One of the ways in which a researcher performing forecasting for any market variable such as stock market volatility can ensure that the forecasting is accurate and authentic is through the use of time series analysis. This is because in time series analysis, researchers make use of existing figures and facts in drawing conclusions (Ziya, Dogan and Kelecioglu, 2010).
One interesting phenomenon about time series that make them appropriate for forecasting is the cyclical nature of business. Because of the business cycle that is normally observed in a typical economic environment, there are various cyclical components of time series analysis that makes it possible to forecast based on the assumption that the trends with the behavior of market variables will always remain the same (Williams and Monge, 2000). Indeed in the absence of such cyclical components, forecasting would be virtually impossible because key market variables that could make it possible to make predictions about the market would have to be investigated for each time a time series analysis has to be performed. A typical component of a business cycle is the fact that there are periods of prosperity, which are followed with recession, depression, before recovery (Grebennikov and Shah, 2013). All such cyclical components enhance forecasting.
Ziya, E., Dogan, N. and Kelecioglu, H. (2010). What Is the Predict Level of Which Computer Using Skills Measured in PISA for Achievement in Mathematics. Turkish Online Journal of Educational Technology , 9(4), ...Show more