Econometric analysis of realized volatility and its use in estimating stochastic volatility models
The availability of intraday data on the prices of speculative assets means that we can use quadratic variation-like measures of activity in financial markets, called realized volatility, to study the stochastic properties of returns. Here, under the assumption of a rather general stochastic volatil...
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| Veröffentlicht in: | Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2002-05, Vol.64 (2), p.253-280 |
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| container_end_page | 280 |
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| container_issue | 2 |
| container_start_page | 253 |
| container_title | Journal of the Royal Statistical Society. Series B, Statistical methodology |
| container_volume | 64 |
| creator | Barndorff-Nielsen, Ole E. Shephard, Neil |
| description | The availability of intraday data on the prices of speculative assets means that we can use quadratic variation-like measures of activity in financial markets, called realized volatility, to study the stochastic properties of returns. Here, under the assumption of a rather general stochastic volatility model, we derive the moments and the asymptotic distribution of the realized volatility error-the difference between realized volatility and the discretized integrated volatility (which we call actual volatility). These properties can be used to allow us to estimate the parameters of stochastic volatility models without recourse to the use of simulation-intensive methods. |
| doi_str_mv | 10.1111/1467-9868.00336 |
| format | Article |
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Here, under the assumption of a rather general stochastic volatility model, we derive the moments and the asymptotic distribution of the realized volatility error-the difference between realized volatility and the discretized integrated volatility (which we call actual volatility). 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Management science ; Parametric models ; Portfolio theory ; Power variation ; Pricing ; Probability and statistics ; Quadratic variation ; Quarticity ; Realized volatility ; Risk premiums ; Sciences and techniques of general use ; Statistical methods ; Statistical variance ; Statistics ; Stochastic models ; Stochastic processes ; Stochastic volatility ; Stochasticity ; Subordination ; Superposition ; Volatility</subject><ispartof>Journal of the Royal Statistical Society. 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Series B, Statistical methodology</title><description>The availability of intraday data on the prices of speculative assets means that we can use quadratic variation-like measures of activity in financial markets, called realized volatility, to study the stochastic properties of returns. Here, under the assumption of a rather general stochastic volatility model, we derive the moments and the asymptotic distribution of the realized volatility error-the difference between realized volatility and the discretized integrated volatility (which we call actual volatility). These properties can be used to allow us to estimate the parameters of stochastic volatility models without recourse to the use of simulation-intensive methods.</description><subject>Applications</subject><subject>Applied sciences</subject><subject>Autocorrelation</subject><subject>Autoregressive moving average</subject><subject>Availability</subject><subject>Computer simulation</subject><subject>Econometric analysis</subject><subject>Econometrics</subject><subject>Economic models</subject><subject>Estimate reliability</subject><subject>Estimates</subject><subject>Estimators</subject><subject>Exact sciences and technology</subject><subject>Insurance, economics, finance</subject><subject>Kalman filter</subject><subject>Leverage</subject><subject>Linear inference, regression</subject><subject>Lévy process</subject><subject>Markets</subject><subject>Mathematics</subject><subject>Modeling</subject><subject>Multivariate analysis</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Parametric models</subject><subject>Portfolio theory</subject><subject>Power variation</subject><subject>Pricing</subject><subject>Probability and statistics</subject><subject>Quadratic variation</subject><subject>Quarticity</subject><subject>Realized volatility</subject><subject>Risk premiums</subject><subject>Sciences and techniques of general use</subject><subject>Statistical methods</subject><subject>Statistical variance</subject><subject>Statistics</subject><subject>Stochastic