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Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Stock market- India"

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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Анотація:
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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2

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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Анотація:
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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3

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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Анотація:
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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4

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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Анотація:
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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5

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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Анотація:
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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6

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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Анотація:
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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7

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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Анотація:
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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8

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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Анотація:
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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9

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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Анотація:
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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10

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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Анотація:
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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Більше джерел

Дисертації з теми "Stock market- India"

1

Camilleri, Silvio J. "Emerging stock market microstructure : empirical studies of the National Stock Exchange of India." Thesis, Loughborough University, 2006. https://dspace.lboro.ac.uk/2134/7891.

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Анотація:
This thesis adopts an empirical approach to examine various market microstructure issues, using data from the National Stock Exchange of India (NSE). Whilst the respective empirical analyses may be considered as self-contained investigations, they are primarily linked through the common objective of understanding the mechanics of the pricing process as it occurs on actual markets, using the NSE as exemplar. The first major focus of the dissertation is non-synchronous trading: empirical evidence of nonsynchronicity is obtained by testing for predictability as between indices of different levels of liquidity. A simple test of the analysis of trading-break returns is proposed to infer whether predictability may be mainly attributable to non-synchronous trading or whether it constitutes a delayed adjustment of traders' expectations. The second question tackled in the thesis is whether volatility on the NSE may be considered as justified or excessive. Rathert han adopting the established methodology of comparing stock price changes to information about expected dividends, the research question is split up into two subsidiary ones. The first question is whether volatility is related to information flows, whilst the second related questionc oncernst he relationship betweenv olatility and returns. Three sources of excessive volatility are pin-pointed. Monday effects are found in index data but not in the underlying stocks-indicating index fluctuations which are not information-related. A second indicator of excessive price movements is the pronounced volatility which coincides with the fiscal year end of quoted companies but which is not accompanied by a similar increase in long-term returns. A third indication of unjustified price fluctuations is that volatility seems unrelated to returns when considering a long-term time series. The third topic of the thesis relates to the efficacy of opening and closing call auctions. This issue may be considered as the crux of the dissertation and it is tackled by analysing the effects of the suspension of a call auction system on NSE. Changes in volatility, efficiency and liquidity following the suspension are analysed, and an event study is presented. The relationship between call auctions and long-term volatility is also investigated. The findings suggest that the expected benefits of call auctions may not always materialise, possibly due to an inappropriately structured auction, or because a liquidity threshold for stocks must be surpassed for the expected benefits to accrue.
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2

Baggio, Isacco <1987&gt. "The microstructure of stock and futures market on the National Stock Exchange of India." Master's Degree Thesis, Università Ca' Foscari Venezia, 2013. http://hdl.handle.net/10579/2360.

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Анотація:
L'elaborato propone uno studio del comportamento degli investitori attivi sul mercato azionario e su quello dei futures della borsa indiana NSE National Stock Exchange, una delle principali piattaforme di e-trading del mondo per numero di scambi. Attraverso l'analisi delle scelte di investimento dei traders nel periodo compreso tra l'inizio di aprile 2006 e la fine del mese di giugno dello stesso anno, la tesi intende approfondire le dinamiche relative alla liquidità e il ruolo dei grandi investitori nel condizionare l'andamento delle transazioni. L'analisi derivante dall'applicazione di misure di liquidità del mercato e lo studio delle frequenze di trading, dei volumi e dei profitti ottenuti dagli investori permettono di evidenziare alcune delle dinamiche che governano i mercati finanziari. Lo studio è stato condotto sull'andamento del trading su un singolo asset scambiato presso NSE National Stock Exchange of India.
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3

Khan, Muhammad. "An analysis of market efficiency in the South Asian emerging stock markets : Bangladesh, India, Pakistan and Sri Lanka." Thesis, University of Dundee, 2013. https://discovery.dundee.ac.uk/en/studentTheses/83508702-3366-4045-a0b1-63adc92e3f83.

