• The Journal of Industrial Distribution & Business
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• v.9 no.10
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• pp.83-89
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• 2018

Purpose - The purpose of this study examines when the optimism impact on financial asset price forecasting and the boundary condition of optimism in the financial asset price forecasting. People generally tend to optimistically forecast their future. Optimism is a nature of human beings and optimistic forecasting observed in daily life. But is it always observed in financial asset price forecasting? In this study, two factors were focused on considering whether the optimism that people have applied to predicting future performance of financial investment products (e.g., mutual fund). First, this study examined whether the degree of optimism varied depending on the direction of the prior price trend. Second, this study examined whether the degree of optimism varied according to the forecast period by dividing the future forecasted by people into three time horizon based on forecast period. Research design, data, and methodology - 2 (prior price trend: rising-up trend vs falling-down trend) × 3 (forecast time horizon: short term vs medium term vs long term) experimental design was used. Prior price trend was used between subject and forecast time horizon was used within subject design. 169 undergraduate students participated in the experiment. χ² analysis was used. In this study, prior price trend divided into two types: rising-up trend versus falling-down trend. Forecast time horizon divided into three types: short term (after one month), medium term (after one year), and long term (after five years). Results - Optimistic price forecasting and boundary condition was found. Participants who were exposed to falling-down trend did not make optimistic predictions in the short term, but over time they tended to be more optimistic about the future in the medium term and long term. However, participants who were exposed to rising-up trend were over-optimistic in the short term, but over time, less optimistic in the medium and long term. Optimistic price forecasting was found when participants forecasted in the long term. Exposure to prior price trends (rising-up trend vs falling-down trend) was a boundary condition of optimistic price forecasting. Conclusions - The results indicated that individuals were more likely to be impacted by prior price tends in the short term time horizon, while being optimistic in the long term time horizon.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.343-352
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• 2022

We present the user-friendly graphical user interface design and implementation of Monte Carlo simulation (MCS) for computing option price of the four-underlying asset step-down equity linked securities (ELS) using the Android platform. The ELS has been one of the most important and influential financial products in South Korea. Most ELS products are based on one-, two-, and three-underlying assets. However, currently there is a demand for higher coupon payment from ELS products because of the increased interest rate in financial market. In order to allow the investors to have higher coupon payment, it is necessary to design a multi-asset ELS such as four-asset step-down ELS. We conduct the computational experiments to demonstrate the performance of the Android platform for pricing four-asset step-down ELS. Furthermore, we perform a comparison test with a three-asset step-down ELS.

• Journal of the Korean Society of Costume
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• v.54 no.6
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• pp.1-12
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• 2004

Price is one of the most important components of marketing mix. For consumers, price is an always-existing cue and definite evaluation criteria. However, information on price is meaningful only when it is perceived. Sources of price perception can be the actual retail price at the selling point, the internal reference price expected by consumers for a certain clothing product, and the external reference price advertised by marketer such as the price before mark-down. The purpose of this study was to investigate the influence of internal reference price on consumers' purchasing process of clothing products. A questionnaire including clothing stimuli was developed in order to assess consumers' internal reference price level. Usable data from 680 adult female urban residents were used for data analysis. Results indicated that consumers with relatively lower internal reference price tend to react low-price focused external reference price and use discount stores and unit price promotions. Consumers with relatively higher internal reference price advertisement are likely to have higher level of education, tend to infer price information to higher quality or prestige of products, and purchase clothing with regular retail price or coupons.

• The Journal of Korean Society for School & Community Health Education
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• v.17 no.2
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• pp.31-44
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• 2016

Objectives: This study was aimed at finding out the current smoking situation of workers in the field of railroad electricity and vehicles and changes of their smoking behaviors after the raise of price of tobacco in 2015. Methods: With a self-administered questionnaire conducted from February 9 to March 6 2015, one-way ANOVA and crosstabs(PASW Statistics Ver. 18.0) were conducted on the data of 626 people. Results: As the result, the smoking rate was 39.1% and 90.5% of the smoking experienced group showed some changes including cutting down on smoking due to raise of price of tobacco. Factors related to smoking included stress, the number of times of drinking, awareness of harmfulness of smoking, the number of days with hard exercise per week and the marital status. Conclusion: Therefore, it is assumed that there is necessity of top-down intervention using these factors to cut down the smoking rate.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

• Journal of the Korea Fashion and Costume Design Association
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• v.7 no.3
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• pp.145-156
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• 2005

