Generalized AutoRegressive Conditional Heteroskedasticity – GARCH

What is ‘Generalized AutoRegressive Conditional Heteroskedasticity (GARCH)’

A statistical model used by financial institutions to estimate the volatility of stock returns. This information is used by banks to help determine what stocks will potentially provide higher returns, as well as to forecast the returns of current investments to help in the budgeting process.

Explaining ‘Generalized AutoRegressive Conditional Heteroskedasticity (GARCH)’

There are many variations of GARCH, including NGARCH to include correlation, and IGARCH which restricts the volatility parameter. Each model can be used to accomodate the specific qualities of the stock, industry or economic state.

Further Reading