Abstract: A system for correctly evaluating a price distribution and a risk distribution for a financial product or its derivatives introduces a probability density function generated with a Boltzmann model at a higher accuracy than the Gaussian distribution for a probability density. The system has an initial value setup unit and an evaluation condition setup unit. Initial values include at least one of price, price change rate, and the price change direction of a financial product. The evaluation conditions include at least time steps and the number of trials. The Boltzmann model analysis unit receives the initial values and the evaluation conditions, and repeats simulations of price fluctuation, based on the Boltzmann model using a Monte Carlo method. A velocity/direction distribution setup unit supplies the probability distributions of the price, price change rate, and the price change direction for the financial product to the Boltzmann model analysis unit.

Abstract: A system for correctly evaluating price distribution and risk distribution for a financial product or its derivatives introduces a probability density function generated with a Boltzmann model at a higher accuracy than the Gaussian distribution for a probability density. The system has an initial value setup unit and an evaluation condition setup unit. Initial values include at least one of price, price change rate, and price change direction of a financial product. The evaluation conditions include at least time steps and a number of trials. A Boltzmann model analysis unit receives the initial values and the evaluation conditions, and repeats simulations of price fluctuation, based on the Boltzmann model using a Monte Carlo method. A velocity/direction distribution setup unit supplies probability distributions of the price, price change rate, and price change direction for the financial product to the Boltzmann model analysis unit.

Abstract: A system for correctly evaluating a price distribution and a risk distribution for a financial product or its derivatives introduces a probability density function generated with a Boltzmann model at a higher accuracy than the Gaussian distribution for a probability density. The system has an initial value setup unit and an evaluation condition setup unit. Initial values include at least one of price, price change rate, and the price change direction of a financial product. The evaluation conditions include at least time steps and the number of trials. The Boltzmann model analysis unit receives the initial values and the evaluation conditions, and repeats simulations of price fluctuation, based on the Boltzmann model using a Monte Carlo method. A velocity/direction distribution setup unit supplies the probability distributions of the price, price change rate, and the price change direction for the financial product to the Boltzmann model analysis unit.

Abstract: This disaster risk assessment system assesses a difference between a disaster-time direct loss amount in current equipment and disaster-time direct loss amount in equipment after taking measures and compares the difference with a disaster measures equipment cost for presenting decision making information on disaster measures. As assessment requirements, the system also takes a business value loss amount into consideration and presents an insurance premium that is required to cover an expected disaster-time loss amount by an insurance payment.

Abstract: A power trading risk management system includes means for evaluating and inputting a predicted value of an electricity demand, an electricity price in a spot market, a cost function of a power generator to be used, a fuel price, a fixed cost and the like, means for modeling a random fluctuation of a future electricity price by use of a fluctuation of a past electricity price, means for calculating a profit accrued from electricity sale and the like, means for evaluating a risk accrued from a random fluctuation of the electricity price, means for producing an appropriate electricity portfolio, means for reevaluating a value of the portfolio on a daily basis, means for reorganizing the portfolio for risk reduction, and means for deciding a price of a financial derivative instrument for risk hedging. The system measures a market risk associated with a power trading, and produces the portfolio for maximizing a profit while maintaining the risk within a tolerance.

Abstract: For a comprehensive risk evaluation of the electricity price fluctuations, respective relationships between power supplies or power demands and electricity prices are derived from data of historical power supply or power demand and data of historical electricity price for respective power exchanges, respective probability distributions of electricity price fluctuations relating to uncertain fluctuations of the power supply or the power demand are computed by using the respective relationships in a given period for evaluation of a market risk, the market risk of electricity price is measured by using the respective probability distributions of electricity price fluctuations, a probability distribution for randomly fluctuating components is derived by Monte Carlo simulation, and a market risk to the electricity price fluctuations is evaluated.