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Information and Knowledge Management                                                         www.iiste.orgISSN 2224-5758 (...
Information and Knowledge Management                                                          www.iiste.orgISSN 2224-5758 ...
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2.[7 14]an impact of ict on the growth of capital market-empirical evidence from indian stock exchange

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2.[7 14]an impact of ict on the growth of capital market-empirical evidence from indian stock exchange

  1. 1. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011 An Impact of ICT on the Growth of Capital Market-Empirical Evidence from Indian Stock Exchange Amalendu Bhunia Reader in Commerce Fakir Chand College, Diamond Harbour South 24-Parganas-743331 West Bengal, India *E-mail: bhunia.amalendu@gmail.comAbstractThis paper examines the impact of ICT on the growth of the Indian Stock Exchange using a modifiedversion of the Gompertz technology diffusion model introduced by Chow (1983) and therefore rearrangesthe model such that ICT development becomes the independent variable while stock market growthindicators are the dependent variables. Capital markets have become excessively volatile since the adoptionof computer assisted trading strategies as the latter increase short-term price volatility and risks. Fama andFrench (1988) argued that information technology have made capital markets more efficient as attendantstock prices now reflect important information and investors’ perception of stocks more swiftly. The data inthe present study is obtained from BSE and NSE stock exchanges database, MCX India database,Securities and Exchange Commission and websites of World Development Indicators. In the courseof analysis, market capitalization model, stock market value traded model, stock market volume tradedmodel, turnover model, number of securities listed model, public sector bond model and private sector debtmodel has been designed. The results disclose that selected variables are significantly affected byinformation and communications technology especially in respect of increase in the number of stockbrokers,investors and access to ICT. Information Technology have contributed to growth of the Indian CapitalMarket, with the effect mostly seen in the availability of information to investors and the improvements inthe trading patterns of the Indian Stock Exchange.Keywords: Indian stock market, ICT, Gompertz model, macroeconomic variables1. IntroductionThe effect of information and communication technology (ICT) on the growth and development of capitalmarkets has been a subject of debate in recent times. A school of thought led by authors like Shiller (1989),Summers (1988), Porteba and Summers (1988) would argue that capital markets have become excessivelyvolatile since the adoption of computer assisted trading strategies as the latter increase short-term pricevolatility and risks. They also argue that very few investors have access to online trading systems. Fewactually own computers and have easy access to the Central Securities Clearing System. Many investor,they claimed, do not have access to a system that sends orders to stockbrokers for automated execution.They also contend that ICT driven capital market operations are fraught with fraud and manipulation,which mostly affect individual investors. A case in point relates to the sale of shares without authorizationof the stockholders, a practice that is given impetus by greed and dishonesty of some market participants.They further argued that surveillance problems and the lack of proper enforcement of penalties by the legalsystem make the adoption of a fast-paced ICT system dangerous to investors.The second school of thought, which includes authors Fama and French (1988), on the other hand, arguedthat information technology have made capital markets more efficient as attendant stock prices now reflectimportant information and investors perception of stocks more swiftly. In their contention, ICT has made7|Pagewww.iiste.org
  2. 2. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011the capital market more efficient by providing all participants with faster and more effective means ofexchanging information. They maintained that new products and instruments have been made readilyavailable as a result of the advent of sophisticated ICT. Evidently, capital markets can be more resilient,possess greater depth and breadth with the intervention of ICT.It must be observed that the premises of the above theorizing are capital markets in developed countries.Would their arguments hold true for the less Developed Countries (LDC)? Which school of thought wouldappropriately explain the experiences of the LDCs? Perhaps the critical questions that need to be addressedwould include: Has the adoption of information technology had a positive or negative impact on the IndianCapital Market? Has ICT transformed the way business is conducted on the Exchange? Has ICT benefitedthe Indian investor? The plethora of research questions can go on