Jump diffusion model with application to the Japanese stock market

Maekawa, Koichi; Lee, Sangyeol; Morimoto, Takayuki; Kawai, Ken-ichi

doi:10.1016/j.matcom.2008.01.030

Cited by 16 publications

(7 citation statements)

References 13 publications

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“…The MJD model developed by Merton (1976) is a key extension of the BS model. Several studies suggest that the anomalies of market return could be a result of jump events, and large price jumps are observed in market return data; see Das and Sundaram (1999), Drost et al (1998), Jarrow and Rosenfeld (1984), Kim et al (1994) and Maekawa et al (2008). Burger and Kliaris (2013) argue that while the diffusion process captures the volatility generated by trading activities, the jump component captures more significant changes of stock prices generated by new information.…”

Section: Literature Reviewmentioning

confidence: 99%

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Parameter estimation risk in asset pricing and risk management: A Bayesian approach

Tunaru

Zheng

2017

International Review of Financial Analysis

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Section: Literature Reviewmentioning

confidence: 99%

“…The equity index return is impacted by dividend payments. Among all studies on index option pricing, many of them ignore dividend impacts; see Eraker et al (2003), Johannes and Polson (2010), Jacquier and Jarrow (2000), Maekawa et al (2008) and Bauwens and Lubrano (2002). However, this may bias the results.…”

Section: Parameter Inferencementioning

confidence: 99%

Parameter estimation risk in asset pricing and risk management: A Bayesian approach

Tunaru

Zheng

2017

International Review of Financial Analysis

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“…The jump diffusion model is used as the data‐generating process because it is empirically well known that log‐returns contain jumps. Refer to Kou (2002) and Maekawa et al . (2008) for a detailed explanation of the model.…”

Section: Simulation Studymentioning

confidence: 99%

Optimal Weight for Realized Variance Based on Intermittent High-Frequency Data*

Masuda

Morimoto

2011

Japanese Economic Review

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In Japanese stock markets, there are two kinds of breaks, i.e., nighttime and lunch break, where we have no trading, entailing inevitable increase of variance in estimating daily volatility via naive realized variance (RV). In order to perform a much more stabilized estimation, we are concerned here with a modification of the weighting technique of Hansen and Lunde (2005). As an empirical study, we estimate optimal weights in a certain sense for Japanese stock data listed on the Tokyo Stock Exchange. We found that, in most stocks appropriate use of the optimally weighted RV can lead to remarkably smaller estimation variance compared with naive RV, hence substantially to more accurate forecasting of daily volatility.JEL classification: C19, C22, C51

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“…It has been noticed recently (Barndorff-Nielsen and Shephard 2006;Aigbedion et al, 2008;Maekawa et al, 2008;Akkurt *Corresponding author. E-mail: zhanggsumei@sina.com.…”

Section: Introductionmentioning

confidence: 98%

Fast Fourier transform technique for the European option pricing with double jumps

Wang¹

2012

Int. J. Phys. Sci.

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In this paper, we provided a fast algorithm for pricing European options under a double exponential jump-diffusion model based on Fourier transform. We derived a closed-form (CF) representation of the characteristic function of the model. By using fast Fourier transform (FFT) technique, we obtained an approximation numerical solution for the prices of European call options. Our numerical results show that our method is fast, accurate and easy to implement. The proposed option pricing method is useful for empirical analysis of asset returns and managing the corporate credit risks.

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Jump diffusion model with application to the Japanese stock market

Cited by 16 publications

References 13 publications

Parameter estimation risk in asset pricing and risk management: A Bayesian approach

Parameter estimation risk in asset pricing and risk management: A Bayesian approach

Optimal Weight for Realized Variance Based on Intermittent High-Frequency Data*

Fast Fourier transform technique for the European option pricing with double jumps

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