Volatility 201 – ARCH Modeling

This week, we’ll take the prior discussion further and develop an understanding of autoregressive conditional heteroskedasticity (ARCHi) volatility modeling. Why do we care? Volatility cannot be directly observed, and volatility modeling is more complicated than those of a conditional mean. The concepts…

Volatility 102

This week, we continue our on-going series on volatility modeling and forecast. In this issue, we start by defining the various terms in an asset’s return time (e.g. holding period), and explain the multi-period forecast of returns and volatility. Finally,…

Volatility 101

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…

Volatility Forecast with GARCH

This week, the “Tips & Tricks” newsletter tackles the issue of the volatility forecast using GARCHi Modeling techniques. Starting with S&P 500 ETFi monthly prices, the paper illustrates the few steps it takes to process the raw data; specify a model; fit…