• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.85-93
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• 2011

Many policies, such as transit-oriented development, encouraged use of bicycle and pedestrian, reduction of green house gas (GHG) and etc., have been deployed to support transport sustainability. Although various studies regarding GHG were presented, no one has yet adequately explained the behavior of travelers. This paper proposes a GHG emission model by highlighting its sensitivity, elasticity with regard to such travel cost as travel time, travel fare, and GHG pricing, introduced to reduce the amount of GHG in transportation system. For better estimation of GHG, the proposed model adopts (1) a production-constrained gravity model and (2) the travel distance from the origin and the destination (OD). The gravity model has a merit that it considers travel pattern between OD pairs. The model was tested with an example, and the promising results confirmed its validation and applications.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.101-107
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• 2010

Among a variety of asset dynamics models in order to explain the common properties of financial underlying assets, parametric models are meaningful when their parameters are set reliably. There are two main methods from which we can obtain them. They are to use time-series data of an underlying price or the market option prices of the underlying at one time. Based on the Girsanov theorem, in the pure diffusion models, the parameters calibrated from the option prices should be partially equivalent to those from time-series underling prices. We call this phenomenon model consistency. In this paper, we verify that the two-state regime switching Black-Scholes model is superior in the sense of model consistency, comparing with two popular conventional models, the Black-Scholes model and Heston model.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.513-522
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• 2014

Using the assumption that the price of a stock follows a geometric Brownian motion with constant volatility, Black and Scholes (BS) derived a formula that gives the price of a European call option on the stock as a function of the stock price, the strike price, the time to maturity, the risk-free interest rate, the dividend rate paid by the stock, and the volatility of the stock's return. However, implied volatilities of BS method tend to depend on the stock prices and the time to maturity in practice. To address this shortcoming, we estimate the implied volatility function as a function of the strike priceand the time to maturity for data consisting of the daily prices for KOSPI200 call options from January 2007 to May 2009 using support vector regression (SVR), the multiple additive regression trees (MART) algorithm, and ordinary least squaress (OLS) regression. In conclusion, use of MART or SVR in the BS pricing model reduced both RMSE and MAE, compared to the OLS-based BS pricing model.

• Journal of Fashion Business
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• v.20 no.4
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• pp.172-188
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• 2016

This study is conducted in grades 4, 5, and6 of Elementary schools located in Seoul. The results would be recognized by the Consumer Behavior Survey and the Use of Beauty. Students in the higher grades of elementary schools are exposed to beauty products for the first time. This is a crucial age, where they start becoming interested in their appearance. This behavior is being exploited to increase the desire to use beauty products. Although the initial use is self-motivated, choosing a quality product is highly influenced by peers, reasonable pricing, and internet impact. The higher the grade of the elementary school, we observed an increase in this trust and impulsiveness in the consumer behavior. More than 2 million students spent considerable amounts of money, and showed trends of consumer behavior of the impulsive type. The results of this study can provide a significant base to further study trends of beauty usage in higher grades of elementary schools, and give an indication of the consumer behavior based on the beauty culture and use of health products.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.563-585
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• 2008

This paper presents how to improve the efficiency and accuracy in the pricing and sensitivity evaluation for derivatives, since the need for the evaluation of complicated derivatives is increased. The Monte Carlo(MC) simulation using the quasi random number instead of pseudo random number can improve the elapsed time and accuracy for the valuation of European-type derivatives. However, the quasi MC simulation method has its limit for applying it in the multi-dimensional case such as American-type and path-dependent options due to the increased correlation between dimensions as the dimension of random numbers is increased. In order to complement this problem, we develop a modified method in which correlation values are controlled to be below a pre-specified value. Thus, this method is applicable for the pricing of either derivatives ill which underlying assets or risk factors are several or derivatives having path-dependent or early redemption property. Furthermore, we illustrate that it is important to take an appropriate grid interval for the use of finite difference method(FDM) by applying the FDM to one example of non-symmetrical butterfly spreads.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.1
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• pp.25-36
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• 2018

This paper presents a new airport slot allocation model that uses AIP model to balance the use of airport slots within existing capacity based on the limitation of capacity expansion of airport slots. This new model is called a 'balanced airport slot allocation model', which integrates the airport facility usage system, which is applied independently without linkage, with the airport slot allocation system, introducing the market logical characteristic of 'administered incentive pricing. In this paper, we propose a new proposal to dramatically change the airport slot allocation system in the current situation where the expansion of facilities is limited in the urgent problem of the airport slot shortage, and it is necessary to balance the airport slot allocation. Airline paying for the use of an airport slot can determine the slot of the desired time slot based on the costs incurred by differentiating in the new airport slot allocation model. This is a system that allows the airlines that are willing to pay a lot of money in the market to use preferred airport slots.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.7
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• pp.995-1003
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• 2000

This study examined the role of apparel merchandisers’in Korea. Data were collected by interviewing 7 apparel merchandisers who had worked for major apparel manufacturers. The interviews were analyzed by use of chronologically sequenced events. Korean apparel merchandisers take part in planning and production of the merchandise, sales management, and promotion. Merchandisers’activities related to merchandise planning were as follows: analysis of fashion trend and market, concept evolvement, planning of assortment and volume assortment, time table set up, color pallette decision, fabrication, line adoption, pricing, line preview, production planning, and placing order of materials. Merchandisers’activities related to apparel production were planning and controlling production and consolidation. In sales, merchandisers analyze retail sales and control inventory by reorder or conducting markdown sale. In relation to promotion, apparel merchandisers monitor merchandise advertisement, and educate salesman.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.589-596
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• 2011

The conditional autoregressive value at risk (CAViaR) model is useful for risk management, which does not require the assumption that the conditional distribution does not vary over time but the volatility does. But it does not provide volatility forecasts, which are needed for several important applications such as option pricing and portfolio management. For a variety of probability distributions, it is known that there is a constant relationship between the standard deviation and the distance between symmetric quantiles in the tails of the distribution. This inspires us to use a support vector quantile regression (SVQR) for volatility forecasts with the distance between CAViaR forecasts of symmetric quantiles. Simulated example and real example are provided to indicate the usefulness of proposed forecasting method for volatility.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.1
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• pp.19-30
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• 2019

In this paper, we develop an accurate explicit finite difference method for the two-dimensional Black-Scholes equation with a hybrid boundary condition. In general, the correlation term in multi-asset options is problematic in numerical treatments partially due to cross derivatives and numerical boundary conditions at the far field domain corners. In the proposed hybrid boundary condition, we use a linear boundary condition at the boundaries where at least one asset is zero. After updating the numerical solution by one time step, we reduce the computational domain so that we do not need boundary conditions. To demonstrate the accuracy and efficiency of the proposed algorithm, we calculate option prices and their Greeks for the two-asset European call and cash-or-nothing options. Computational results show that the proposed method is accurate and is very useful for nonlinear boundary conditions.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.859-870
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• 2018

Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.