Self-Exciting Jumps, Learning, and Asset Pricing Implications

The paper proposes a self-exciting asset pricing model that takes into account cojumps between prices and volatility and self-exciting jump clustering. We employ a dence of self-exciting jump clustering since the 1987 market crash, and its importance Bayesian learning approach to implement real time...

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Main Authors: FULOP, Andras, LI, Junye, YU, Jun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/soe_research/1587
https://ink.library.smu.edu.sg/context/soe_research/article/2586/viewcontent/02_2014.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.soe_research-25862019-04-19T08:49:29Z Self-Exciting Jumps, Learning, and Asset Pricing Implications FULOP, Andras LI, Junye YU, Jun The paper proposes a self-exciting asset pricing model that takes into account cojumps between prices and volatility and self-exciting jump clustering. We employ a dence of self-exciting jump clustering since the 1987 market crash, and its importance Bayesian learning approach to implement real time sequential analysis. We find evidence of self-exciting jump clustering since the 1987 market crash, and its importance becomes more obvious at the onset of the 2008 global financial crisis. It is found that learning affects the tail behaviors of the return distributions and has important implications for risk management, volatility forecasting and option pricing. 2014-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1587 https://ink.library.smu.edu.sg/context/soe_research/article/2586/viewcontent/02_2014.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Self-Excitation Jump Clustering Tail behaviors Parameter Learning Sequential Bayes Factor Excess Volatility Volatility Forecasting Option Pricing Econometrics Finance and Financial Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Self-Excitation
Jump Clustering
Tail behaviors
Parameter Learning
Sequential Bayes Factor
Excess Volatility
Volatility Forecasting
Option Pricing
Econometrics
Finance and Financial Management
spellingShingle Self-Excitation
Jump Clustering
Tail behaviors
Parameter Learning
Sequential Bayes Factor
Excess Volatility
Volatility Forecasting
Option Pricing
Econometrics
Finance and Financial Management
FULOP, Andras
LI, Junye
YU, Jun
Self-Exciting Jumps, Learning, and Asset Pricing Implications
description The paper proposes a self-exciting asset pricing model that takes into account cojumps between prices and volatility and self-exciting jump clustering. We employ a dence of self-exciting jump clustering since the 1987 market crash, and its importance Bayesian learning approach to implement real time sequential analysis. We find evidence of self-exciting jump clustering since the 1987 market crash, and its importance becomes more obvious at the onset of the 2008 global financial crisis. It is found that learning affects the tail behaviors of the return distributions and has important implications for risk management, volatility forecasting and option pricing.
format text
author FULOP, Andras
LI, Junye
YU, Jun
author_facet FULOP, Andras
LI, Junye
YU, Jun
author_sort FULOP, Andras
title Self-Exciting Jumps, Learning, and Asset Pricing Implications
title_short Self-Exciting Jumps, Learning, and Asset Pricing Implications
title_full Self-Exciting Jumps, Learning, and Asset Pricing Implications
title_fullStr Self-Exciting Jumps, Learning, and Asset Pricing Implications
title_full_unstemmed Self-Exciting Jumps, Learning, and Asset Pricing Implications
title_sort self-exciting jumps, learning, and asset pricing implications
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/soe_research/1587
https://ink.library.smu.edu.sg/context/soe_research/article/2586/viewcontent/02_2014.pdf
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