• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.253-255
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• 2015

Crude oil is the world's most actively traded commodity and also one of the most significant resources in the world. The impact of oil price volatility has great influences on macroeconomic activities. This presentation is to review and analyze the oil price fluctuation and to examine the effects especially on the offshore oil production and thereafter to look over the challenges and opportunities in this sector focusing on the petroleum logistics.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.93-104
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• 2024

China is playing more predominant role in the liquefied natural gas (LNG) market worldwide and LNG import price is subject to various factors both at home and abroad. Nevertheless, previous studies rarely heed a multiple of factors. A time-varying parameter factor augmented vector auto-regression (TVP-FAVAR) model is adopted to discover the determinants of China's LNG import price and their dynamic impacts from January 2012 to December 2021. According to the findings, market fundamentals have a greater impact on the import price of natural gas in China than overall economic demand, financial considerations, and world oil prices. The primary determinants include domestic gas consumption, consumer confidence and other demand-side information. Then, there are diverse and time-varying spillover effects of the four common determinants on the volatility of China's LNG import price at different intervals and time nodes. The price volatility is more sensitive and long-lasting to domestic natural gas pricing reform than other negative shocks such as the Sino-US trade war and the COVID-19 pandemic. The results in this study further proves the importance of domestic natural gas market liberalization. China ought to do more to support the further marketization of natural gas prices while working harder to guarantee natural gas supplies.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.93-104
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• 2022

In forecasting realized volatility of the major US stock price indexes (S&P 500, Russell 2000, DJIA, Nasdaq 100), internet search volume reflecting investor's interests and implied volatility are used to improve forecast via a deep learning method of the LSTM. The LSTM method combined with search volume index produces better forecasts than existing standard methods of the vector autoregressive (VAR) and the vector error correction (VEC) models. It also beats the recently proposed vector error correction heterogeneous autoregressive (VECHAR) model which takes advantage of the cointegration relation between realized volatility and implied volatility.

• The Journal of Industrial Distribution & Business
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• v.9 no.10
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• pp.73-82
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• 2018

Purpose - Unstable vegetable prices have been one of the major concerns in Korean agricultural and food marketing system. The Korean government has implemented a number of policy instruments, including government purchasing programs in order to alleviate fluctuations in vegetable prices. The economic impact of policy instruments has been assessed based on the average monthly price change rate before and after the implementation of the policy. However, this approach failed to provide a net impact of policy measures on price stabilization in the vegetable markets, as policy impacts could not be successfully distinguished from other effects on price changes in the vegetable market. The purpose of this study is to evaluate the net impact of the government purchasing program on the price volatility of dried red pepper which is considered one of the major vegetables in Korea. Research design, data, and methodology - This study develops a monthly dynamic partial equilibrium model of Korean dried red pepper market. Behavioral equations in the model were estimated by OLS and synthetic method based on the annual and monthly time series data from 1993 to 2015. The model is first simulated to yield actual dried red pepper market conditions in 2015 as a baseline and then compared it to the scenario assuming that there were no government purchases of dried red pepper in 2015. Results - According to the ex-post scenario analysis using the developed model, without the government procurements in 2015, the average monthly price change rate and the value of coefficient of variation of dried red pepper in 2015 would be respectably 7.9 percent and 0.10. It is relatively higher than the actual average monthly price change rate and the value of coefficient of variation of dried red pepper in 2015 which were respectively 1.7 percent and 0.06. Conclusions - The ex-post simulation results in this study shows that if there were no government purchases of dried red pepper in 2015, the dried red pepper market would have had much higher volatile price movements. The results of this study would provide useful information for future price stabilization policy of vegetable markets in Korea.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.49-67
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• 2006

This study examines whether won/dollar futures have price discovery function and volatility spillover effect or not, using intraday won/dollar futures prices, volumes, and spot rates for the interval from March 2, 2005 through May 30, 2005. Futures prices and spot rates are non-stationary, but there is the cointegration relationship between two time series. Futures returns, spot returns, and volumes are stationary. Asymmetric effects on volatility in futures returns and spot returns does not exist. Analytical results of mean equations of the BGARCH-EC (bivariate GARCH-error correction) model show that the increase of futures returns raise spot returns after 5 minutes, which implies that futures returns lead spot returns and won/dollar futures have price discovery function. In addition, the long-run equilibrium relationship between the two returns could help forecast spot returns. Analytical results of variance equations indicate that short-run innovations in the futures market positively affect the conditional variances of spot returns, that is, there is the volatility spillover effect in the won/dollar futures market. A dummy variable of volumes does not have an effect on two returns but influences significantly on two conditional variances.

