Diffusion Approximation of a Poisson Model for Cumulative Excess Returns
Cybernetics and Systems Analysis 2015
Oksana Pavļenko, Aija Pola, Jevgeņijs Carkovs

The paper analyzes the regressive equation for cumulative excess returns with residual conditional variances as a GARCH(1,1) process and statistical uncertainty as an AR(1) Gaussian process with correlation parameter ρ. Under assumption that the lengths of time intervals between transactions are independent exponentially distributed random variables with sufficiently small mean h, we derive diffusion approximation equations. The continuous time limit equation allows concluding that a stationary conditional variance exists. Moreover, we derive this stationary distribution as inverse gamma distribution and analyze the dependence of this distribution on the correlation parameter ρ


Atslēgas vārdi
diffusion approximation – volatility of excess returns – correlation of regression residuals
DOI
10.1007/s10559-015-9770-5
Hipersaite
http://link.springer.com/article/10.1007/s10559-015-9770-5

Pavļenko, O., Pola, A., Carkovs, J. Diffusion Approximation of a Poisson Model for Cumulative Excess Returns. Cybernetics and Systems Analysis, 2015, Vol.51, Iss.5, 772.-781.lpp. ISSN 1060-0396. e-ISSN 1573-8337. Pieejams: doi:10.1007/s10559-015-9770-5

Publikācijas valoda
English (en)
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