Statistical Inference of Stochastic Copulas and Their Application to Finance
| Project/Area Number |
23530250
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Economic statistics
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| Research Institution | Hitotsubashi University |
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Principal Investigator |
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 確率的裾依存性コピュラ / 確率的ヴァインコピュラ / 粒子フィルター法 / CVaR最小化 / レバレッジ付き確率ボラティリティ / テールリスク・パリティ / 動的条件付きコピュラ / ボラティリティ・パズル / 多変量ファクター確率ボラティリティ / MCMC |
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| Research Abstract |
We find out that the particle filtering technique is an effective method for statistical inference of stochastic copulas with time-varying dependence structure. As financial applications we have developed copula-based stochastic volatility(SV) model, multi-variate SV model,stochastic vein copula model, and so on. Furthermore, we have proposed new types of portfolio optimization based on the tail-risk parity/budgeting approach.
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Report
(4 results)
Research Products
(28 results)