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Анотація:
This thesis investigates the weak-form of the Efficient Market Hypothesis (EMH) in the South Asian region. In particular, the emerging market countries of Bangladesh, India, Pakistan and Sri Lanka are considered. According to the weak-form of the EMH, current share prices reflect all available historical information such that investors should not be able to outperform the market on a consistent basis by trading on past information. It is an important topic for investigation given the economic growth as well as the financial development which have taken place in the region over the last two decades (South Asian Financial Markets Review, 2010). Moreover, most previous studies have investigated the topic for developed or other emerging markets; the South Asian region has largely been ignored. Prior studies which have investigated the South Asian markets have either focused on each country separately, or included one or two countries from the region as part of a broader sample. This thesis tries to fill this gap in the literature by investigating market efficiency in the South Asian markets as a regional grouping. In the first part of the analysis the long- and short-run relationships among the four stock markets are examined by employing a multivariate cointegration framework, the Vector Error Correction Model (VECM) approach, the Granger Causality test, Impulse Response Function analysis and Variance Decomposition analysis. A large sample of weekly stock index data is used in the analysis covering the 18-year period January 1993 - December, 2010. To analyse the effect of important global events on market integration, the data are split into the two sub-periods of pre- and post-September 11, 2001. The results suggest that linkages exist among the markets in both the long- as well as in the short-run. These findings imply that share price changes may be predicted from historical information not only in the market itself but from the changes in the other three markets as well. In addition, international portfolio diversification into the region may have limited benefits in the long-run as equity prices in all four countries move together in an equilibrium fashion over the longer run.In the second empirical analysis, relationship between the equity returns and macroeconomic variables is investigated. The research examines the EMH by investigating whether lagged shocks to macroeconomic variables are important in explaining equity returns. Both local and global macroeconomic variables are used and their importance in predicting the equity returns for each of the region’s markets is analysed. In particular, 12 macroeconomic variables were investigated, including seven local and five global measures being employed. Principal Components Analysis (PCA) is used to narrow down the most relevant factors. Principal Components (PCs) are then extracted and used as inputs into regressions explaining future returns. The resulting findings show that local economic factors are important in explaining share returns in the South Asian emerging stock markets. The findings support the notion that historical macroeconomic information may be used to predict share price changes in the regional markets. Finally, to investigate market linkages in greater depth, the thesis studies volatility and return interactions among the markets simultaneously. A multivariate GARCH-BEKK model is used to investigate return and volatility spillovers in own as well as in cross-markets. Results from the analysis indicated that the four markets of Bangladesh, India, Pakistan and Sri Lanka are linked not only by the news transmission about the share returns but also by the transmission of volatility. The evidence supports the notion that ‘news’ in one market influences not only the returns in that market but also the variance of price changes in other markets. These findings imply that equity returns in the South Asian stock markets are predictable from historical share price changes in their own, as well as from the other markets of the region; this result calls the weak form of the EMH into question since it suggests that an investor could outperform by studying historic return and volatility data in the region.
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4

Johansson, Christoffer, and Petter Lundström. "Finding Value Through Sustainable Performance : A cross-sectional study of the relationship between risk-adjusted return and Environmental, Social and Governance performance on the Indian stock market." Thesis, Umeå universitet, Företagsekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-105684.

