Local risk-minimization for Barndorff-Nielsen and Shephard models

Takuji Arai, Yuto Imai, Ryoichi Suzuki

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

We obtain explicit representations of locally risk-minimizing strategies for call and put options in Barndorff-Nielsen and Shephard models, which are Ornstein–Uhlenbeck-type stochastic volatility models. Using Malliavin calculus for Lévy processes, Arai and Suzuki (Int. J. Financ. Eng. 2:1550015, 2015) obtained a formula for locally risk-minimizing strategies for Lévy markets under many additional conditions. Supposing mild conditions, we make sure that the Barndorff-Nielsen and Shephard models satisfy all the conditions imposed in (Arai and Suzuki in Int. J. Financ. Eng. 2:1550015, 2015). Among others, we investigate the Malliavin differentiability of the density of the minimal martingale measure. Moreover, we introduce some numerical experiments for locally risk-minimizing strategies.

Original languageEnglish
Pages (from-to)551-592
Number of pages42
JournalFinance and Stochastics
Volume21
Issue number2
DOIs
Publication statusPublished - 2017 Apr 1

Fingerprint

Minimal Martingale Measure
Malliavin Calculus
Stochastic Volatility Model
Differentiability
Numerical Experiment
Model
Strategy
Local risk-minimization
Market
Call option
Minimal martingale measure
Numerical experiment
Stochastic volatility model
Put option
Malliavin calculus

Keywords

  • Barndorff-Nielsen and Shephard models
  • Local risk-minimization
  • Lévy processes
  • Malliavin calculus
  • Stochastic volatility models

ASJC Scopus subject areas

  • Statistics and Probability
  • Finance
  • Statistics, Probability and Uncertainty

Cite this

Local risk-minimization for Barndorff-Nielsen and Shephard models. / Arai, Takuji; Imai, Yuto; Suzuki, Ryoichi.

In: Finance and Stochastics, Vol. 21, No. 2, 01.04.2017, p. 551-592.

Research output: Contribution to journalArticle

Arai, Takuji ; Imai, Yuto ; Suzuki, Ryoichi. / Local risk-minimization for Barndorff-Nielsen and Shephard models. In: Finance and Stochastics. 2017 ; Vol. 21, No. 2. pp. 551-592.
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