The purpose of this study was to identify the characteristics of export clothing articles in Korea. For the purpose, the proportion and unit price of each export clothing articles were analyzed to each important market. The results of the study were as follows : First, on the proportional aspect, to all world market, SITC 845(Articles of apparel, of textile fabrics, n.e.5.), 842(Women's clothing, of textile font knittedabrics), and 841 (Men's clothing of textile fabrics, not knitted), 844(Women's clothing, of textile, knitted or crocheted) and 846(Clothing accessories, of textile fabrics), 848(Articles of apparel, clothing access., excluding textile), 843(Men's or boy's clothing, of textile, knitted, crocheted.) in order were in large exported, after the mid-1990's. To each important market, the proportion of export clothing articles was varied. Second, on the unit price aspect, to all world market, the unit price of export clothing articles went down slightly. For each item, 844(Women's clothing, of textile, knitted or crocheted) went up a little, 843(Men's or boy's clothing, of textile, knitted, croche.) and 845(Articles of apparel, of textile fabrics, n.e.s.) went down a little, 841(Men's clothing of textile fabrics, not knitted), 842(Women's clothing, of textile fabrics), 846(Clothing accessories, of textile fabrics) and 848(Articles of apparel, clothing access., excluding textile) went down greatly. The unit price to industrialized countries, newly industrializing countries, developing countries in order was high, reflecting the developing stage of each nation's.

• Korean Journal of Organic Agriculture
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• v.25 no.1
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• pp.23-35
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• 2017

The objective of this study is to analyze a price of environment-friendly and conventional rice with POS data. And we estimate the value of environment-friendly's certification with hedonic price model. In case of price level, organic and pesticide-free rice is higher than conventional rice, 22.5% and 10.6%, respectively. In contrast, price variation of conventional rice is higher environment-friendly rice. The value of organic and pesticide are 839.5 Won and 313.7 Won, respectively. As time goes by, the certification's value goes down in environment-friendly rice. In particular, price level and certification's value of pesticide-free rice is similar with conventional rice. The results of this study show that price of the environment-friendly rice is not higher than expected. Therefore it is necessary to establish a new marketing and promotion strategies for environment-friendly rice.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.51
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• pp.133-158
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• 2011

The purpose of this study is to analyze one of CIETEC(China International Economic and Trade Arbitration Commission) Award on the dispute arising from Cotton Sale Contact which deals with damages and reduction of the price. Especially this case focused on the effect of reduction of the price to damages. The purpose of damages is to place the aggrieved party in as good a position as if the other party had properly performed the contract. So court costs and attorney's fee should be regarded as the loss, because these are caused by consequence of the breach which is recoverable. With the same reason, overpaid taxes should also regard as the loss. It is not impossible, however, to claim both damages and reduction of the price for same loss at the same time. It means buyer could not claim damages for the same loss, once he already claimed reduction of the price. So Korean companies should consider which remedy is proper to himself under the circumstances. He should choose reduction of the price when market price is down. In case of rising market price, he should consider follows: first, it is better to choose damages based on current price(Art.76), if upswing of non-conformity price is higher then upswing of market price. Second, it is better to choose general rule for measuring damages(Art.74), if upswing of market price is higher then upswing of non-conformity price.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.115-130
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• 1999

The price structure of housing market varies depending upon market price policy rather than low or high price policy because of IMF. The object of this study is to develop an analysis system for analyzing housing market and its demand. The analysis system consists of four major categories: macro index analysis, market decision analysis, housing market analysis, and consumer analysis. We model each category by using a variety of techniques such as generalized linear model, categorical analysis, bubble analysis, drill-down analysis, price sensitivity meter analysis, optimum price index analysis, profit index measurement analysis, correspondence analysis, conjoint analysis, and multidimensional scaling analysis. Seoul apartment data is analyzed to demonstrate the practical usefulness of the system.

• Journal of the Korean Professional Engineers Association
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• v.39 no.3 s.186
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• pp.32-35
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• 2006

The recent speculation fever in Kangnam have been cooled down by the August 31 heavy taxation tool for curbing speculators. Another March 30 real estate control equipped with high capital gains tax up to 50% was targeting reconstruction projects of dilapidated apartment complexes mostly inside of Kangnam area. The shortage of larger unit supply with its high demand results in price polarization problem. It makes higher price for larger units and less price for smaller units, and therefore higher priced home owners become richer and lower priced home owners become poorer. To avoid the polarization problem and anther probable price hikes in the near future, it may be suggested to supply quality homes by loosening the tight rules for the apartment reconstruction project, and thereby kangnam housing price stabilization can be achieved.