and on. However, this paper seeks toascertain how the adoption of information technology has impacted on stock market development indicatorsand the way business is conducted on the Indian Stock Exchange. A possible area of future research wouldrelate to the benefits of ICT adoption by the capital market to the Indian (individual) investor, which is notpresently covered in this paper.This paper adopts an internal influence model with the population of interest being participants in theIndian Stock Exchange. Samaddar et al (2002) studied internal influence models (Gompertz, logistic andexponential models) and found that the Gompertz model best characterized current and future ICTgrowth/diffusion. The aim of this paper is not to investigate the innovations but to ascertain the impact ofICT innovations on trends in the stock exchange development indicators.2. Review of LiteraturesThis section starts with conceptual clarifications of some important terms implicated in the topic. Suchterms include diffusion, information diffusion model, capital market peculiarities and information andcommunication technology. Rogers (1995, 2003) defines diffusion as a ‘process in which an innovation iscommunicated through certain channels over time among the members of a social system’. Simply,diffusion is the way a given information and technology innovation spreads amongst a given population.Traditionally, there are two widely used diffusion models – the internal influence model and the externalinfluence model. The former assumes that there is a given level of interaction among the subjects of thegiven population such that knowledge of the innovation is disseminated through the interaction channels tothe entire population. This model is represented by an S curve (Mahajan & Peterson, 1985) and it capturesthe slow beginning (low awareness), rapid expansion and the leveling off as it spreads throughout thepopulation. The external influence model presumes little or no interaction between members of thepopulation and therefore the transmission mechanism is exogenous to the given population.The current stock of finance and economics literature on the diffusion of ICT have focused on the impact ofstock market financing on ICT growth and development as well as the determinants of ICT development(Saint-Paul, 1992, Black & Gibson, 1998, Allen & Gale, 1999). This probably accounts for the dearth ofliterature on the impact of ICT diffusion on stock exchange development indicators. Several researchershave examined the benefits of adoption of ICT in developing as well as developed capital markets. Suchstudies agree that ICT makes capital markets more efficient for example Mahonney (1997) describes thesecurities markets as where information technology innovations often lead to changes in the way securitiestransactions are negotiated, executed, cleared and settled.In a study on stock market development in sub-Saharan Africa, Yartey and Adjani (2007) proposed that theadoption of a robust electronic trading system and a central depository system among others are keypreconditions for addressing the prevalent problem of liquidity as these stock exchanges seek regionalintegration.Lucas et al (2002) analyzed adoption of ICT in the New York Stock Exchange (NYSE) and concluded thatthe NYSE invested in ICT to create new resources for advantage and to enhance existing resources.According to the paper, ICT provides for efficient trade executions and adequate trading capacity, ensures ahigh quality securities market and reduces labour expenses and the demand for physical space. Levine(1991) proposed that stock market liquidity – ability to trade shares easily- which is facilitated by ICT play8|Pagewww.iiste.org
  3. 3. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011a key role in economic development.Clemons and Weber (1990) examined the 1986 Big Bang reforms of the London Stock Exchange andargued that the adoption of ICT and the exchange’s new screen based market were a strategic necessity.The available literature examined suggests that automation of stock exchanges reduce the costs andinefficiencies associated with share trading, increase trading activity and liquidity. Also adoption of ICTspeeds up operations and activities of the exchange and reduces costs associated with manual systems. ICTenables the exchanges extend trading days and hours as cumbersome processes are eliminated. It alsoeliminates the need for intermediation (stockbrokers) as investors can monitor markets and trade online.On the relationship between capital markets and ICT development in an economy, King and Levine (1993)contend that capital markets facilitate the diversification of ICT risks and therefore positive development ofstock markets enhances innovations in ICT. However, Singh et al (2000) investigated the relationshipbetween ICT and the capital market using multivariate regression analysis on cross sectional data from 63countries including both emerging and developed economies. They found that stock markets are neithernecessary nor sufficient conditions for promoting the development of ICT. The econometric analysis did notreveal any