• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제26권1호
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• pp.23-48
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• 2022

In this paper, we provide predictive models for the market price of fruits, and analyze the performance of each fruit price predictive model. The data used to create the predictive models are fruit price data, weather data, and Korea composite stock price index (KOSPI) data. We collect these data through Open-API for 10 years period from year 2011 to year 2020. Six types of fruit price predictive models are constructed using the LSTM algorithm, a special form of deep learning RNN algorithm, and the performance is measured using the root mean square error. For each model, the data from year 2011 to year 2018 are trained to predict the fruit price in year 2019, and the data from year 2011 to year 2019 are trained to predict the fruit price in year 2020. By comparing the fruit price predictive models of year 2019 and those models of year 2020, the model with excellent efficiency is identified and the best model to provide the service is selected. The model we made will be available in other countries and regions as well.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.105-108
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• 1997

Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.

• 한국항해항만학회지
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• 제48권3호
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• pp.206-213
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• 2024

본 연구는 지정학적 위기와 해운기업 주식가격 변동성의 인과관계를 분석하였다. 해운산업은 국가간의 교역에 의해서 수요가 파생되는 국제성을 가지기 때문에, 여러 가지 종류의 불확실성과 리스크에 직면하고 있다. 이에 본 연구에서는 최근 러시아-우크라이나 전쟁 및 이스라엘-하마스 전쟁 등으로 부상하고 있는 지정학적 위기가 해운산업에 미치는 영향을 분석하고자 한다. 특히, 지정학적 불확실성이 해운기업의 주식가격 변동성에 미치는 영향에 대해서 분석함으로서 이에 대한 시사점을 제공하고자 한다. 2000~2023년 기간 동안 한국거래소에 상장된 해운기업 5개사의 주식가격 변동성과 지정학적 위기 지수의 관계를 벡터자기회귀모형 기반의 인과성을 검정한 결과, 다음과 같은 결론이 도출되었다. 첫째, 지정학적 위기가 고조될수록 해운기업 주식가격의 변동성은 확대되었다. 둘째, 외교적 마찰로 인한 지정학적 위기보다는 실제 발생하는 이벤트에 의한 지정학적 위기의 영향이 통계적으로 유의하였다. 마지막으로, 지정학적 위기로 인한 주식가격 변동성의 확대는 주로 벌크부문에 나타났다.

• 국제지역연구
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• 제20권3호
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• pp.123-144
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• 2016

This paper investigates the linkages between returns both in foreign exchange and stock markets, and uncertainties in two markets using daily data for the period of 16 July 2004 to 30 June 2014 in Nepalese economy. Four hypotheses are tested about how uncertainty influences the stock index and exchange rates. From the empirical results, a bivariate EGARCH-M model is the best to explain the volatility in the two markets. There is a negative relationship from the exchange rates return to stock price return. Empirical results do provide strong empirical confirmation that negative effect of stock index uncertainty and positive effect of exchange rates uncertainty on average stock index. GARCH-in-mean variables in AR modeling are significant and shows that there is positive effect of exchange rates uncertainty and negative effect of stock index uncertainty on average exchange rates. Stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainly in the foreign exchange market. The effect of the last period's shock, volatility is more sensitive to its own lagged values.

• 응용통계연구
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• 제34권5호
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• pp.745-760
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• 2021

금융시장에서 주식 가격 자체 또는 가격의 방향성에 대한 예측은 오래 전부터 관심의 대상이 되어 왔기에 여러 방면에서 다양한 연구가 이어져 왔다. 특히 1960년대에 들어서며 많은 연구가 진행되었고 예측가능성에 대해 찬반의 의견들이 있었는데, 1970년대에 나타난 효율적 시장 가설이 지지를 받으면서 주식 가격의 예측은 불가능하다는 의견이 주를 이루었다. 그러나 최근 기계학습 등 예측기술의 발달로 인해 주식 시장에서 미래를 예측해 보려는 새로운 시도가 이어져, 주식시장의 효율성을 부정하고 높은 예측력을 주장하는 연구들이 등장하고 있다. 이 논문에서는 과거 연구들을 평가방법 별로 정리하고, 새로운 주장의 신빙성을 확인하기 위해 이차판별분석, support vector machine, random forest, extreme gradient boost, 심층신경망 등 다양한 기계학습 모형을 적용하여 한국유가증권시장에 상장된 종목 중 삼성전자, LG화학, Naver 주식 가격의 방향성을 예측해보았다. 이때, 널리 사용되는 기술적 지표 변수들과 더불어 price earning ratio, price book-value ratio 등 회계지표를 활용한 변수와, 은닉마르코프모형의 출력값 변수를 사용하였다. 분석결과, 이번 연구의 조건 하에서는 통계적으로 유의미한 예측력을 제시하는 모형이 존재하지 않았고, 현 시점에서 단기 주가 방향성의 예측은 어렵다고 판단되었다. 비교적 단순한 이차판별분석 모형과 회계지표를 활용한 변수를 추가한 모형이 상대적으로 높은 예측력을 보였다는 점에서, 복잡한 모형을 시도하기 보다는 주식 가격에 대한 투자자들의 의견 및 심리가 반영될 수 있는 다양한 변수를 개발하여 활용한다면 향후 유의미한 예측이 가능할 수도 있을 것이다.

