Volatility Clustering

Definition: Volatility clustering is as follows: In a time series of stock prices, it is observed that the variance of returns or log-prices is high for extended periods and then low for extended periods. (E.g. the variance of daily returns can be high one month and low the next.) This occurs to a degree that makes an iid model of log-prices or returns unconvincing. This property of time series of prices can be called 'volatility clustering' and is usually approached by modeling the price process with an ARCH-type model.

(Econterms)

Terms related to Volatility Clustering:

• Variance
• Variance Decomposition
• Quasi-Differencing

About.Com Resources on Volatility Clustering:

• How Stock Prices Are Determined
• Do Changes in Stock Prices Cause Recessions?
• When Stock Prices Go Down, Where Does the Money Go?

Writing a Term Paper? Here are a few starting points for research on Volatility Clustering:

Books on Volatility Clustering:

• Forecasting in Business and Economics, Second Edition
• Handbook of Economic Forecasting, Volume 1
• Long-Run Economic Relationships: Readings in Cointegration

Journal Articles on Volatility Clustering:

• Volatility Clustering in Financial Markets: A Microsimulation of Interacting Agents
• Clustered volatility in multiagent dynamics
• Volatility Clustering and Scaling for Financial Time Series due to Attractor Bubbling