• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.20 no.2
• /
• pp.123-135
• /
• 2016

This article deals with the pricing of Asian options under a constant elasticity of variance (CEV) model as well as a stochastic elasticity of variance (SEV) model. The CEV and SEV models are underlying asset price models proposed to overcome shortcomings of the constant volatility model. In particular, the SEV model is attractive because it can characterize the feature of volatility in risky situation such as the global financial crisis both quantitatively and qualitatively. We use an asymptotic expansion method to approximate the no-arbitrage price of an arithmetic average Asian option under both CEV and SEV models. Subsequently, the zero and non-zero constant leverage effects as well as stochastic leverage effects are compared with each other. Lastly, we investigate the SEV correction effects to the CEV model for the price of Asian options.

• East Asian mathematical journal
• /
• v.35 no.1
• /
• pp.59-66
• /
• 2019

In this paper we study implicit-explicit (IMEX) methods combined with a semi-Lagrangian scheme to evaluate the prices of fixed strike arithmetic Asian options under jump-diffusion models. An Asian option is described by a two-dimensional partial integro-differential equation (PIDE) that has no diffusion term in the arithmetic average direction. The IMEX methods with the semi-Lagrangian scheme to solve the PIDE are discretized along characteristic curves and performed without any fixed point iteration techniques at each time step. We implement numerical simulations for the prices of a European fixed strike arithmetic Asian put option under the Merton model to demonstrate the second-order convergence rate.

• Journal of the Korea Society of Computer and Information
• /
• v.8 no.3
• /
• pp.113-123
• /
• 2003

Many researches on the application of neural networks for making financial index prediction have proven their advantages over statistical and other methods. In this paper, a neural network model is proposed for the Buying, Holding or Selling timing prediction in stocks by the price index of stocks by inputting the closing price and volume of dealing in stocks and the technical indexes(MACD, Psychological Line). This model has an equalized multi-layer arithmetic function as well as the time series prediction function of backpropagation neural network algorithm. In the case that the numbers of learning data are unbalanced among the three categories (Buying, Holding or Selling), the neural network with conventional method has the problem that it tries to improve only the prediction accuracy of the most dominant category. Therefore, this paper, after describing the structure, working and learning algorithm of the neural network, shows the equalized multi-layer arithmetic method controlling the numbers of learning data by using information about the importance of each category for improving prediction accuracy of other category. Experimental results show that the financial index prediction using the equalized multi-layer arithmetic neural network has much higher correctness rate than the other conventional models.

• Journal of Intelligence and Information Systems
• /
• v.1 no.2
• /
• pp.103-121
• /
• 1995

This study proposes a artificial neural network method to predict the time to buy and sell the stocks listed on the Korea Composite Stock Price Index(KOSPI). Four types (NN1, NN2, NN3, NN4) of independent networks were developed to predict KOSPIs up/down direction after four weeks. These networks have a difference only in the length of learning period. NN5 - arithmetic average of four networks outputs - shows an higher accuracy than other network types and Multiple Linear Regression (MLR), and buying and selling simulation using systems outputs produces higher reture than buy-and-hold strategy.

• Communications of the Korean Mathematical Society
• /
• v.28 no.2
• /
• pp.397-406
• /
• 2013

We present an improved binomial method for pricing European- and American-type Asian options based on the arithmetic average of the prices of the underlying asset. At each node of the tree we propose a simple algorithm to choose the representative averages among all the effective averages. Then the backward valuation process and the interpolation are performed to compute the price of the option. The simulation results for European and American Asian options show that the proposed method gives much more accurate price than other recent lattice methods with less computational effort.

• Journal of Distribution Science
• /
• v.16 no.4
• /
• pp.67-74
• /
• 2018

Purpose - Most of the amendments to the law on the improvement of the distribution structure of mobile communication terminal equipment, the fully self-sufficient system of terminals, and the separated disclosure system on the terminals are aimed at securing transparency of the distribution structure by eliminating or reducing handset subsidies. This study investigates what items are important for the purchase of mobile phones in various and rapidly changing mobile phone markets from the consumer's point of view and tries to make a strategic suggestion for future mobile distribution strategies. Research design, data, and methodology - The procedure of this study takes place in four steps. In step 1, only the SF type respondents selected for this study were extracted through MBTI analysis. In step 2, they were divided into three hierarchies for the AHP analysis and each element was arranged. In step 3, the AHP analysis was converted to a Fuzzy-AHP number using the trigonometric centroid method. This was to eliminate the ambiguity of the response by converting into a fuzzy number even if data consistency was maintained with CI value below 0.1. In step 4, the number of converted 2-layer and 3-layer was combined to derive the priority when the final handset is selected. Results - First, the highest importance among the four items in the second tier was the terminal function item, followed by brand, price, and design item. Second, in the third tier, the highest importance was level of after-sales service, followed by device price, processing speed, ease of use, usefulness, and rate system. Third, the arithmetic average of the determinant of the fuzzy function showed that processing speed, ease of use and usefulness in the function item, level of after-sales service in the brand item, and device price in the price item were the five most important factors among 16 choice factors. Conclusions - First, there will be a change in the consumption patterns of consumers who have compared distributors and dealers to purchase handsets with more subsidies. Second, it is highly likely that people will purchase new handsets only when they need to change their devices because they can not receive subsidies by switching phone brands any more.

• Korean journal of food and cookery science
• /
• v.4 no.1
• /
• pp.75-85
• /
• 1988

This survey was conducted to investigate about purchasing, use and management of cooking oil, and the intake amounts of each food and fats & oils from each food on 296 housewives in a big city, medium and small city, farming village, fishing village, and mountain village from June 5 to July 20 in 1987. The percentage and $x^2$-test were used in data analysis and the arithmetic mean of the gross intake divided by the total subjects gave the intake amounts per capita per day. The results of this study are as following; 1. Purchasing and keeping of cooking oil. The reading ratio of label in purchasing cooking oil was high among housewives of cities and highly educated housewives. There were dissatisfactions about quality (46.7%), price (33.7%), and packing (19.5%) after purchasing cooking oil. Cooking oil was being kept mainly in glasses (64.7%) or in synthetic plastics (31.5%), and also in dark & cool places. 2. Use and refining of cooking oil. More housewives (70.6%) kept cooking oil used once in a different container after filtering. The housewives re-using used oil after adding new oil to it were only 30.0%. There were a lot of housewives frying foods twice or three times in the same oil. 3. Intake of fats & oils and foods containing fats & oils. Average intake amounts of food containing fats & oils per person per day was 6.85g in fats & oils, 42.96g in meat & its products, 95.13g in fishes & shellfishes, 22.89g in eggs, 60.69g in legumes & its products, 61.00g in milk & milk products, 4.22g in seeds & nuts, and 9.36g in instant noodles. Average intake amounts of fats & oils per person per day taken from these foods was 6.4g from fats & oils, 2.3g from meat & its products, 4.3g from fishes & shellfishes, 2.7g from eggs, 3.0g from legumes & its products, 2.5g from milk & milk products, 1.8g from seeds & nuts, and 1.7g from instant noodles.