• Land and Housing Review
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• v.12 no.3
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• pp.27-37
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• 2021

This paper empirically examined the relationship between the housing market and the stock market to investigate the price and the asymmetric volatility spillover effects. The monthly housing price index and the monthly KOSPI were used for analysis. This research employed the EGARCH model. The analysis period was from January 1986 until June 2021 with periodization centered on the Asian Financial Crisis: before and after the crisis - the end of December 1997. The EGARCH model allows analysis of 'good news' and 'bad news' in understanding volatility. The price spillover effect was observed one way from the stock market to the housing market. On the contrary, the spillover effect was not found from the housing market to the stock market. The empirical evidence suggests that there are price and asymmetric volatility effects in the entire period of analysis in both housing and the stock markets. In the housing market, the negative effects of information were found pre-financial crisis while the positive effects, in other periods. However, in the stock market, the negative effects of information were found in the pre- and post-financial crisis periods. This means that the housing market is more affected by 'good news' than 'bad news' when information spreads to the markets while the stock market is more affected by 'bad news' than 'good news'. It is of significance to discover the variable returns by different information.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.3
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• pp.5-16
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• 2014

This study aims to examine the dynamics of price changes and trading volume of Kuala Lumpur Options and Financial Futures Exchange (KLOFFE) from 2000 to 2008. With augmented analysis, our results support two hypotheses. First, under information spillover, our findings support noise traders' hypothesis as the time span for variance of past trading volume to cause variance of current return is found to be asymmetric under bull and bear markets. Second, looking at the dynamic relation between volume and volatility of price changes, our findings support Liquidity-Driven Trade hypothesis as past trading volume and subsequent volatility of return exhibit positive correlation. In terms of investors' behavior in response to the news, we find that investors are more risk taking in bull market and more risk reverse in bear market. Our study suggests that investors should adjust their strategy in the futures market in a dynamic manner as the time span of new information arrival is not consistent. Also, uninformed investors with information asymmetry should expect noninformational trading from informed investors to establish their desired positions for better liquid position.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.59-66
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• 2023

The Golden Cross is commonly seen as a buy signal in financial markets, but its reliability for predicting stock price movements is limited due to market volatility. This paper introduces a time-invariant approach that considers the Golden Cross as a singular event. Utilizing LSTM neural networks, we forecast significant stock price changes following a Golden Cross occurrence. By comparing our approach with traditional time series analysis and using a confusion matrix for classification, we demonstrate its effectiveness in predicting post-event stock price trends. To conclude, this study proposes a model with a precision of 83%. By utilizing the model, investors can alleviate potential losses, rather than making buy decisions under all circumstances following a Golden Cross event.

• Bulletin of the Korean Mathematical Society
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• v.46 no.2
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• pp.209-227
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• 2009

We examine a unified approach of calculating the closed form solutions of option price under stochastic volatility models using stochastic calculus and the Fourier inversion formula. In particular, we review and derive the option pricing formulas under Heston and correlated Stein-Stein models using a systematic and comprehensive approach which were derived individually earlier. We compare the empirical performances of the two stochastic volatility models and the Black-Scholes model in pricing KOSPI 200 index options.

• The Journal of Information Systems
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• v.29 no.1
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• pp.289-301
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• 2020

Purpose This study analyzes whether Internet search of cryptocurrency has a causal relationship to return and volatility of cryptocurrency. Design/methodology/approach Google Trend was used as a measure of the level of Internet search, and the parametric tests of Granger causality in the 1st moment and the 2nd moment were adopted as the analysis method. We used Bitcoin's dollar-based price, which is the No. 1 market value among cryptocurrency. Findings The results showed that the Internet search measured by Google Trends has a causal relationship to cryptocurrency in both average and volatility, while there is a difference in causality and its degree according to the search area and category that Google Trend user should set. Because the Granger causality is based on the improvement of prediction, the analysis results of this study indicate that Internet search can be used as a leading indicator in predicting return and volatility of cryptocurrency.