robust systematic relationship between stock market development indicators and ICTdevelopment indicators.Similarly, Yartey (2006) examined the role of financial development and financial structure in explainingcross country diffusion of ICT. The paper found that the structure of a country’s capital market does notappear to have any significant relationship with the level of ICT development. Financial developmenthowever was found to be an important determinant of ICT development and the paper therefore emphasizedthe need to develop financial markets in emerging economies. Previous researchers attempted to establishrelationships between ICT diffusion in an economy as facilitated by capital markets.This paper contributes to current literature by examining ICT diffusion in the Indian Stock Exchange with aview to ascertaining its impact on the stock market development indicators. The results obtained wouldanswer to a large extent the question of whether the increase experienced in the stock market developmentindicators can be attributed to the adoption of ICT.3. Methodology3.1 The modelThis paper tests the role of information and communication technology on the growth of the Indian StockExchange using a modified version of the Gompertz technology diffusion model introduced by Chow(1983). The Gompertz model assumes that over time technology usage tends to an equilibrium level alongan S-shaped path and it is given as:Log ηit - log ηit-1 = θi [log η*i - log ηit-1] 1a)Where:ηit is ICT use in country I in year tη*i is post diffusion equilibrium levelθi is the speed of adjustmentThe Gompertz model examines the relationship between ICT as the dependent variable and the factors thatimpact change in the level of ICT as the independent variables. There is need to adjust this model to fit it tothe data and objectives of this study. This paper examines the impact of ICT on the growth of the IndianSock Exchange and therefore rearranges the model such that ICT development becomes the independentvariable while stock market growth indicators are the dependent variables. Thus the adjusted model is givenas:log Xit - log Xit-1 = θi [log X*i - log Xit-1] (1b)Where: X represents the stock exchange growth variables and other variables are as previously defined. Theequilibrium level of change in growth in the Exchange (X*i ) can be taken as a function of change in ICT9|Pagewww.iiste.org
  4. 4. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011development indicators (Y) and thus express this as:logX*i=αi+βilogYit (2)Substituting and adding an error term, equation (1) can be expressed as:log Xit - log Xit-1 = θi αi + θi βi log Yit - θi log Xit-1+ εit (3)Considering that the expression for the dependent variable in equation (3) implies a change in that variable,the equation is thus simplified and expressed as:∆Xit = θi αi + θi βi log Yit - θi log Xit-1+ εit (4)3.2 Data and VariablesTable 1 shows summary statistics for the Stock Exchange development indicators. The minimum value of262 for market capitalization was recorded in 2001 while the maximum of 9468 was recorded in 2011showing an increase of more than 97%. Also the number of listed securities rose marginally from aminimum of 258 in 2001 to 301 in 2011. Similarly, the value traded, volume traded and turnover also rosesignificantly. Market capitalization had the highest variability in data with a standard deviation of 2927.6.The dependent variables to be tested for the impact of ICT are the Stock Exchange development indicatorsexamined earlier and they include: market capitalization (m), stock market value traded (v), stock marketvolume traded (λ), turnover (Ћ), number of securities listed (f), public sector bond (Þ) and private sectordebt (φ). The data in the present study is obtained from BSE and NSE stock exchanges database, MCXIndia database, Securities and Exchange Commission and websites of World DevelopmentIndicators. The independent variable is ICT development indicators in the Indian Stock Exchange. Fourmeasures are used: number of stockbrokers (δ), number of stockbrokers with functional websites (γ), totalnumber of internet users (ή), total number of mobile and telephone mainline users (ψ).Applying the model in equation (4) to our variables results in the following expressions:3.3 Market Capitalization (m) Model∆mit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log mit-1+ εit (5)Market capitalization is the value of all the listed shares that is number of shares multiplied by price ofshares. This is used as a measure of stock market size. Available statistics show that market capitalization asa percentage of GDP in India has been on the increase from 9.6% in 2001 to 19.8% in 2011. Economicliterature agrees that market capitalization is positively correlated to the amount of capital raised and theability for market participants to diversify risks. However, this paper presumes that the growth in marketcapitalization is positively correlated with ICT development in the Indian Stock Exchange.3.4 Stock Market Value Traded (v) Model∆vit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log vit-1+ εit (6)This measure represents the