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Анотація:
Problem background and discussion: Emerging countries economies are growing substantially; one of these is India which stock market has been one of the best performing in the world in recent years. Analysts are forecasting further development and some claims that India has the most business- and investment-stimulating political leaders in the world. However, stock markets in emerging countries are highly volatile and normally more risky than in developed economies. One approach to emphasise the more common risks in emerging countries are by including Environmental, Social and Governance (ESG) rating into the fundamental investment model. However, there is a conflict of what previous studies suggest regarding ESG investments. Some argues there is a positive relation and others a negative relation between ESG factors and risk- adjusted return. Research question: “Is there a relation between risk-adjusted return and ESG performance at the Indian stock market?” Objective: The objective is to determine if there is a relationship between ESG performance and risk-adjusted return in India. Another objective is to determine if there is a relationship between ESG performance and risk-adjusted return among companies with high Total ESG rating as well as for companies with low Total ESG rating. Theoretical framework: ESG is an established approach to describe sustainability issues, where screening is a process designed to select those companies that meet ESG criteria. A basic description of Capital Asset Pricing Model CAPM, which calculates an asset's expected return, has been used to calculate risk-adjusted return. Efficient Market Hypothesis EMH is the basic theory of market efficiency and is used to explain any non-linear relationship between ESG factors and risk-adjusted returns. Adaptive Market Hypothesis AMH has been taken into account as it deals with financial behaviour. Method: A quantitative study using a deductive approach has been selected to perform this study. The practical approach is a cross sectional study where the relationship in the Indian market has been analysed and significance-tested during 2014. ESG information for 126 companies listed on the Bombay Stock Exchange (BSE) has been purchased from Sustainalytics, a global leader in research for responsible investment. Empirical findings and analysis: The results of the study demonstrate no significant relationship between Total ESG rating and risk-adjusted return during 2014. In the examination of individual categories, Environmental and Social rating does not have a significant association with the risk-adjusted Return. Though, the results display a negative relationship between Governance rating and risk-adjusted return. This relationship is also obtained among companies in with low Total ESG rating but not companies with high ESG rating. Conclusion: Results implies that investors have not been able to use the information of Total ESG performance to obtain a better risk-adjusted return on the Indian stock market in 2014. However, this can be achieved by using Governance rating.
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5

Rao, Jyothi G. "A Theoretical Model And Empirical Analysis Of Components Of Spread In Over The Counter Exchange Of India." Thesis, Indian Institute of Science, 2001. https://etd.iisc.ac.in/handle/2005/267.

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Анотація:
Over the Counter Exchange of India (OTCEI) was established in 1992 mainly to provide a platform for small and medium sized companies to raise money for their capital requirements. It is a well defined dealer market with market makers giving bid and ask quotes. It was established with state-of-the art technology with ringless, scripless trading. In this study, we develop a theoretical model to decompose spread into its three components in a dealer market. This model is further empirically examined by using OTCEI data. We find that Inventory holding cost to be the highest on OTCEI followed by Adverse Information cost and Order Processing cost. The result reflects market microstructure which is peculiar to OTCEI. The methodology developed in this study is basically a generalization of S toll's (1989) methodology. . Roll(1984) shows that in a pure order processing world, spread equals the square root of negative of serial covariances of successive differences of transaction prices. Stoll (1989) relates spread to the covariance of successive difference of transaction prices and that of the quotes. Stoll introduces two parameters, 5, which is a measure of magnitude of price change and JI, the probability of reversal of type of transaction, that is, from Bid to Ask or vice-versa, to model the Bid/Ask price movements from one transaction to the next. Thus Stoll, from this model, establishes a theoretical relationship between serial covariances of successive differences of transaction and quote returns and spread. 