Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
A model that has been widely employed to measure the volatility is GARCH (General Autoregressive Conditional Heteroskedasticity). In this paper, GARCH will be employed to evaluate impacts of measure to narrow the fluctuation limit on risks in Vietnam’s stock market. | 116 | Lê Đình Nghi Evaluating Impacts of Reduction in Fluctuation Limit Evaluating Impacts of Reduction in Fluctuation Limit on Stock Price Risks in Vietnam LÊ ĐÌNH NGHI Master of Economics, Sài Gòn University Email: nghiledinh@gmail.com ABSTRACT Vietnam’s stock market in late 2007 experienced a sharp fall. Since March 2008, the State Security Commission of Vietnam (SSC) has from time to time adjusted the fluctuation limit on stock price in the hope of precluding the panic among investors and reducing the market risks. Theoretically, risks can be quantified by the volatility which can be measured by the conditional variance of the chain of rates of returns. A model that has been widely employed to measure the volatility is GARCH (General Autoregressive Conditional Heteroskedasticity). In this paper, GARCH will be employed to evaluate impacts of measure to narrow the fluctuation limit on risks in Vietnam’s stock market. Keywords: returns, GARCH, fluctuation limit, stock market JED No.214 October 2012 | 117 1. INTRODUCTION Vietnam’s stock market since late 2007 has suffered a sharp decline. Just from March 2008 to August 2008, SSC adjusted the fluctuation limit three times hoping to prevent an unexpected “panic” among investors and reduce market risks. Measuring the dispersion of probability density of random variables is based on the price volatility, i.e. the standard deviation or the square root of variance of a random variable. Specifically, if we take stock indices into account, the volatility or the dispersion of rates of return of a stock or a market index can be measured by the standard deviation of the stock return at the time t. In the event that the rate of return of a stock is displayed by a logarithmic equation, the volatility can be written as follows: ( ) [ ] where, Pt is the market index or the stock price at the time t; and t-1 denotes the standard deviation at the time t-1. Accordingly, the higher the volatility, the higher the stock .