We start a new on-going series on volatility modeling and forecast. In this issue, we start with the definition and general dynamics of volatility in financial time series. Next, we will use historical data to develop a few methods to forecast volatility. These methods will pave the road to more advanced treatment in future issues.
Why do we care? Predicting volatility is crucial for many functions in financial markets. For a start, volatility is used by many for risk management (e.g. VaR), options pricing, asset allocation, and many other applications. Understanding volatility is vital for virtually all-time series analysis.