5 and n are estimated via regression of serial covariances of transaction and quote, returns on average proportional spread square. With these two parameters, Stoll finally decomposes spread into three components. δ, is the amount of price change between transactions for two reasons- Inventory holding reason and adverse information reason. Stoll explains these price changes due to two reasons with just one parameter, 5. This forms the main motivation of this study. In our study, we let 8 assume two different values, 5i and 82 which attempts to capture the price changes due to the two different causes viz inventory holding and adverse information. It is convenient to think of these two S's being associated with two different states of transactions. However, these states themselves are indeterminate . In other words, the price change could be due to inventory reasons, or due to trading with an informed trader, or due to both. Thus, while Stoll assumes only one 8, in our study, we have two different values of 8. Thus, with three parameters, 81, 82 and n, this study attempts to estimate the relevant parameters and realistically decompose the three components of spread in a dealer market. Just like Stoll, the developed theoretical model also relates serial covariances of transaction price changes and quoted price changes to spread square. However, unlike Stoll, now there are 3 parameters, namely, 5j, 82 and n. As it is impossible to solve three unknowns with just two equations, it becomes necessary to introduce one more equation relating the three parameters to the spread. It is here that we introduce, for the first time, the serial covariance of the second order differences of the transaction price changes, which is related to spread via an equation. Intuitively, we can explain this relationship using Roll's result. Roll(1984) has shown that spread equals square root of the negative serial covariances of transaction price changes in a pure order processing world. Since the second order difference is nothing but the rate of price changes, it also must be related to spread, since the price change themselves are related to it, empirically, we find that spread square significantly affects the serial covariance of second order difference of price changes as well. Besides explaining the price changes with just one 5, Stoll's method of decomposition is not realistic. Though his method of decomposition does yield three components of spread, in reality, it lumps Adverse information cost and Inventory holding cost together. In our study, we make use of the state-of-the art Huang and Stoll's (1997) methodology of decomposition of spread. We first embed the developed theoretical price-movement model into that of Huang and S toll's this yields a functional relationship between 5i and 52 and a and |3 of Huang and Stoll, which directly refers to the adverse information and inventory holding components respectively. Thus, in our study, we realistically decompose the components of spread and OTCEI and empirically too, we find that the components estimated from our methodology does reflect the market microstructure of OTCEI. Apart from developing and empirically testing the theoretical model, we also see if it fits the observed data on OTCEI. We find that the theoretical model does not exactly conform to the observed data in OTCEI, necessitating some empirical fine-tuning. We build an empirical model which is again used to get the three components of spread. We also estimate components of spread in OTCEI using Stoll's and Huang and Stoll's methodology and we compare them with the estimates obtained using our methodology. We find that Stoll's methodology overstates the Adverse information component of spread and understates the inventory holding component of spread and Huang and Stoll's methodology and Our methodology and model yields estimates of components of spread which is more in tune with the market micros tructure of OTCEI. The estimates obtained from empirical model too conforms to the market microstructure of OTCEI.
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6

