Parameter estimation from multinomial trees to jump diffusions with k means clustering

Lee, Kiseop and Xu, Mingxin (2007): Parameter estimation from multinomial trees to jump diffusions with k means clustering. Unpublished.

Abstract

Ever since the pioneering work of Cox, Ross and Rubinstein, tree models have been popular among asset pricing methods. On the other hand, statistical estimation of parameters of tree models has not been studied as much. In this paper, we use K Means Clustering method to estimate the parameters of multinomial trees. By the weak convergence property of multinomial trees to continuous-time models, we show that this method can be in turn used to estimate parameters in continuous time models, illustrated by an example of jump-diffusion model.

• Item Type: MPRA Paper
• Institution: University of North Carolina at Charlotte
• Language: English
• Keywords: parameter estimation; multinomial tree; jump model; weak convergence; K means clustering
• Subjects: G - Financial Economics > G1 - General Financial Markets > G10 - General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C10 - General

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