2023 Fiscal Year Annual Research Report
A new type of volatility estimator defined by jump diffusion model
| Project/Area Number |
18K03431
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| Research Institution | Tokyo City University |
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Principal Investigator |
金川 秀也 東京都市大学, 共通教育部, 教授 (50185899)
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| Co-Investigator(Kenkyū-buntansha) |
滑川 光裕 嘉悦大学, 経営経済学部, 教授 (60289931)
前園 宜彦 中央大学, 理工学部, 教授 (30173701) [Withdrawn]
税所 康正 東京学芸大学, 教育学部, 研究員 (70195973) [Withdrawn]
細野 泰彦 東京都市大学, 情報工学部, 准教授 (40157029) [Withdrawn]
上江洲 弘明 金沢工業大学, 基礎教育部, 准教授 (60350401)
新海 公昭 東京家政学院大学, 現代生活学部, 准教授 (10612137)
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| Project Period (FY) |
2018-04-01 – 2024-03-31
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| Keywords | stock market index / Merton model / Black-Scholes model / compound Poisson process / stochastic volatility |
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| Outline of Annual Research Achievements |
We investigates the daily share prices of Japan NIKKEI 225 Stock Market Indexes and the Dow-Jones industrial average for long term observations and identifies pure jumps using a Merton model, which consists of the Black-Scholes model and a compound Poisson process with a stochastic volatility. The financial data is observed in the 30 years period from 25/May/1985 to 2/May/2015. Furthermore, a robustness of the scheme with respect to selecting observation periods is also shown to investigate three periods of each 10 years in the 30 years. To resolve the above problem we focus on that the number of big jumps of returns of stock indexes which follows Poisson distribution since such returns are generated from the compound Poisson part of the Merton model.
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