Rao, Jyothi G. "A Theoretical Model And Empirical Analysis Of Components Of Spread In Over The Counter Exchange Of India." Thesis, Indian Institute of Science, 2001. http://hdl.handle.net/2005/267.

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Over the Counter Exchange of India (OTCEI) was established in 1992 mainly to provide a platform for small and medium sized companies to raise money for their capital requirements. It is a well defined dealer market with market makers giving bid and ask quotes. It was established with state-of-the art technology with ringless, scripless trading. In this study, we develop a theoretical model to decompose spread into its three components in a dealer market. This model is further empirically examined by using OTCEI data. We find that Inventory holding cost to be the highest on OTCEI followed by Adverse Information cost and Order Processing cost. The result reflects market microstructure which is peculiar to OTCEI. The methodology developed in this study is basically a generalization of S toll's (1989) methodology. . Roll(1984) shows that in a pure order processing world, spread equals the square root of negative of serial covariances of successive differences of transaction prices. Stoll (1989) relates spread to the covariance of successive difference of transaction prices and that of the quotes. Stoll introduces two parameters, 5, which is a measure of magnitude of price change and JI, the probability of reversal of type of transaction, that is, from Bid to Ask or vice-versa, to model the Bid/Ask price movements from one transaction to the next. Thus Stoll, from this model, establishes a theoretical relationship between serial covariances of successive differences of transaction and quote returns and spread. 5 and n are estimated via regression of serial covariances of transaction and quote, returns on average proportional spread square. With these two parameters, Stoll finally decomposes spread into three components. δ, is the amount of price change between transactions for two reasons- Inventory holding reason and adverse information reason. Stoll explains these price changes due to two reasons with just one parameter, 5. This forms the main motivation of this study. In our study, we let 8 assume two different values, 5i and 82 which attempts to capture the price changes due to the two different causes viz inventory holding and adverse information. It is convenient to think of these two S's being associated with two different states of transactions. However, these states themselves are indeterminate . In other words, the price change could be due to inventory reasons, or due to trading with an informed trader, or due to both. Thus, while Stoll assumes only one 8, in our study, we have two different values of 8. Thus, with three parameters, 81, 82 and n, this study attempts to estimate the relevant parameters and realistically decompose the three components of spread in a dealer market. Just like Stoll, the developed theoretical model also relates serial covariances of transaction price changes and quoted price changes to spread square. However, unlike Stoll, now there are 3 parameters, namely, 5j, 82 and n. As it is impossible to solve three unknowns with just two equations, it becomes necessary to introduce one more equation relating the three parameters to the spread. It is here that we introduce, for the first time, the serial covariance of the second order differences of the transaction price changes, which is related to spread via an equation. Intuitively, we can explain this relationship using Roll's result. Roll(1984) has shown that spread equals square root of the negative serial covariances of transaction price changes in a pure order processing world. Since the second order difference is nothing but the rate of price changes, it also must be related to spread, since the price change themselves are related to it, empirically, we find that spread square significantly affects the serial covariance of second order difference of price changes as well. Besides explaining the price changes with just one 5, Stoll's method of decomposition is not realistic. Though his method of decomposition does yield three components of spread, in reality, it lumps Adverse information cost and Inventory holding cost together. In our study, we make use of the state-of-the art Huang and Stoll's (1997) methodology of decomposition of spread. We first embed the developed theoretical price-movement model into that of Huang and S toll's this yields a functional relationship between 5i and 52 and a and |3 of Huang and Stoll, which directly refers to the adverse information and inventory holding components respectively. Thus, in our study, we realistically decompose the components of spread and OTCEI and empirically too, we find that the components estimated from our methodology does reflect the market microstructure of OTCEI. Apart from developing and empirically testing the theoretical model, we also see if it fits the observed data on OTCEI. We find that the theoretical model does not exactly conform to the observed data in OTCEI, necessitating some empirical fine-tuning. We build an empirical model which is again used to get the three components of spread. We also estimate components of spread in OTCEI using Stoll's and Huang and Stoll's methodology and we compare them with the estimates obtained using our methodology. We find that Stoll's methodology overstates the Adverse information component of spread and understates the inventory holding component of spread and Huang and Stoll's methodology and Our methodology and model yields estimates of components of spread which is more in tune with the market micros tructure of OTCEI. The estimates obtained from empirical model too conforms to the market microstructure of OTCEI.
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7

Mathew, David G. "On The Impact Of Fundamental Variables In The Determination Of Stock Returns In India." Thesis, 1997. https://etd.iisc.ac.in/handle/2005/1826.

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Mathew, David G. "On The Impact Of Fundamental Variables In The Determination Of Stock Returns In India." Thesis, 1997. http://etd.iisc.ernet.in/handle/2005/1826.

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9

Harshita. "Stock market anomalies : an empirical study in Indian context." Thesis, 2018. http://eprint.iitd.ac.in:80//handle/2074/7933.

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Jothimani, Dhanya. "Portfolio optimization in Indian market : a study using financial analytics." Thesis, 2017. http://localhost:8080/iit/handle/2074/7517.

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Книги з теми "Stock market- India"

1

Bal, Krishan. Industrial securities market in India. New Delhi, India: Commonwealth Publishers, 1989.

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Gupta, Saloni. Stock market in India: Working and reforms. New Delhi: New Century Publications, 2010.

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Alak, Ghosh, and Indian Economic Association, eds. Emerging money markets in India. New Delhi: Deep & Deep Publications, 2001.

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Kanuk, Alan R. Capital markets of India: An investor's guide. Hoboken, N.J: John Wiley & Sons, Inc., 2007.

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Biswal, Pratap Chandra. On stock market development, banks, and economic growth in India. Bangalore: Institute for Social and Economic Change, 2000.

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Biswal, Pratap Chandra. Stock market development in India: Is there any trend break? Bangalore: Institute for Social and Economic Change, 2000.

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7

Gokhale Institute of Politics and Economics, ed. Evolution of the capital markets and their regulations in India. Pune: Gokhale Institute of Politics and Economics, 2009.

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Functional instability or paradigm shift?: A characteristic study of Indian stock market in the first decade of the new millennium. New Delhi: Springer, 2012.

