2012/01/13 by Steven Kou, Kou, Steven, Tony Sit +3
Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Economics and business #Innovation Diffusion and Forecasting #Methodology (stat.ME) #Pricing of Securities (q-fin.PR) #Stochastic processes and financial applications
paper · pdf · doi:10.48550/arxiv.1201.2899
openalex publication_date 2012/01/13 · openalex created_date 2021/02/01 · openalex updated_date 2026/07/28
During the last decade Levy processes with jumps have received increasing\npopularity for modelling market behaviour for both derviative pricing and risk\nmanagement purposes. Chan et al. (2009) introduced the use of empirical\nlikelihood methods to estimate the parameters of various diffusion processes\nvia their characteristic functions which are readily avaiable in most cases.\nReturn series from the market are used for estimation. In addition to the\nreturn series, there are many derivatives actively traded in the market whose\nprices also contain information about parameters of the underlying process.\nThis observation motivates us, in this paper, to combine the return series and\nthe associated derivative prices observed at the market so as to provide a more\nreflective estimation with respect to the market movement and achieve a gain of\neffciency. The usual asymptotic properties, including consistency and\nasymptotic normality, are established under suitable regularity conditions.\nSimulation and case studies are performed to demonstrate the feasibility and\neffectiveness of the proposed method.\n