Garch Based Volatility Modeling in Bank's Stock

ABSTRACTVolatility in the stock return is an integral part of stock market with the alternating bull and bear phases. In the bullish market, the share prices soar high and in the bearish market share prices fall down and these ups and downs determine the return and volatility of the stock market. Volatility is a symptom of a highly liquid stock market. Volatility of returns in financial markets can be a major stumbling block for attracting investment. In this study, we use the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to model volatility. The analysis was done using a time series data for the period 1st January 2008 to 10th April 2012 on 18 banks in India and empirical findings revealed that all banks stock return series reports an evidence of time varying volatility which exhibits clustering and high persistence.Keywords: ARCH Model, GARCH Model, Volatility, Volatility Persistence. (ProQuest: . denotes formulae omitted.)INTRODUCTION:Wide swings in stock market prices in India in recent years have revived the financial community interest in the concept of volatility. As a concept, volatility is simple and intuitive. It measures to what extent the current price of an asset deviates from its average past values. Merton Miller (1991), the Nobel Prize winner in Economics in 1990 wrote in his book Financial Innovation and Stock Market Volatility "By volatility public seems to mean days when large market movements, particularly down moves, occur. These precipitous market wide price drops cannot always traced to a specific news event. Nor should this lack of smoking gun be seen as in any way anomalous in market for assets like common stock whose value depends on subjective judgment about cash flow and resale prices in highly uncertain future. The public takes a more deterministic view of stock prices; if the market crashes, there must be a specific reason". Modeling volatility has been subject of many theoretical and practical studies due to three main reasons i.e. firstly; volatility is an essential factor in derivative security (option) pricing formula of Black- Scholes model. Secondly, volatility index (VIX) recently becomes a popular financial instrument since its starting of trading in futures i.e. in 2004. Thirdly, volatility plays an important role for investors by helping them in taking good investment decisions. As a proxy of risk, volatility is not only of great concern for investors but also for policy makers. Investors are interested in knowing the impact of time varying volatility on the pricing of securities and the policy makers are mainly focused on the effect of volatility on the stability of financial markets and on the growth of economy. Volatility may impair the smooth functioning of the financial system and adversely affect economic performance. Stock market volatility affects the economy through its impact on consumer spending and business investment. The impact of stock market volatility on consumer spending is related via wealth effect. Increase in stock market will increase consumer wealth and this will drive up consumer spending. On the other hand, a fall in stock market will weaken consumer confidence and thus drive down consumer spending. Equity investment becomes more risky when stock market volatility is increasing. So investors shift their investment from high volatile securities to low volatile securities. Thus stock market volatility can be a sticking point in the way to attract investments in an emerging economy. Due to a number of its applications in financial market, volatility is deserved of plentiful studies for accurate estimation and forecast. Although there has been a huge number of studies that focused on estimating stock price volatility but the emerging capital markets has been paid little attention, comparable to developed capital markets. This paper measures the conditional and unconditional volatility of 18 commercial banks in India. …