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9

National Conference on Forecasting Financial Markets in India (2008 Kharagpur, India) and National Conference on Forecasting Financial Markets in India (2008 Vinod Gupta School of Management). Forecasting financial markets in India. New Delhi: Allied Publishers, 2009.

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10

Hiremath, Gourishankar S. Indian Stock Market. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1590-5.

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Частини книг з теми "Stock market- India"

1

Dhankar, Raj S. "Stock Market Overreaction." In India Studies in Business and Economics, 63–76. New Delhi: Springer India, 2019. http://dx.doi.org/10.1007/978-81-322-3950-5_4.

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Dhankar, Raj S. "Market Efficiency and Stock Market." In India Studies in Business and Economics, 131–51. New Delhi: Springer India, 2019. http://dx.doi.org/10.1007/978-81-322-3950-5_8.

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Chattopadhyay, Sadhan Kumar. "Dynamics of the Indian Stock Market." In India Studies in Business and Economics, 421–48. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1650-6_25.

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4

Vanipriya, C. H., and K. Thammi Reddy. "Indian Stock Market Predictor System." In ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol II, 17–26. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03095-1_3.

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5

Barodawala, Rubina, and Diksha Ranawat. "Fundamental Drivers of Indian Stock Market." In Current Issues in the Economy and Finance of India, 69–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99555-7_5.

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6

Paul, Moumita, and Kalluru Siva Reddy. "Impact of US UMP on Indian Stock Market." In India Studies in Business and Economics, 647–62. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7062-6_33.

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7

Chakraborty, Kuntal. "An empirical exploration of the Indian stock market." In Neoliberalism in the Emerging Economy of India, 103–10. 1 Edition. | New York : Routledge, 2021. | Series: Routledge studies in the modern world economy: Routledge, 2021. http://dx.doi.org/10.4324/9781003131762-8.

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Chakrabarti, Gagari. "Regime Switching Dynamic Currency Exposure of Indian Stock Market." In India Studies in Business and Economics, 229–51. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7668-0_12.

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Dhankar, Raj S. "Indian Stock Market and Relevance of Capital Asset Pricing Models." In India Studies in Business and Economics, 19–37. New Delhi: Springer India, 2019. http://dx.doi.org/10.1007/978-81-322-3950-5_2.

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Chakraborty, Indrani. "Stock Returns and Real Economic Activities: Is There a Connection in India?" In Exploring What Drives Indian Stock Market During Covid-19, 99–113. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8001-5_6.

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Тези доповідей конференцій з теми "Stock market- India"

1

Naik, Suchismita. "A Narrative Data Visualization Of The Indian Stock Market." In IHCI '16: India HCI 2016. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/3014362.3014382.

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2

Agarwal, Udit, and A. Sai Sabitha. "Time series forecasting of stock market index." In 2016 1st India International Conference on Information Processing (IICIP). IEEE, 2016. http://dx.doi.org/10.1109/iicip.2016.7975381.

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3

Dias, Rui, Paula Heliodoro, Paulo Alexandre, and Cristina Vasco. "THE SHOCKS BETWEEN OIL MARKET TO THE BRIC STOCK MARKETS: A GENERALIZED VAR APPROACH." In 4th International Scientific Conference – EMAN 2020 – Economics and Management: How to Cope With Disrupted Times. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/eman.2020.25.

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The pandemic (Covid-19) has affected the global economy, and the impact on financial markets seems inevitable. In view of these events, this essay aims to analyse the shocks between the stock market indices of Brazil (BOVESPA), China (SSEC) India (SENSEX), Russia (IMOEX) and oil (WTC), in the period from January 2, 2019 to May 29, 2020. In order to carry out this analysis, different approaches were undertaken with a view to gauging whether (i) the global pandemic has accentuated the shocks between the BRIC financial markets and the WTC? The daily yields do not have normal distributions, show negative asymmetries, leptokurtic, and exhibit conditional heteroscedasticity. In general, we find evidence that the WTC causes the markets of Russia and India, China does not cause any market, and Brazil is not caused by any market analysed. On the other hand, short-term market shocks are relevant and create some arbitrage opportunities. However, our study did not analyse anomalous returns in these financial markets. These findings also open space for market regulators to take action to ensure better information between international financial markets.
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4

Sidhu, Priya, Himanshu Aggarwal, and Madan Lal. "Stock Market Prediction using LSTM." In Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India. EAI, 2021. http://dx.doi.org/10.4108/eai.27-2-2020.2303545.

