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Statistical Hypothesis Testing for Roughness of Volatility

Research Project

Project/Area Number 19K23224
Research Category

Grant-in-Aid for Research Activity Start-up

Allocation TypeMulti-year Fund
Review Section 0107:Economics, business administration, and related fields
Research InstitutionHiroshima University

Principal Investigator

Takabatake Tetsuya  広島大学, 人間社会科学研究科(社), 助教 (80846949)

Project Period (FY) 2019-08-30 – 2023-03-31
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords非整数Brown運動 / 高頻度観測 / 観測誤差 / 確率ボラティリティ / 高頻度データ / 確率ボラティリティモデル / ラフボラティリティ
Outline of Research at the Start

本研究の目的は、対数資産価格の実現分散時系列データに基づく、資産価格のボラティリティ(価格変動の大きさを表す)変動の激しさに関する統計的仮説検定理論を構築することである。目的の達成に向け、高頻度自己相似定常Gauss時系列に観測誤差が加わった状況下での、(近似)尤度関数やスコア関数などの漸近挙動を明らかにする。また、非整数Ornstein-Uhlenbeck過程などの、非整数Brown運動で駆動されるエルゴード的確率微分方程式に対し、Hurst指数と拡散係数の推定と同時に、ドリフト項が含む未知定数を推定する手法の開発も並行して行っていく。

Outline of Final Research Achievements

In order to accurately estimate the Hurst index and volatility of the driving noise of the log-volatility process, which is a latent variable, from the log-realized variance time series data, we developed a theory of estimating the Hurst index and volatility of the driving noise under noisy observations. In this study, we analyze the local asymptotic behavior of the likelihood ratio random fields under the condition that high-frequently observed data of the fractional Brownian motion contains observational errors, so that we succeeded to derive optimal convergence rates and asymptotic variances of estimators and construct an estimator that satisfies the asymptotic optimality.

Academic Significance and Societal Importance of the Research Achievements

本研究で行なった高頻度観測データからスケール則や観測誤差の構造を推定する手法の開発、特に最適な収束レートや漸近分散を満たす推定量の開発は幾つかの技術的困難によりこれまで未解決な問題であったため、本研究の学術的意義は大きいと考える。また上述したファイナンスの問題に限らず、計量経済学や工学などの分野で観測される実際のデータには、推定したい確率過程とは別の確率過程が観測誤差として含まれる状況がごく自然に生じるため、様々な分野への応用が今後期待できる。

Report

(5 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (13 results)

All 2023 2022 2021 2020 2019 Other

All Int'l Joint Research (1 results) Journal Article (2 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 2 results) Presentation (10 results) (of which Int'l Joint Research: 5 results,  Invited: 4 results)

  • [Int'l Joint Research] University Paris-Dauphine/Le Mans University(フランス)

    • Related Report
      2022 Annual Research Report
  • [Journal Article] Corrigendum: Error Bounds and Asymptotic Expansions for Toeplitz Product Functionals of Unbounded Spectra2023

    • Author(s)
      Tetsuya Takabatake
    • Journal Title

      Journal of Time Series Analysis

      Volume: -

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Consistent estimation for fractional stochastic volatility model under high‐frequency asymptotics2022

    • Author(s)
      Fukasawa Masaaki、Takabatake Tetsuya、Westphal Rebecca
    • Journal Title

      Mathematical Finance

      Volume: 32 Issue: 4 Pages: 1086-1132

    • DOI

      10.1111/mafi.12354

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Presentation] Asymptotically Efficient Estimation of Fractional Brownian Motion with Additive Noise2023

    • Author(s)
      Tetsuya Takabatake
    • Organizer
      SH3 Conference
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 観測誤差を含む非整数Brown運動に対する漸近有効推定2022

    • Author(s)
      髙畠 哲也
    • Organizer
      統計関連学会連合大会
    • Related Report
      2022 Annual Research Report
  • [Presentation] Asymptotically Efficient Estimation of Fractional Brownian Motion with Additive Noise2022

    • Author(s)
      Tetsuya Takabatake
    • Organizer
      EFFI Japan-France statistic seminar
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Local Asymptotic Normality Property for Fractional Brownian Motion with Measurement Error2022

    • Author(s)
      Tetsuya Takabatake
    • Organizer
      The SH3 Conference on Econometrics
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research
  • [Presentation] Local Asymptotic Normality Property for Fractional Brownian Motion with Measurement Error2021

    • Author(s)
      Tetsuya Takabatake
    • Organizer
      Computational and Methodological Statistics
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] ドリフトを持つ非整数Brown運動に対する疑似尤度解析2021

    • Author(s)
      髙畠 哲也
    • Organizer
      統計関連学会連合大会
    • Related Report
      2021 Research-status Report
    • Invited
  • [Presentation] 連続観測に基づく非整数Ornstein-Uhlenbeck過程の局所漸近正規性2021

    • Author(s)
      髙畠 哲也
    • Organizer
      岡山確率論セミナー
    • Related Report
      2021 Research-status Report
  • [Presentation] 観測誤差を含む非整数Brown運動に対する局所漸近正規性2020

    • Author(s)
      高畠 哲也
    • Organizer
      統計関連学会連合大会
    • Related Report
      2020 Research-status Report
  • [Presentation] Is Volatility Rough ?2019

    • Author(s)
      Tetsuya Takabatake
    • Organizer
      EcoSta 2019
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] 観測誤差を含む非整数Brown運動に対する局所漸近正規性2019

    • Author(s)
      高畠 哲也
    • Organizer
      第七回数理ファイナンス合宿型セミナー
    • Related Report
      2019 Research-status Report
    • Invited

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Published: 2019-09-03   Modified: 2024-01-30  

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