total shares traded on the stock exchange and it reflects the liquidity of themarket. Liquidity here is taken to be the ability of participants to buy and sell shares easily. Access tostock-brokers websites and telephones are presumed to be crucial trade facilitators here. Available datashows that value traded on the Indian Stock exchange rose from 13.57 in 2001 to over 1075.5 in 2011.Stock value traded is expected to be positively related to ICT development.3.5 Stock Market Volume Traded (λ) Model∆λit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log λit-1+ εit (7)The total volume traded refers to the number of shares exchanged in the course of trading. This valuecomplements value traded in measuring liquidity in the market. As stated in value traded, ease of trading isa crucial factor in determining the volume of daily trades and hence access to the stockbrokers eitherthrough their websites via the internet or by telephone plays a major role. Thus stock volume traded isexpected to be positively related to ICT development.3.6 Turnover (Ћ) Model10 | P a g ewww.iiste.org
  5. 5. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011∆Ћit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log Ћit-1+ εit (8)The turnover ratio refers to the value of total shares traded divided by market capitalization. This is also ameasure of liquidity and it explains the rate at which shares are exchanged. A high turnover ratio implieslow transaction costs and vice versa. The data shows that turnover varied from 0.05 in 2001 to 0.11 in 2011.Turnover is expected to be positively related to ICT development.3.7 Number of Securities Listed (f) Model∆fit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log fit-1+ εit (9)The number of firms listed is another measure of market size. Statistics show that there has been minimalvariation in the number of listed securities between 2001 and 2011 suggesting a limited market. Equation 9seeks to explain the variability in terms of ICT development and presumes that increase in ICT diffusion,which translates to increased awareness and investor confidence would lead to an increase in the number oflisted shares.3.8 Public Sector Bond (Þ) Model∆Þit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log Þit-1+ εit (10)This study includes trading in public sector bonds to capture the extent of government participation in themarket. This is regressed on ICT development indicators to ascertain if the adoption of ICT has contributedto the increase in the value of bonds traded on the exchange. The bond market in India is small and notactively traded like the equities market. ICT indicators are not expected to affect government bondssignificantly.3.9 Private Sector Bond (φ) Model∆φit = θi αi + θi βi log δit + θi βi log γit+ θi βi log ήit+ θi βi log ψit - θi log φit-1+ εit (11)This measure is also examined to ascertain the effect of ICT development on private sector debt in the stockexchange. The private sector debt market in India is similar to the government bond market in that it issmall and not actively traded like the equities market. ICT indicators are not expected to affect privatesector bonds significantly.4. Empirical Results and AnalysisThis study estimates the modified Gompertz ICT diffusion equation using data for the period 2001 toMarch 2011. The explanatory variables are simultaneously regressed with the dependent variables includinga lagged parameter of the dependent variable. This section presents the results of the empirical analysis onthe basis of available data for the period 2001 to March 2011. To test the fitness of the model, six equationswere estimated using the same explanatory ICT variables for each stock market growth indicator. This isbased on the assumption that the same ICT variables are likely to impact on all the stock marketdevelopment indicators. The results of applying the adjusted Gompertz model to the relationship betweenthe Stock Exchange growth indicators and the measures of ICT adoption are reported in Table 2.Using market capitalization as the dependent variable, the results show that the model captures thediffusion process with an R2 of 0.925. The number of dealers is positively correlated with marketcapitalization and is significant at 10%. Specifically, a percentage point increase in the number of dealers’increases market capitalization by 7.04 percentage points. Access to internet and telephone mainlines areinsignificant while access to mobile phones have a significant although negative relationship with marketcapitalization. Dealers with websites also showed a significant but negative relationship.Value traded represents growth in stock market activity and the model shows an R2 of 0.738 although thelagged dependent value is positive and significant at 0.87 implying that the model is suitable for thisrelationship. The results show that only access to telephone mainlines is significantly and positivelycorrelated to the value of shares traded on the Indian Stock Exchange. The number of dealers, access tointernet, mobile phones and dealers’ websites are all statistically insignificant. The volume traded refers tothe number of shares exchanged during trades. The number of dealers is significant at 2.5% and thisdemonstrates a strong positive correlation. Specifically, a percentage point increase in the number of11 | P a g ewww.iiste.org