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5

Silva, Natacha, Maria José Palma Lampreia Dos Santos, and Nuno Baptista. "The impact of COVID-19 pandemic on South Asian Stock Markets." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003902.

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The main aim of this paper is to analyze the impact of the pandemic COVID-19 on the efficiency of capital markets in countries of South Asia, namely, the market efficiency of these stock markets in the pre and post-COVID-19 global wave. The methods include quantitative research and time series analysis. Information and data were collected from the stock indices of Pakistan (KSE), India (BSE), Bangladesh (DSE) and Sri Lanka (CSE) for the period from August 2018 to July 2021. The results confirm that all capital markets are efficient before the global outbreak. In a meanwhile, after the pandemic (COVID-19) all the financial markets present a low efficiency. Explain more in economic terms. This conclusion helps the regulators of markets and investors to take a step to make certain information in these economies, subsequently, returns of some stocks can be predictable and generate opportunities for abnormal earnings and arbitrage.
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6

T, Praveen Kumar, Mallieswari R, and Kirupa Priyadarsini M. "Predicting Stock Market Price Movement Using Machine Learning Technique: Evidence from India." In 2022 Interdisciplinary Research in Technology and Management (IRTM). IEEE, 2022. http://dx.doi.org/10.1109/irtm54583.2022.9791640.

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7

Dias, Rui, Paula Heliodoro, Paulo Alexandre, and Maria Manuel. "EVIDENCE OF INTRADAY MULTIFRACTALITY IN BRIC STOCK MARKETS: AN ECONOPHYSICS APPROACH." In Fourth International Scientific Conference ITEMA Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/itema.s.p.2020.57.

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The pandemic outbreak (Covid-19) has affected the global economy, and the impact on financial markets seems inevitable. In view of these events, this essay intends to analyse the efficiency, in its weak form, in the BRIC markets, namely the stock indexes of Brazil (BRAZIL IBOVESPA), China (Shanghai Stock Exchange), India (S&P BSE SENSEX), Russia (MOEX Russia). The data are intraday (1 hour), from May 2019 to May 2020; to obtain more robust results, we divided the sample into time scales up to 5 days (Period I), and above 10 days (Period II), in a complementary way, and we use the opening and closing prices to estimate the adjustment time of each market. The results indicate that the BRIC markets have significant persistence (over 10 days), which may jeopardize market efficiency, in its weak form. On the other hand, the low initial correlation in certain stock indexes may create some arbitrage opportunities. However, our study did not analyse anomalous meturns in these financial markets. These conclusions also open space for market regulators to take measures to ensure better information between these markets and international ones.
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8

Verma, Rajit, Kiran Sood, and Shivani Inder. "An Event Study Analysis on Stock Market Reaction amid Geo-Political Crisis in India." In 2022 International Conference on Emerging Smart Computing and Informatics (ESCI). IEEE, 2022. http://dx.doi.org/10.1109/esci53509.2022.9758374.

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9

Sapkota, Amosh, Anand Kumar, and Anjali Mathur. "Intelligent System for the Detection of Insider Trading in Indian Stock Market." In Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India. EAI, 2021. http://dx.doi.org/10.4108/eai.7-12-2021.2314574.

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10

Hsueh, Hsin-Pei, and Fangjhy Li. "Wavelet Analysis on the Relevance of Stock Market and Exchange Rate between China and India." In the 2nd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3366650.3366673.

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Звіти організацій з теми "Stock market- India"

1

Campbell, John, Tarun Ramadorai, and Benjamin Ranish. Do the Rich Get Richer in the Stock Market? Evidence from India. Cambridge, MA: National Bureau of Economic Research, August 2018. http://dx.doi.org/10.3386/w24898.

