• Journal of Electrical Engineering and Technology
• /
• 제1권1호
• /
• pp.1-7
• /
• 2006

In an electricity market, the spot market is normally integrated with a forward or future market. The advantage of the forward market is to allow the market participants to deal in a part or the whole trading portfolio at a fix price in advance and to avoid risk associated to the uncertain price of the spot market. Japan has introduced a continuous auction base forward market from April 2005. This paper analyzes the Japanese forward market rules and operations, and introduces a new algorithm that may improve the efficiency of the market itself. The proposed algorithm enables us to give consideration to the specific characteristics of the power system and to integrate them in the auction mechanism. The benefits of the proposed algorithm are verified on an electronic simulation platform and the results described in this paper.

• 한국수학교육학회지시리즈B:순수및응용수학
• /
• 제21권4호
• /
• pp.295-305
• /
• 2014

Yan & Hanson [8] and Makate & Sattayatham [6] extended Bates' model to the stochastic volatility model with jumps in both the stock price and the variance processes. As the solution processes of finding the characteristic function, they sought such a function f satisfying $$f({\ell},{\nu},t;k,T)=exp\;(g({\tau})+{\nu}h({\tau})+ix{\ell})$$. We add the term of order ${\nu}^{1/2}$ to the exponent in the above equation and seek the explicit solution of f.

• Journal of applied mathematics & informatics
• /
• 제12권1_2호
• /
• pp.335-349
• /
• 2003

Almost all business are affected by the weather so that weather derivatives has been traded to hedge weather risk. Since the weather itself is not an asset with a market price, some analysts believe that the Black-Scholes equation could not be used appropriately to price weather derivative options. But some weather derivatives can be considered as an Asian option, we revisit the Black-scholes model. Numerical solution of the Black-Scholes equation has a significant error at the money option or around the money option, it is necessary to adopt adaptive mesh near to the strike value. Here we propose a numerical method with an adaptive grid refinement.

• KIEE International Transactions on Power Engineering
• /
• 제4A권3호
• /
• pp.159-166
• /
• 2004

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York： New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.

• 경영과학
• /
• 제24권2호
• /
• pp.115-126
• /
• 2007

Weekly minima of daily log returns of Korean composite stock price index 200 and its five industry-based business divisions over the period from January 1990 to December 2005 are fitted using two block-based extreme distributions: Generalized Extreme Value(GEV) and Generalized Logistic(GLO). Parameters are estimated using the probability weighted moments. Applicability of two distributions is investigated using the Monte Carlo simulation based empirical p-values of Anderson Darling test. Our empirical results indicate that both the GLO and GEV models seem to be comparably applicable to the weekly minima. These findings are against the evidences in Gettinby et al.[7], who claimed that the GEV model was not valid in many cases, and supported the significant superiority of the GLO model.

• 경영과학
• /
• 제30권2호
• /
• pp.117-132
• /
• 2013

The objective of this paper is to provide an improved technology appraisal model, which considers a variety of macroeconomic variables such as consumer price index and producer price index. The improved model was built using cross correlation analysis and logistic regression analysis. The AUROC analysis showed that goodness-of-fit of the proposed model turned out to be improved than that of the existing model. The model proposed in the paper would be helpful for making a reasonable investments and financing decision, lessening the default rates by systematic risk management, and enhancing the technology commercialization capabilities.

• 산업경영시스템학회지
• /
• 제34권4호
• /
• pp.89-97
• /
• 2011

Traditional quality control for manufacturing or service sector is not suitable for the quality control of a project as the project is one-time task constrained by time, cost, and quality. To meet the internal and external customers' requirements, quality costs approach to the project will be effective. Hence, we propose PONC (price of nonconformance) estimation procedure and a mathematical model, which are focused on activity-based prevention in the execution step and warranty step of EPLC (extended project life cycle). This procedure and model will help project manager develop preventive action plan for project quality costs minimization from nonconformance risk activities and PONC estimates information.

• Journal of Multimedia Information System
• /
• 제8권3호
• /
• pp.183-190
• /
• 2021

In this paper, we implement a system for a fund recommendation based on the investment propensity and for a future fund price prediction. The investment propensity is classified by scoring user responses to series of questions. The proposed system recommends the funds with a suitable risk rating to the investment propensity of the user. The future fund prices are predicted by Prophet model which is one of the machine learning methods for time series data prediction. Prophet model predicts future fund prices by learning the parameters related to trend changes. The prediction by Prophet model is simple and fast because the temporal dependency for predicting the time-series data can be removed. We implement web pages for the fund recommendation and for the future fund price prediction.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권10호
• /
• pp.621-628
• /
• 2020

The study investigates a promising sustainable crop-insurance risk mitigation plan, namely, Group Risk Income Protection (GRIP) insurance, for the cultivation of Para rubber, a crop for which Southern Thailand constitutes over half of the national harvested area, but which recently experienced a shift in prices and yields, substantially affecting farmers. The research takes as its starting point historical data covering the 2001-2018 period for this crop's cultivation in three of Thailand's Andaman South Coast provinces - Trang, Krabi, and Phangnga. The results indicate that, from a relatively high base in 2001, Trang's yields dropped sharply before a more gradual decline (apparently still ongoing), whereas those for Krabi and Phangnga followed a smoother downward trajectory throughout the period. Meanwhile, prices everywhere rose steadily before falling from 2011 onwards - a decrease that shows no signs of abating. The yield/price relationship was negative for one province and slightly positive for the other provinces. Furthermore, all provinces' Para rubber income initially grew continually but fell after 2011, with this trend seemingly persisting to this day. The paper's findings suggest that, after early moves to entrench GRIP insurance, it looks set to become a feasible option for Para rubber, making policy agreement details an interesting subject for subsequent investigations.

• 대한가정학회지
• /
• 제30권1호
• /
• pp.149-161
• /
• 1992

The purpose of this study is to analyze information search activity in purchasing behavior of household electric goods. Qusetionare survey method was used in this research. The sample was taken from 302 housewives living in Seoul, from 9th of Nov. to 20th of Nov, in 1991. Used statical methods were Frequency, Percentage, Crosstab, Anova, and Regression Analysis. The major findings are summarized as follows : 1) Component elements of information search : The means of acquiring information is that friends, neighbors, sales are most. A cause of choosing information is the sequence of satisfaction after using, easiness of interaction. The time in choosing goods is more month. 2) Component element of information search as social economic status housewife : children numbers and means of acquiring information(P<.01), education and a cause of choosing information(P<.05), life cost per month and a cause of choosing information(P<.05), social economic status and a time information search are significant. 3) A perception of risk as searching information : Among searching content of information a price influence a perception of risk. 4) Content of searching information and satisfaction of purchasing experience : Best choice is significant as quality of goods, difference of quality is significant as safety and degree of offering information is significant as a brand. 5) Satisfaction of purchasing experience following practical use of information : Best choice is significant as viewing of an exhibit and opinion of user. Difference of quality is not significant as any vairable. Degree of offer information influence searching pamphlet, searching an advertisement and opinion of user. 6) A perception of risk following source of an information : A perception of risk is most influenced by pamphlet.