models</subject><subject>Stochastic processes</subject><subject>Stochastic volatility</subject><subject>Stochasticity</subject><subject>Subordination</subject><subject>Superposition</subject><subject>Volatility</subject><issn>1369-7412</issn><issn>1467-9868</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqFUk1v1DAQjRCVKIUzFw65gLik9Vcc50irUihVESyoEhfLcSbUixMvdraQ_nomTbVwgpHsGfu9sZ6fnWXPKDmkGEdUyKqolVSHhHAuH2T7u52HWHNZF5Wg7FH2OKU1wZAV38-aUxuG0MMYnc3NYPyUXMpDl0cw3t1Cm98Eb0bn3Tgh3uZuTPk2Qe6GHNLoesSGb3kag702uLZ_8_vQgk9Psr3O-ARP7_NB9uXN6eeTt8XFh7N3J68vCisplUUJtCo7SVhFBDQgraDAhKlJV0tjTUeY4qqSRlhiq5Za1pSEQ9mKhlELRvGD7OVy7iaGH1sUp3uXLHhvBgjbpHlNRUkoQ-KrfxKpUoJSji4i9Wih2hhSitDpTcQ7x0lTomfb9Wyynk3Wd7Zjx_nSEWEDdkdvvFmHmFKjbzQ3UuA04WCEMExuLnFs5lxyzRTR12OPh724V2qSNb6LZrAu_dHAZclKQZAnFt5P52H6n0b9abU6XrQ-X9rW-H5x18aJUlVdI1wssEsj_NrBJn7X-HeqUl9dnmn19eMxX51f6ff8NxfLxCU</recordid><startdate>200205</startdate><enddate>200205</enddate><creator>Barndorff-Nielsen, Ole E.</creator><creator>Shephard, Neil</creator><general>Blackwell Science, Ltd</general><general>Blackwell Publishers</general><general>Blackwell</general><general>Royal Statistical Society</general><scope>BSCLL</scope><scope>IQODW</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>200205</creationdate><title>Econometric analysis of realized volatility and its use in estimating stochastic volatility models</title><author>Barndorff-Nielsen, Ole E. ; Shephard, Neil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c6116-5e175f602704ebe6c41e24a90f96acaf0283876a4c0c7d1c2b503e5d4b21cea83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Applications</topic><topic>Applied sciences</topic><topic>Autocorrelation</topic><topic>Autoregressive moving average</topic><topic>Availability</topic><topic>Computer simulation</topic><topic>Econometric analysis</topic><topic>Econometrics</topic><topic>Economic models</topic><topic>Estimate reliability</topic><topic>Estimates</topic><topic>Estimators</topic><topic>Exact sciences and technology</topic><topic>Insurance, economics, finance</topic><topic>Kalman filter</topic><topic>Leverage</topic><topic>Linear inference, regression</topic><topic>Lévy process</topic><topic>Markets</topic><topic>Mathematics</topic><topic>Modeling</topic><topic>Multivariate analysis</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Parametric models</topic><topic>Portfolio theory</topic><topic>Power variation</topic><topic>Pricing</topic><topic>Probability and statistics</topic><topic>Quadratic variation</topic><topic>Quarticity</topic><topic>Realized volatility</topic><topic>Risk premiums</topic><topic>Sciences and techniques of general use</topic><topic>Statistical methods</topic><topic>Statistical variance</topic><topic>Statistics</topic><topic>Stochastic models</topic><topic>Stochastic processes</topic><topic>Stochastic volatility</topic><topic>Stochasticity</topic><topic>Subordination</topic><topic>Superposition</topic><topic>Volatility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barndorff-Nielsen, Ole E.</creatorcontrib><creatorcontrib>Shephard, Neil</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Journal of the Royal Statistical Society. 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| identifier | ISSN: 1369-7412 |
| ispartof | Journal of the Royal Statistical Society. Series B, Statistical methodology, 2002-05, Vol.64 (2), p.253-280 |
| issn | 1369-7412 1467-9868 |
| language | eng |
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| source | RePEc; Business Source Complete; JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; Oxford University Press Journals All Titles (1996-Current); Wiley Online Library All Journals |
| subjects | Applications Applied sciences Autocorrelation Autoregressive moving average Availability Computer simulation Econometric analysis Econometrics Economic models Estimate reliability Estimates Estimators Exact sciences and technology Insurance, economics, finance Kalman filter Leverage Linear inference, regression Lévy process Markets Mathematics Modeling Multivariate analysis Operational research and scientific management Operational research. Management science Parametric models Portfolio theory Power variation Pricing Probability and statistics Quadratic variation Quarticity Realized volatility Risk premiums Sciences and techniques of general use Statistical methods Statistical variance Statistics Stochastic models Stochastic processes Stochastic volatility Stochasticity Subordination Superposition Volatility |
| title | Econometric analysis of realized volatility and its use in estimating stochastic volatility models |
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