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Trembeczki, Zsolt. Japanese FDI in India Part II : Drivers and Obstacles from the Viewpoint of Japanese Investors. Külügyi és Külgazdasági Intézet, 2022. http://dx.doi.org/10.47683/kkielemzesek.ke-2022.69.

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This policy brief is part of a two-part series analysing the history and current situation of Japanese foreign direct investment (FDI), and its potential role in India’s economy. The previous part found that while Japan has become a major investor in India over the recent decades, top-level political relations in the past had limited impact on India’s actual ability to attract Japanese foreign direct investment. This policy brief examines the factors that determine Japanese companies’ willingness to establish or increase their presence in India. It finds that India’s dynamically growing market, relatively cheap talent pool, infrastructure ‘spending spree’, and recent policies promoting the industry are highly attractive to Japanese companies. That being said, Japanese investors are deeply concerned about India’s poor infrastructure and still relatively restrictive regulatory environment. For these reasons, the realisation of the 2022 March announcement by Japanese Prime Minister Kishida, which would add an up to 136% increase in Japanese FDI stock in India, would first and foremost depend on India’s own ability to implement reforms and improve its infrastructure, rather than on the political will of top Indian and Japanese leaders.
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3

Das, Jishnu, Joanna Härmä, Lant Pritchett, and Jason Silberstein. Forum: Why and How the Public vs. Private Schooling Debate Needs to Change. Research on Improving Systems of Education (RISE), March 2023. http://dx.doi.org/10.35489/bsg-rise-misc_2023/12.

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“Are private schools better than public schools?” This ubiquitous debate in low- and middle-income countries is the wrong one to have. The foreword and three essays collected in this Forum each explore how to move past the stuck “public vs. private” binary. Jason Silberstein is a Research Fellow at RISE. His foreword is titled “A Shift in Perspective: Zooming Out from School Type and Bringing Neighborhood Education Systems into Focus.” It summarizes the current state of the “public vs. private” debate, outlines an alternative approach focused on neighborhood education systems, and then synthesizes key findings from the other essays. Jishnu Das has conducted decades of research on school systems in low-income countries, including in Zambia, India, and Pakistan. His essay is titled “The Emergence and Consequence of Schooling Markets.” It describes exactly what schooling markets look like in Pakistan, including the incredible variance in school quality in both public and private schools within the same village. Das then reviews the evidence on how to engineer local education markets to improve learning in all schools, including polices that have underdelivered (e.g., vouchers) and more promising policies (e.g., finance and information structured to take advantage of inter-school competition, and a focus on the lowest performing public schools). Das’ research on Pakistan is available through leaps.hks.harvard.edu, which also houses the data and documentation for the project. Lant Pritchett writes from a global lens grounded in his work on systems thinking in education. His essay is titled “Schooling Ain’t Just Learning: Controlling the Means of Producing Citizens.” It observes that governments supply, and families demand, education for many reasons. The academic emphasis on one of these reasons, producing student learning, has underweighted the critical importance of other features of education, in particular the socialization function of schooling, which more persuasively explain patterns of provision of both public school and different kinds of private schools. With this key fact in mind, Pritchett argues that there is a strong liberty case for allowing private schools, but that calls for governments to fund them are either uncompelling or “aggressively missing the point”. Joanna Härmä has done mixed-methods research on private schools across many cities and rural areas in sub-Saharan Africa and India, and has also founded a heavily-subsidized private school in Uttar Pradesh, India. Her essay responds to both Das and Pritchett and is titled “Why We Need to Stop Worrying About People’s Coping Mechanism for the ‘Global Learning Crisis’—Their Preference for Low-Fee Private Schools”. It outlines the different forces behind the rise of low-fee private schools and asserts that both the international development sector and governments have failed to usefully respond. Policy toward these private schools is sometimes overzealous, as seen in regulatory regimes that in practice are mostly used to extract bribes, and at other times overly solicitous, as seen in government subsidies that would usually be better spent improving the worst government schools. Perhaps, Härmä concludes, “we should leave well enough alone.”
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