Takahiro Ohno

Finding Strong Relationships of stock prices using blockwise symbolic representation with dynamic time warping

This paper proposes the Blockwise Strong Relationship (BSR) method that calculates the degree of relationship between any pair of stocks based on only their prices. Our method deploys the data transformation adapted from the symbolic aggregation approximation (SAX) and the distance measure using dynamic time warping (DTW). We propose that the time series data should be processed in blocks of some appropriate size rather than the whole series at once. The experiment was done using IMI Energy indices. The result shows that our method can accurately draw the strongest related pair of stocks out of those that all look related on the surface.

An Efficient Method for Option Pricing with Finite Elements: An Endogenous Element Length Approach

This paper proposes an efficient version of the finite element method (FEM) in option pricing. In this study, we determine element lengths from the curvature of the PDE endogenously. Our method consists of two algorithms, the coarsening and the refinement of the elements. The model makes the element larger if the curvature of the local domain is low, and smaller if it is high at each time step. We apply this approach to one-dimensional options, a European up-and-out call option, and an American put option. As a result, we find that this method is able to reduce the experiment time while the accuracy remains at a comparable level.

A New Method for Parameter Estimation of the GNL Model Using Real-Coded GA

In this paper, a new parameter estimation method is proposed for the generalized nested logit (GNL) model using real-coded genetic algorithms (GA). We propose a method to recalculate and verify whether the offsprings violate constraints. In addition, we improve the selection and mutation operators in order to find the higher log likelihood. In the numerical experiments, the log likelihood of our method is compared to that obtained by the Quasi-Newton method and the normal real-coded GA, which use SPX and JGG, and not the mutation operator, with the actual point of sales data. Thus, we prove that our method finds a higher log likelihood than conventional methods.

Solving an Option Game Problem with Finite Expiration: Optimizing Terms of Patent License Agreements

In this study, we investigate the effect of expiration on the outputs of an option game problem. For this purpose, we solve a problem with finite expiration. Many previous studies have investigated the option game approach, and most of them consider infinite expiration in order to enable the problem to be solved analytically. However, there exist several situations in which it is necessary to consider finite expiration, e.g. a patent licensing agreement. Therefore, in this study, we focus on a model based on the case of a patent licensing agreement for a licenser and perform calculations for optimizing the agreement under the condition of finite expiration. We also determine the effect of sudden death risk on the outputs of an option game problem, which, in this case, are optimal terms for the licenser. By numerical experiments, we find that both expiration and sudden death risk have a strong influence on the optimal terms.