Inference theory on volatility functional dependencies
We develop inference theory for models involving possibly nonlinear transforms of the elements of the spot covariance matrix of a multivariate continuous-time process observed at high frequency. The framework can be used to study the relationship among the elements of the latent spot covariance matr...
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sg-smu-ink.soe_research-35702022-02-07T04:00:18Z Inference theory on volatility functional dependencies LI, Jia TODOROV, Viktor TAUCHEN, George. We develop inference theory for models involving possibly nonlinear transforms of the elements of the spot covariance matrix of a multivariate continuous-time process observed at high frequency. The framework can be used to study the relationship among the elements of the latent spot covariance matrix and processes defined on the basis of it such as systematic and idiosyncratic variances, factor betas and correlations on a fixed interval of time. The estimation is based on matching model-implied moment conditions under the occupation measure induced by the spot covariance process. We prove consistency and asymptotic mixed normality of our estimator of the (random) coefficients in the volatility model and further develop model specification tests. We apply our inference methods to study variance and correlation risks in nine sector portfolios comprising the S&P 500 index. We document sector-specific variance risks in addition to that of the market and time-varying heterogeneous correlation risk among the market-neutral components of the sector portfolio returns. 2016-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2571 info:doi/10.1016/j.jeconom.2016.01.004 https://ink.library.smu.edu.sg/context/soe_research/article/3570/viewcontent/Inference_Theory.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University High-frequency data; Occupation measure; Semimartingale; Specification test; Stochastic volatility Economic Theory |
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High-frequency data; Occupation measure; Semimartingale; Specification test; Stochastic volatility Economic Theory LI, Jia TODOROV, Viktor TAUCHEN, George. Inference theory on volatility functional dependencies |
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We develop inference theory for models involving possibly nonlinear transforms of the elements of the spot covariance matrix of a multivariate continuous-time process observed at high frequency. The framework can be used to study the relationship among the elements of the latent spot covariance matrix and processes defined on the basis of it such as systematic and idiosyncratic variances, factor betas and correlations on a fixed interval of time. The estimation is based on matching model-implied moment conditions under the occupation measure induced by the spot covariance process. We prove consistency and asymptotic mixed normality of our estimator of the (random) coefficients in the volatility model and further develop model specification tests. We apply our inference methods to study variance and correlation risks in nine sector portfolios comprising the S&P 500 index. We document sector-specific variance risks in addition to that of the market and time-varying heterogeneous correlation risk among the market-neutral components of the sector portfolio returns. |
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LI, Jia TODOROV, Viktor TAUCHEN, George. |
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LI, Jia TODOROV, Viktor TAUCHEN, George. |
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LI, Jia |
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Inference theory on volatility functional dependencies |
title_short |
Inference theory on volatility functional dependencies |
title_full |
Inference theory on volatility functional dependencies |
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Inference theory on volatility functional dependencies |
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Inference theory on volatility functional dependencies |
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inference theory on volatility functional dependencies |
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Institutional Knowledge at Singapore Management University |
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2016 |
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https://ink.library.smu.edu.sg/soe_research/2571 https://ink.library.smu.edu.sg/context/soe_research/article/3570/viewcontent/Inference_Theory.pdf |
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