Physics – Physics and Society
Scientific paper
2005-03-18
Physics
Physics and Society
6 pages, 4 figures
Scientific paper
In the past few decades considerable effort has been expended in characterizing and modeling financial time series. A number of stylized facts have been identified, and volatility clustering or the tendency toward persistence has emerged as the central feature. In this paper we propose an appropriately defined conditional probability as a new measure of volatility clustering. We test this measure by applying it to different stock market data, and we uncover a rich temporal structure in volatility fluctuations described very well by a scaling relation. The scale factor used in the scaling provides a direct measure of volatility clustering; such a measure may be used for developing techniques for option pricing, risk management, and economic forecasting. In addition, we present a stochastic volatility model that can display many of the salient features exhibited by volatilities of empirical financial time series, including the behavior of conditional probabilities that we have deduced.
Chen Kan
Jayaprakash Ciriyam
Yuan Baosheng
No associations
LandOfFree
Conditional Probability as a Measure of Volatility Clustering in Financial Time Series does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Conditional Probability as a Measure of Volatility Clustering in Financial Time Series, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Conditional Probability as a Measure of Volatility Clustering in Financial Time Series will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-502532