of Business Perspective 6, no. 2 (July 2002): 73–79. http://dx.doi.org/10.1177/097226290200600207.
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From 1997 onwards, the effect of globalization is becoming evident in the Indian capital markets. The stock prices of Indian companies and the stock market indices have been driven not just by the macro and micro factors of the Indian economy. Events in other parts of the world have also increasingly started having an impact. This is in stark contrast to the situation in the insular days prior to 1991, when major policy changes were made by the Indian government to open up the economy. The increased volatility of stock markets and reduction in controls over capital movements across borders has reflected in the stock prices in India. This paper aims at validating that indeed globalization has found its way into the Indian capital markets. It estimates the extent of correlation between the major world stock markets in USA, UK, Japan and Hong Kong with the Indian Stock Market Index like the BSE Sensex and also how portfolio fund flows have affected its movement. The study restricts itself to the period between January 1997 and June 2000. In brief, this paper seeks to: establish the relationship between the Bombay 30 Stock Sensitivity Index (SENSEX) and the global indices mentioned above like Dow Jones Industrial Average, NASDAQ Composite of USA, FTSE100 of UK, Nikkei 225 of Japan and the Hang Seng of Hong Kong. look at how portfolio funds flows have been affecting the Indian stock market.
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Venkataiah, Dr G. C., M. Yellaiah Naidu, and Dr M. Paparao. "Analysis of Influencing Factors of Investor’s Perceptions on Indian Stock Markets." Revista Gestão Inovação e Tecnologias 11, no. 4 (September 27, 2021): 5629–33. http://dx.doi.org/10.47059/revistageintec.v11i4.2587.
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Investing in the Indian stock market is a great way for groups of investors to pool their funds for a common goal. Stock market schemes in India are managed by companies sponsored by financial institutions, banks, private companies, or international companies. This study was conducted to learn more about people's attitudes toward investing in the Indian stock market. For this study, the researcher spoke with 101 people who have invested in stock markets such as the BSE and NSE. The study is empirical in nature, and the universe for this study is Hyderabad city investors, with convenient sampling as the sampling technique. This study relied on primary data gathered through a structured questionnaire. The findings of the study suggest that stock market investors should pay close attention to other factors such as currency fluctuations, international relationships, tax rates, inflation rates, and political decisions, as these factors have an impact on stock market prices at the BSE and NSE, and that international relationships, tax rates, and political decisions influence investor perceptions.
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Qadri, Syed Usman, Naveed Iqbal, and Syeda Shamaila Zareen. "Stock Return Predictability and Market Efficiency in Pakistan; A Role of Asian Growing Economies of India and Malaysia." ANNALS OF SOCIAL SCIENCES AND PERSPECTIVE 2, no. 2 (November 24, 2021): 257–67. http://dx.doi.org/10.52700/assap.v2i2.95.
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The purpose of this study is to determine the predictability of the Pakistani stock market's one-day forward returns by utilizing lagged daily returns for Pakistan, India, and Malaysia from 2006 to 2016. The findings indicate that lagged Pakistani market returns significantly predict Pakistani one-day ahead market returns. However, the other two growing stock markets, India and Malaysia, show no association with one-day ahead market returns. Mostly, stock market behavior in the pre-2008 and post-2008 eras was the same, although industry return behaviour was different due to the economic crisis of 2008. However, the Pakistani stock market one-day ahead returns predict the own Pakistani lag returns due to an inefficient market and prices do not follow a random walk. As a result, investors and financial analysts can foresee and generate anomalous returns by using previous data and information.
Key words: Stock Market Returns Predictability, Stock Market crash, Market efficiency
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Dawar, Varun. "Earnings persistence and stock prices: empirical evidence from an emerging market." Journal of Financial Reporting and Accounting 12, no. 2 (September 30, 2014): 117–34. http://dx.doi.org/10.1108/jfra-06-2013-0044.
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Purpose – This study aims to investigate the persistence ability of accounting variables, namely, abnormal earnings, book value, accruals and cash flows over a period of time and their valuation relevance in Indian scenario. Design/methodology/approach – The study utilizes the generalized version of the Ohlson model which links market prices with abnormal earnings, book value and earning components (accruals and cash flows). Fixed-effect panel data regression is used to analyze six years of data on the sample units to determine the persistence and valuation relevance. Findings – The findings provide evidence on the construct of persistence and value relevance of earnings and book value of equity in the Indian context. The findings further confirm that investors in India are fixated on earnings and fail to attend separately to the cash flow and accrual components of earnings while undertaking their investment decisions. Practical implications – The empirical findings of the study will enable the analysts and investors to understand the relevance and persistence of accounting variables in case of an emerging market like India. Originality/value – The study extends the extant literature on value relevance studies in developed markets to an emerging market like India and enriches it in several ways.