  6. 6. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011stock-brokers increases volume of shares traded by 29.6 percentage points. Similarly, access to mobilephones is significant at 10% showing an increase of 0.2 in volume traded per percentage point increase inthe number of mobile phone users. Internet access, telephone mainlines and access to stockbrokers websitesare statistically but negatively correlated with volume traded. The number of listed securities fluctuatedmarginally within the period under review. The results show that the adoption of technology might not haveimpacted on the number of listed shares as the maximum of 301 is not far from the minimum of 258. Thenumber of stockbrokers as well as access to mobile phones are significant at 10% while access to internet,telephone mainlines and stockbrokers are significant but in a negative manner. The model is appropriatewith an R2 of 0.92.Analysis of the relationship between federal and state government bonds and ICT reveal that the number ofstockbrokers is insignificant although with a high coefficient of 55.5 while internet and mobile phoneaccess are insignificant. Telephone mainlines and access to stock-brokers websites is significant althoughnegatively with public bonds. Private debt stock increased from 3.1 in 2001 to 11.1 in 2009 but reduced to3.3 in 2011. Application of the model reveals that the number of stockbrokers was significant at 1% with acoefficient of 38.25 and t value of 5.71. Similarly, access to telephone mainlines and mobile phones weresignificant at 5% and 1% respectively while internet access and use of stock-brokers websites werenegatively significant. R2 recorded a value of 0.9957.Turnover as used in this study refers to the relationship between the value of shares traded and the marketcapitalization and is used as a measure of liquidity. The relationship between turnover on the one hand andnumber of stockbrokers, internet access, and access to stock-brokers websites on the other is statisticallyinsignificant while access to mobile telephone is significant at 1%, implying the considerable influence ofinformation technology on capital market development in Indian..5. ConclusionThis study utilized a modified Gompertz model of technology diffusion to examine the impact ofinformation and communication technology on the growth of the Indian Capital Market. The results revealthe following important findings: Growth in market capitalization is affected by the level of interactionbetween stockbrokers and investors brought about by ICT in the form of internet access, telephone(mainlines and mobile) as well as access to the websites of stockbrokers. Growth in the total value of sharestraded is significantly affected by communication technology (telephones).Growth in the volume of shares traded arises from the interaction between stockbrokers and investorsmainly via mobile telephony. The number of securities listed on the Stock Exchange does not appear tohave any significant relationship with the adoption of information and communication technology.Similarly, growth in federal and state government bonds has not been significantly affected by informationand communications technology. Private debt stock appears to have been significantly affected byinformation and communications technology especially the increase in the number of stockbrokers andaccess to telephone lines. Lastly, turnover in the market seem to be affected significantly and positively byaccess to mobile phone technology. Information Technology has contributed to growth in the Indian CapitalMarket. The effect is mostly seen in the availability of information to investors and the improvements in thetrading patterns of the Exchange. The results call for further advances in information technology that couldhelp to broaden and deepen the market thus improving its effectiveness and efficiency.In spite of the phenomenal growth recorded in the Indian Capital Market as reflected in aggregates such asmarket capitalization and value of transactions, the market is still relatively thin compared to other moredeveloped markets. This reveals that there is great potential for further growth. First, the continuedexpansion of the internet creates opportunities for innovation in financial services, thus the regulators of theIndian Capital Market should seek to expand and deepen the market by introducing new products such asderivatives like option and futures trading. In addition, online trading by investors directly through theinternet or mobile phones should be explored rather than the present system of passing all trades throughstockbrokers creating unnecessary delays and inappropriate pricing of securities.12 | P a g ewww.iiste.org