• East Asian Economic Review
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• 제19권3호
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• pp.275-322
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• 2015

The key objective of this study is to investigate the return and volatility spillover effects among stock market, credit default swap (CDS) market and foreign exchange market for three countries: Korea, the US and Japan. Using the trivariate VAR BEKK GARCH (1,1) model, the study finds that there are significant return and volatility spillover effects between the Korean CDS market and the Korean stock market. In addition, the return spillover effects from foreign exchange markets and the US stock market to the Korean stock market, and the volatility spillover effect from the Japanese stock market to the Korean stock market are both significant.

• 응용통계연구
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• 제21권5호
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• pp.755-763
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• 2008

This paper approaches the problem of option pricing in an incomplete market, where the underlying asset price process follows a compound Poisson model. We assume that the price process follows a compound Poisson model under an equivalent martingale measure and it converges weakly to the Black-Scholes model. First, we express the option price as the expectation of the discounted payoff and expand it at the Black-Scholes price to obtain a pricing formula with three unknown parameters. Then we estimate those parameters using the market option data. This method can use the option data on the same stock with different expiration dates and different strike prices.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.913-921
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• 2021

The objective of the study is to investigate the impact of the COVID-19 pandemic on Saudi Arabia stock market. The study relied on the data of the daily closing stock market price index Tadawul All Share Index (TASI), and the number of daily cases infected with COVID-19 during the period from March 15, 2020, to August 10, 2020. The study employs the Vector Auto-Regressive (VAR) model, the Impulse Response Function (IRF) and Autoregressive Conditional Heteroscedasticity (ARCH) models. The results of the correlation matrix and the Impulse Response Function (IRF) show that stock market returns responded negatively to the growth in COVID-19 infected cases during the pandemic. The results of ARCH model confirmed the negative impact of COVID-19 pandemic on KSA stock market returns. The results also showed that the negative market reaction was strong during the early days of the COVID-19 pandemic. The study concluded that stock market in KSA responded quickly to the COVID-19 pandemic; the response varies over time according to the stage of the pandemic. However, the Saudi government's response time and size of the stimulus package have played an important role in alleviating the impacts of the COVID-19 pandemic on Saudi Arabia Stock Market.

• 아태비즈니스연구
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• 제12권3호
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• pp.37-50
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• 2021

Purpose - This study aimed to examine the behavior surrounding the Initial Public Offering (IPO) event of firms within the same conglomerate and the impact of under-pricing and Return on Equity(ROE) on a firm's abnormal stock returns. Design/methodology - This study collected data from 166 South Korean Chaebols, consisting of 355 firms distributed as 202 listed on Korea Composite Stock Price Index (KOSPI) and 153 firms listed on Korean Securities Dealers Automated Quotations (KOSDAQ) from 2000 to 2020. The Capital Asset Pricing Model (CAPM) and the multiple regression analysis were hired to analyze the data. Findings - First, we found an adverse price reaction of IPO listing in the same chaebol group, and firms with higher under-pricing affect other firms' stock prices more adversely within the conglomerate. Next, we explored a negatively significant relation between ROE and the chaebol firms' stock returns during IPO events. Research implications - The novelty of this study is there are not many empirical studies on the impact of IPO within a conglomerate. So, the findings of this study contribute to the literature for analyzing stock's abnormal returns within a conglomerate.

• 수산경영론집
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• 제40권1호
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• pp.133-152
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• 2009

The purpose of this paper is to model price formation and analyze demand structures for fishes under the restriction of Korean fisheries regulations. This study suggests the model that the price of fish is formed by its quantity, expenditure, and habit persistence. In economic literature, such a fishery market demand is called the inverse demand with dynamic habit persistence. Based upon a static differential price formation model, the paper has generalized it dynamically incorporating habit persistence effects. The empirical results show that all the species have values less than one and (-) sign of price flexibilities, thus being price inflexible. The estimated habit adjustment coefficients are significant at the level of 1%. Especially, TAC species have the smaller values of them than those of other main fish species. The contribution and results are summarized as follows. First, the fishery market demand has a strong dynamic effects from habit persistence. Second, the fishery market demand structure could be analyzed in a way different from the ordinary demand analysis, which is based upon price flexibility, scale flexibility, and cross adjustment flexibility. Third, the limitation of this paper is that it ignores the increasing stock effects by catching restrictions, thus raising consumers' benefit in the future.