dorsal/arxiv
View SchemaConditional Probability as a Measure of Volatility Clustering in Financial Time Series
| Authors | Kan Chen, C. Jayaprakash, Baosheng Yuan |
|---|---|
| Categories | |
| ArXiv ID | physics/0503157 |
| URL | https://arxiv.org/abs/physics/0503157 |
Abstract
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.
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"abstract": "In the past few decades considerable effort has been expended in\ncharacterizing and modeling financial time series. A number of stylized facts\nhave been identified, and volatility clustering or the tendency toward\npersistence has emerged as the central feature. In this paper we propose an\nappropriately defined conditional probability as a new measure of volatility\nclustering. We test this measure by applying it to different stock market data,\nand we uncover a rich temporal structure in volatility fluctuations described\nvery well by a scaling relation. The scale factor used in the scaling provides\na direct measure of volatility clustering; such a measure may be used for\ndeveloping techniques for option pricing, risk management, and economic\nforecasting. In addition, we present a stochastic volatility model that can\ndisplay many of the salient features exhibited by volatilities of empirical\nfinancial time series, including the behavior of conditional probabilities that\nwe have deduced.",
"arxiv_id": "physics/0503157",
"authors": [
"Kan Chen",
"C. Jayaprakash",
"Baosheng Yuan"
],
"categories": [
"physics.soc-ph",
"q-fin.ST"
],
"title": "Conditional Probability as a Measure of Volatility Clustering in Financial Time Series",
"url": "https://arxiv.org/abs/physics/0503157"
},
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