  7. 7. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011ReferencesCBN (2006), “Annual Report and Statement of Account”, December 2006, Abuja: CBN Press.Clemons, E.K, & Weber, B.W (1990), “London’s Big Bang: A Case Study of Information Technology.Competitive Impact and Organizational Change”, Journal of Management Information Systems, 6(4), pp.41-60.Fama, E. (1991), “Efficient Capital Markets 11”, Journal of Finance, 575-1617.Fama, E., & French, K. (1988), “Dividend Yields and Expected Stock Returns”, Journal of FinancialEconomics, 22: 3-25.Lucas , H.C., Oh W., Simon, G., & Weber, B. (2002), “Information Technology and the New York StockExchange’s Strategic Resources from 1982 -1999”, Access from Google Search Engine atwww.rhsmith.umd.edu/cemeLevine, R. (1991), “Stock Markets. Growth and Tax Policy”, Journal of Finance, XLVI, 1445-1465.Mahajan, V., & Peterson ,R.A. (1995), “Models for Innovation Diffusion. Newbury Park CA: SagePublications”, International Journal of Business and Economics Perspectives, Volume 4, Number 1. 2009,p.15.Ndanusi A.M. (2003), “Country Experience with Capital Market Development: The Nigerian Experience”,A paper presented at the Fifty Annual Financial Markets and Development Conference April 2003,Washington D.C.Porteba J., & Summers, L. (1988), “Mean Reversion in Stock Prices: Evidence & Implications”, Journal ofFinancial Economics, 22, pp. 27-59.Rogers, E.M. (2003), “Diffusion of Innovations 5th ed”, New York: Free Press.Samaddar S., Nargundkar, S., & Chatterjee, S. (2002), “E-Market Infrastructure Planning and InternetGrowth”, Eight American Conference on Information Systems in SPECS, 721-728.Securities and Exchange Commission. (2008), “Securities and Exchange Commission databank”, Accessfrom Google Search Engine at http://www.databank.sec.gov.ngSecurities and Exchange Commission. (1991), “Automation and the Nigerian Capital Market”, Issues inCapital Market Development, Securities Market Journal., 1, pp. 73-77.Securities and Exchange Commission. (2005), “The Impact of Electronic Technology on the SecuritiesMarket in Nigeria”, Issues in Capital Market Development. Securities Market Journal, 4, 94-99.Shiller, R. (1989), “Market Volatility”, Journal of Finance , 42, pp. 623 – 655.Singh A., Singh, A., & Weisse, B. (2000), “Information Technology, Venture Capital and the Stock Market.”,A paper prepared as a background paper for the International Labor Organization’s World EmploymentReport 2000-2001.Summers, L. (1988), “Does the Stock Market rationally reflect fundamental values?”, Journal of Finance.,41, pp. 591-601.Wallman, S.M.H. (1998), “Information Technology and the Securities Market”, The Brookings Review,16(1), pp. 26-29.Yartey, C. A. (2006), “Financial Development the Structure of Capital Markets and the Global DigitalDivide”, IMF working paper wp/06/258.16 International Journal of Business and Economics PerspectivesVolume 4. Number 1. 2009Yartey, C. A., & Adjani, C. K. (2007), “Stock Market Development in Sub-Saharan Africa: Critical Issuesand Challenges”, IMF Working Paper Series WP/07/209.Corresponding Author: Dr. Bhunia has experience in teaching accounting, finance, taxation andmanagement courses for 12 years. His areas of academic interest are accounting, taxation and finance inwhich he has published 36 research articles (International-22 and National-14) in peer reviewed journals of13 | P a g ewww.iiste.org
  8. 8. Information and Knowledge Management www.iiste.orgISSN 2224-5758 (Paper) ISSN 2224-896X (Online)Vol 1, No.2, 2011national and international repute. He has completed two research project financially supported theUniversity Grant Commission, India. He has guided M. Phil dissertation paper and Ph.D. thesis undervarious universities in India. Dr. Bhunia is Editor, Associate Editor, Technical Editor, editorial boardmember of 15 International Journals and also active reviewer of various international journals. Table 1: Descriptive Statistics on Indian Exchange growth indicators Market Listed Value Volume Turnover Private Public Capitalizatio Securities traded traded debt bonds nMean 2341.82 272.60 232.91 19.71 0.08 5.38 249.89Maximum 9467.89 301.02 1075.5 76.74 0.11 11.1 1013.0Minimum 262.61 258.01 13.57 3.14 0.047 3.10 2.10Std. Dev 2927.62 14.40 329.74 22.91 0.02 2.82 388.45Observations 2 2 2 2 2 2 2 Table-2: Results of the adjusted Gompertz model showing the relationship between the Stock Exchange growth indicators and the measures of ICT adoption No. of Internet Telephone Mobile phone Dealers with R2 dealers users mainlines lines websitesMarket 7.0406 0.0380 -0.5139 -0.1412 -6.9099 0.925capitalizatio (0.92)*** (0.13) (-0.38) (-1.02)*** (-0.94)***nValue -5.4209 -0.0684 2.1103 0.3509 5.1203 0.738traded (-0.17) (-0.07) (1.05)*** (0.49) (0.17)Volume 29.5669 -0.3495 -0.8457 0.2034 -31.2912 0.981traded (2.126)* (-0.99)*** (-1.06)*** (1.33)*** (-2.17)*Listed 1.7793 -0.0395 -0.1577 0.0399 -1.901 0.919securities (1.097)*** (-0.61) (-1.38)*** (1.38)*** (-1.157)***Public 55.5293 -1.2366 -5.2039 0.1299 -60.1275 0.826bonds (0.84) (-0.60) (-1.167)*** (0.15) (-0.87)Private debt 38.2513 -1.1129 1.0156 0.4100 -41.5663 0.996 (5.71)* (-3.73)* (1.81)** (3.23)* (-6.18)*Turnover 0.1830 -0.1258 -1.1303 0.5113 -1.1834 0.947 (0.03) (-0.45) (-1.50)** (2.48)* (-0.17)14 | P a g ewww.iiste.org

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