Shin'ichi Aihara

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We study the identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility and its systems parameters is constructed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.
When a natural object or phenomenon is modelled mathematically by using a fractal dimension, it is recognized that the object or phenomenon does not often have an autocorrelation. In the fractal theory, a fractal dimension is defined as a determined value (dimension) which is independent of the scale of its covering. In practice, however, the dimension(More)
We study the adaptive filtering for risk premium and system parameters in electricity futures modes. Introducing the jump augmented Vasicek model as the spot price mode, the factor model of the electricity futures is constructed as the stochastic hyperbolic systems with jumps. Representing the main spike phenomena of the electricity spot price from one(More)
This paper treats the filtering and parameter identification for the stochastic diffusion systems with unknown boundary conditions. The physical situation of the unknown boundary conditions can be found in many industrial problems, i.g., the salt concentration model of the river Rhine is a typical example. After formulating the diffusion systems by(More)
The purpose of this paper is to derive the optimal least square state estimator for a class of stochastic pseudo-parabolic systems under noisy observations., First, we are concerned with a study on solution properties of the state equation. Within the framework of function spaces, a rigorous treatment on a class of partial differential equations with(More)