Derivatives
Using GARCH to Forecast Volatility
π― GARCH is not just a descriptive model β its purpose is to forecast the volatility of future returns on invested capital. In previous posts, we: Now we […]
Archive
Category: Excel Models
Derivatives
Validation of Volatility Clustering
Models of return volatility such as EWMA and GARCH aim to explain volatility clustering. In real markets, calm periods tend to be followed by calm periods, while turbulent […]
Derivatives
Maximum Likelihood Method
The maximum likelihood method is used in modeling to estimate the parameters that make historical events most probable. Suppose an event has occurred. If we assume that this […]
Derivatives
GARCH Model
GARCH (1,1) and Volatility Clustering Financial markets exhibit an important property: volatility clustering and reversion toward a long-run average. In other words, large movements tend to be followed […]
Derivatives
EWMA vs Moving Average Volatility
Volatility is such an overused term that we may forget how important the assumptions are that lead to the final number. Let us start with the basics. When […]
Derivatives
VaR – Advanced Issues
In previous posts, I covered the calculation of portfolio Value at Risk (VaR) and Expected Shortfall using the historical simulation and linear modeling methods. Now, in order to […]
Derivatives
VaR – Linear Model
In the previous note about VaR, I discussed and showed how it is calculated using simulation of historical data. Now I will demonstrate how it is calculated using […]