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Azizv, Zohaib, and Javedv Iqbalv. "Testing the Dynamic Linkages of the Pakistani Stock Market with Regional and Global Markets." LAHORE JOURNAL OF ECONOMICS 22, no. 2 (January 1, 2017): 89–116. http://dx.doi.org/10.35536/lje.2017.v22.i2.a4.
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This article examines the dynamic linkages between Pakistan’s emerging stock market and (i) the US market and (ii) the regional markets of India and Japan. Using data for the daily returns and volatility spillovers of three market pairs (Pakistan-US, Pakistan-Japan and Pakistan-India), the study estimates a series of bivariate asymmetric VARMA(1,1)-GARCH(1,1) models. It also fits multivariate asymmetric VARMA(1,1)-GARCH(1,1) models for two groups of markets: Pakistan-India-US and Pakistan-India-Japan. Based on the mean spillovers, the results suggest that the global and regional equity markets (Granger) cause the Pakistani market. There are unidirectional volatility spillovers to Pakistan from the US and Japan, while India is the only regional market with a significant cross-asymmetric effect on Pakistan. In the multivariate case, the regional and global markets have significant joint mean and variance spillovers and asymmetric effects on the Pakistani market. This indicates a weak degree of integration between the Pakistani market and the global and regional markets, implying that local risk factors – either firm-specific or country-specific – explain the expected returns on investment in the Pakistani stock market.
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Fatima, Nudrat, Muhammad Waqas, Rameez Hassan, Ahmad Fraz, and Muhammad Arif. "Cash to Price Ratio & Stock Returns: Evidence from Emerging Markets." International Journal of Economics and Finance 9, no. 11 (October 23, 2017): 153. http://dx.doi.org/10.5539/ijef.v9n11p153.
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This study examines the impact of size premium and value premium on average return in emerging economies i.e. Pakistan, India and China equity markets for the period from June 2000 to June 2015 by using three factors model. This study predicts the significance and positive relationship between value premium(C/P Ratio) and stock return for all non-financial companies listed on Karachi stock exchange, Bombay stock exchange and Shanghai stock exchange on the basis of market Capitalization. The regression results of the study illustrate that size premium predict returns more for small firms than big firms while market premium found significantly positive with stock returns in Pakistan, India, and China. Value premium is found positive for all created portfolios. Therefore, it can be concluded that value effect is present in three emerging markets. High C/P ratio outperforms the low C/P ratio stocks. In this study C/P ratio (value premium) integrated with size and market premium to check whether it can predict stock returns of small and large firms for high or low C/P ratio. The finding is similar that the positive relationship of value premium and stock return and the negative relationship of size premium and stock return. The explanatory power of Fama and French three-factor model is greater than CAPM for all three equity markets, so, the asset pricing model can facilitate investors in efficient portfolio diversification for getting enhanced returns.
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Dubey, Tanuja. "STUDY OF WEAK FORM OF MARKET EFFICIENCY IN INDIA." International Journal of Advanced Research 11, no. 07 (July 31, 2023): 1171–78. http://dx.doi.org/10.21474/ijar01/17331.
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A securitys current market price already accounts for all of its prior trading volumes and prices, according to Indias lax form of market efficiency. An investor cannot generate spectacular returns by only relying on the analysis of previous price movements because any relevant information about the security would already be reflected into its present price. The accuracy and promptness with which prices reflect information about the market is known as market efficiency. All the information from prior prices and traded volume is included in the weak version of the markets current prices. Furthermore, future prices cannot be predicted by looking at past prices. Everyone has access to past prices, even though some people can obtain them more easily than others. Liquidity traders may sell their stocks, generating price volatility, without considering the shares fundamental value. The market price reflects the intrinsic value as a result of the buying and selling of information traders. The filter rule, runs test, and serial correlation are used to assess market efficiency. Run tests have been used in this research to identify market efficiency. Information on stock prices for the selected companies was gathered from the National Stock Exchange (NSE).
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Palamalai, Srinivasan. "Stock Market Development and Economic Growth in India: An Empirical Analysis." International Journal of Finance & Banking Studies (2147-4486) 3, no. 3 (January 19, 2016): 30. http://dx.doi.org/10.20525/.v3i3.187.
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<p><em>The link between </em><em>stock market development and economic activity has always been the subject of considerable debate in the field of economics and it raises empirical question whether stock market development influences economic activity or whether it is a consequence of increased economic activity. This study attempts to investigate the direction of causality between stock market development and economic growth in the Indian context. Using the cointegration and causality tests for the period June 1991 to June 2013, the study confirms a well defined long-run equilibrium relationship between the stock market development indicators and economic growth in India. The empirical results show bidirectional causality between market capitalisation and economic growth and unidirectional causality from turnover ratio to economic growth in the long-run and short-run. By and large, it can be inferred that the stock market development indicators viz. market capitalisation and turnover ratio have a positive influence on economic growth in India.</em><em></em></p>