EVALUATING THE NEXUS BETWEEN FINANCIAL DEEPENING AND STOCK MARKET IN NIGERIA

July edition EVALUATING THE NEXUS BETWEEN FINANCIAL DEEPENING AND STOCK MARKET IN NIGERIA Okoli 0 Margaret Nnenna 0 0 Department of Financial Management, Federal University of Technology , Owerri , Nigeria The paper examines the relationship between financial deepening and stock market returns and volatility in the Nigerian stock market. Estimation depending on the measures of financial deepening and market returns were evaluated using GARCH (1, 1) model. Four modeled equations were estimated and analysed. Financial deepening is represented by two variables, the ratio of the value of stock traded to GDP (FD1t) and the ratio of market capitalization to GDP (FD2t). Empirical results revealed that financial deepening (FD1t) measured as the ratio of value of stock traded to GDP do not affect the stock market and there is no news about volatility. But financial deepening (FD2t) measured as the ratio of market capitalization to GDP affect the stock market. It indicated that financial deepening reduces the level of risk (volatility) in the stock market. Result also recorded that the conditional volatility of returns is slightly persistent. Policy implications emanating from the study is that efforts should be made to improve financial development in the country by increasing the range of financial assets. Deepening finance intermediation may promote economic growth by mobilizing more investments, and lifting returns to financial resources, which raises productivity. Increased investors confidence and less risk perception by them, will invariably further boost the market and ginger growth. Financial Deepening; Stock Market Returns; GARCH Model - importance of volatility in financial theory, it becomes very essential to understand the behavior and nature of stock market volatility. Knowledge of the causes and degree of stock market volatility is beneficial to policy makers and investors and economic forecasters in predicting the direction of the economys growth. This study therefore derives its objective from exploring the effects of financial deepening in stock market returns and volatility in Nigeria using stockmarket based data. The commonly used measures of financial deepening include ratio of money supply to GPD, ratio of domestic credit to GDP, the size of non-bank institutions to the financial system, degree of monetization, the size of currency outside the bank etc (Oloyede.1998), ratio money supply to GDP and ratio of domestic credit to GDP Nwezeaku et al (2010). The point of departure of this study is the use of stock market based variables like the ratio of the value of stock traded to GDP, ratio of market capitalization to GDP. t2 o 1ut21 t21 FD1t(1) ; t 1, 2,..., 30 Rt = stock market return Rt -1 = the lagged value of return t2 = conditional variance FD1t = financial deepening measured as ratio of value of stock traded to GDP t2 o 1ut21 t21 FD2t ; t 1, 2,..., 30 FD2t = financial deepening measured as the ratio of market capitalization to GDP. The monthly returns are computed as logarithm of price relatives Rt = In (Pt/Pt-1) Where Rt is the stock market returns Pt = stock market price index for period t Pt-1= price index for period t-1 In = the logarithm operator Q-Stat Prob Q-Stat Prob From the above results, R1t has a mean of 28.42667, a skewness of 1.602263, a kurtosis of 7.329423, and a Jarque - Bera value of 36.26611 with a probability value of 0.00000. The Jarque - Bera value signifies that R1t is not normally distributed. The same values can be read for FD1t and FD2t from their respective columns. The descriptive statistics showed that there exist a positive relationship between the standard deviation and the returns for all the models. Comparing FD1t and FD1t with R1t, we can see that FD1t is positvely skewed while FD2t has negative skewness showing moderate skewness. Looking at their kurtosis, again model 1 and 2 have lower values compared with R1t with that of model 2 just greater than normal value. However, they are both leptokurtic as shown by their kurtosis measure which is greater than 3 the normal figure. Suggesting again, that their standard deviation is much lower than that of R1t indicating that the distribution tends to be closer to the mean comparatively. Also there is an improvement in the values of their Jarque-Bera statistics which exhibited lower figures. On the 27 whole the model showed an improvement over the raw data. The Correlogram and ADF test have already taken care of the auto regression factor. We can then safely say that the mean equation is correctly specified. Stationary at level in increased investment and improvement in the volume and structure of savings. Incidence of stagnant growth may then be reduced. With strong growth, investors will have confidence to invest in the system. References: Goldsmith, R.W. (1969).Financial Structure, and Development, Yale University Press: New Haven. Greenwood, J., and Jovanoic (1990) Financial Development, Growth, and the Distribution of income, Journal of Political Economy 98(5):1076-107. Mala, Rajni and Reddy Mahendra (2007), Measuring Stock Market Volatility in an Emerging Economy, International Research Journal of Finance and Economics Issue 8.International Research Journal of Finance And Economics. Issue 14. McKinnon, R.I. (1973). Money and Capital in Economic Development, Brookings Institution: Washington DC. Ndukwe, E.C. 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