Conditional correlation in asset return and GARCH intensity model

Choe, Geon Ho; Lee, Kyung Sub

doi:10.1007/s10182-013-0219-8

Cited by 2 publications

(3 citation statements)

References 35 publications

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“…Bacry and Muzy (2014) proposed a multivariate Hawkes process to model the price dynamics and the market impact of market orders to account for the various stylized facts of the market microstructure. For more previous financial studies on market microstructure or price dynamics based on point processes or intensity modeling, the reader should refer to Bauwens and Hautsch (2009), Embrechts et al (2011), Bacry et al (2012), Zheng et al (2014) and Choe and Lee (2014a). The Hawkes process has also been applied to modeling the credit and contagion risk, see Errais et al (2010), Aït-Sahalia et al (2010) and Dassios and Zhao (2012).…”

Section: Introductionmentioning

confidence: 99%

Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data

Lee

Seo

2017

Journal of Economic Dynamics and Control

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This study examine the theoretical and empirical perspectives of the symmetric Hawkes model of the price tick structure. Combined with the maximum likelihood estimation, the model provides a proper method of volatility estimation specialized in ultra-high-frequency analysis. Empirical studies based on the model using the ultra-high-frequency data of stocks in the S&P 500 are performed. The performance of the volatility measure, intraday estimation, and the dynamics of the parameters are discussed. A new approach of diffusion analogy to the symmetric Hawkes model is proposed with the distributional properties very close to the Hawkes model. As a diffusion process, the model provides more analytical simplicity when computing the variance formula, incorporating skewness and examining the probabilistic property. An estimation of the diffusion model is performed using the simulated maximum likelihood method and shows similar patterns to the Hawkes model. integer. This paper only considers the simple counting measure, i.e., k i = 1 for all i. A point process N can be regarded as a stochastic process by letting N (t, ω) = N ((−∞, t], ω). Consider a filtered probability space (Ω, {F t }, P), −∞ < t ≤ T , where the σ-field F t is generated by N (t). The Hawkes process is an orderly stationary point process N constructed by modeling the conditional intensity, λ. The conditional intensity function is represented as an adapted process toFor an M -dimensional Hawkes process (N 1 , . . . , N M is normally a deterministic function and called kernel. The integration of the r.h.s. is the stochastic integration defined pathwise. To apply the stochastic integration theory in the later, the Hawkes and intensity processes are considered to be right continuous processes with left limits. Self and mutually excited HawkesThis subsection briefly reviews the self and mutually excited Hawkes model. Consider a two dimensional Hawkes process (N 1 , N 2 ) with exponential decay kernels in the conditional intensities with constants µ i , α ij and β ij , for 0 < t:α 12 e −β12(t−u) dN 2 (u) = µ 1 + λ 11 (0)e −β11t + λ 12 (0)e −β12t + t 0 α 11 e −β11(t−u) dN 1 (u) + t 0

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Section: Introductionmentioning

confidence: 99%

Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data

Lee

Seo

2017

Journal of Economic Dynamics and Control

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“…First, we review the GARCH intensity model introduced by [5]. In the model, the asset price process movement is described by two Poisson-type processes with time-varying intensity processes.…”

Section: Garch Intensity Modelmentioning

confidence: 99%

“…[13], [12], [8], and [14] incorporate the leverage effects and [1] capture the conditional asymmetry. The GARCH intensity model introduced by [5] also describes the volatility clustering, leverage effect and conditional asymmetry in financial asset price dynamics and based on Poisson type intensity processes.…”

Section: Introductionmentioning

confidence: 99%

Risk-Neutral Option Pricing Under Garch Intensity Model

Lee¹

2017

Int. J. of Pure and Appl. Math.

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Abstract:The risk-neutral option pricing method under GARCH intensity model is examined. The GARCH intensity model incorporates the characteristics of financial return series such as volatility clustering, leverage effect and conditional asymmetry. The GARCH intensity option pricing model has flexibility in changing the volatility according to the probability measure change. A generalized version of the GARCH intensity risk-neutral pricing method is also provided.

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Conditional correlation in asset return and GARCH intensity model

Cited by 2 publications

References 35 publications

Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data

Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data

Risk-Neutral Option Pricing Under Garch Intensity Model

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