• Culinary science and hospitality research
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• v.22 no.3
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• pp.212-223
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• 2016

The purpose of this study is to verify information spillover effects using returns of macroeconomic variables and hotel leisure stock index daily data from January 4, 2000 to December 30, 2015. The findings and implications of the research can be summarized as follows. First, based on time-varying AR(1)-GARCH(1,1) models no evidence of statistically significant conditional mean and volatility spillover effects from returns of macroeconomic variables on the hotel leisure stock index was observed. In addition, no evidence of price volatility spillover from macroeconomic variables on the hotel leisure market was observed. Second, it was discovered that there exists a significantly negative relationship between the return of ER and hotel leisure stock prices, but a positive relationship between the KOSPI and hotel leisure stock prices. Finally, the study also found that was a significantly positive relationship between the volatility of DUB and hotel leisure market, and an adversely negative relationship between the volatility of ER and hotel leisure market. The results of this study are expected to contribute by providing useful information for investment strategies, as well as for risk management for investors and managers.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.135-144
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• 2017

This study is to identify the growth rate and volatility of logistics related firms in the stock market. To do this, we used monthly data for 197 years from June 2000 to October 2016 by selecting KOSPI and Transport & Storage(T&S), KOSDAQ, Transportation(TRANS) index. The purpose of this study is to compare the T&S and TRANS stock index returns with the KOSPI and KOSDAQ index. And we are to judge whether the development potential of the logistics industry and the value of the investment of related companies in the future is high. For this purpose, we will analyze the basic statistics, correlation and growth rate of each index, and compare T&S and TRANS with market returns. Analysis result, for the past 197 months logistics related T&S and TRANS have been higher than market returns. The correlation was highly related to TRANS and T & S in KOSPI, but it was not related to KOSDAQ. TRANS represents high risk and high return, while KOSDAQ represents high risk and low return market. TRANS is considered to be an efficient investment. We expect the future development of logistics related industries and T & S and TRANS to show a high rate of increase compared to the market returns.

• Management & Information Systems Review
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• v.37 no.4
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• pp.63-74
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• 2018

Recently, in the asset management industry, the smart beta strategy, which has an intermediate nature between passive and active strategies, is attracting attention. In this smart beta strategy, value, momentum, low volatility, and quality index are widely used. In this study, we analyzed the quality index which is not clear and complicated to calculate. According to the MSCI methodology, the quality index was calculated using three variables: return on equity, debt to equity, and earnings variability. In addition, we use the index using only return on equity variable, the index using only two variables of return on equity and debt to equity, and the KOSPI index as comparison targets for the quality index. In order to evaluate the performance of the indices used in the analysis, the arithmetic mean return, the coefficient of variation, and the geometric mean return were used. In addition, Fama and French (1993) model, which is widely used in related studies, was used as a pricing model to test whether abnormal returns in each index are occurring. The results of the empirical analysis are as follows. First, in all period analysis, quality index was the best in terms of holding period returns. Second, the quality index performed best in the currency crisis and the global financial crisis. Third, abnormal returns were not found in all indices before the global financial crisis. Fourth, in the period after the global financial crisis, the quality index has the highest abnormal return.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1231-1242
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• 2019

This paper presents a two-dimensional attention-based long short-memory (2D-ALSTM) model for stock index prediction, incorporating input attention and temporal attention mechanisms for weighting of important stocks and important time steps, respectively. The proposed model is designed to overcome the long-term dependency, stock selection, and stock volatility delay problems that negatively affect existing models. The 2D-ALSTM model is validated in a comparative experiment involving the two attention-based models multi-input LSTM (MI-LSTM) and dual-stage attention-based recurrent neural network (DARNN), with real stock data being used for training and evaluation. The model achieves superior performance compared to MI-LSTM and DARNN for stock index prediction on a KOSPI100 dataset.

• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.41-52
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• 2010

Even though REITs (Real Estate Investment Trusts) are listed on the stock market, REITs have characteristics that allow them to invest in real estate and financing for real estate development. Therefore REITs is related with stock market and construction business and real estate business. Using time-series analysis, this study analyzed REITs in relation to construction businesses, real estate businesses, and the stock market, and derived influence factor of REITs. We used the VAR (vector auto-regression) and the VECM (vector error correction model) for the time-series analysis. This study classified three steps in the analysis. First, we performed the time-series analysis between REITs and construction KOSPI(The Korea composite stock price index) and the result showed that construction KOSPI influenced REITs. Second, we analyzed the relationship between REITs and construction commencement area of the coincident construction composite index, office index and housing price index in real estate business indexes. REITs and the housing price index influence each other, although there is no causal relationship between them. Third, we analyzed the relationship between REITs and the construction permit area of the leading construction composite index. The construction permit area is influenced by REITs, although there is no causal relationship between these two indexes, REITs influenced the stock market and housing price indexes and the construction permit area of the leading composite index in construction businesses, but exerted a relatively small influence in construction starts coincident with the composite office indexes in this study.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.387-394
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• 2016

The volatility in the stock market responds differently to information types. That is, the asymmetric volatility exists in the stock market which responds more to unexpected negative returns due to bad news than unexpected positive returns due to good news. This paper examines the asymmetric response of the volatility of KOSPI, large-cap, middle-cap, and small-cap indices returns which is announced in Korea exchange (KRX) by using the MA-GJR model and the MA-EGARCH model. According to empirical analyses, it shows that the asymmetric response of volatility exists in all indices regardless of volatility estimation models and the degree of the asymmetric volatility response of the small-cap index returns is greater than that of the large-cap index returns. Moreover, this results also observed robustly during the period of both before and after the global financial crisis.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1061-1073
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• 2009

Stock price index option investing is a scientific investment method and various index and investment strategies have been developed. The purpose of this study is to apply the variety of option investment strategies that have been introduced in the market and validate them using past option trading data. Option data was based on an actual stock exchange market tick data ranging from September 2001 to January 2007. Visual Basic is used to propose an option back-testing model. Validation process was carried out by transferring the tick data into ten-minute intervals and empirically analyzed. Furthermore, most option-related strategies have been applied to the model, and the usefulness of each strategies can be easily evaluated. As option investment has high leverage followed by high risks and profit, the optimal option investment strategy should be used according to the market condition at the time to make stable profit with minimum risk.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.379-392
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• 2005

The size of state in Korea is like Israel, this country's venture capital is ruled by government. This venture capital's character is below: the concentration on research of venturer affect positively at quality of products. This paper lies with venture capital's risk character & performance. The results show that Korean venture capitals have lager unsystematic risk than systematic risk, which implies they specialize in specific business and/or regional areas instead of diversification. The Sharpe & Jensen measures reveal that the performances of Korean venture capitals are very low relative to even the market portfolio(Kospi) and Kosdaq Venture Index. Contrary to this, Venture firm's performance according to Entrepreneurship will cause to push up stock price.

• Journal of Distribution Science
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• v.13 no.5
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• pp.53-60
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• 2015

Purpose - The purpose of this paper is to shed light on the importance of the slope and curvature of the volatility curve implied in option prices in the KOSPI 200 options index. A number of studies examine the implied volatility curve, however, these usually focus on cross-sectional characteristics such as the volatility smile. Contrary to previous studies, we focus on time-series characteristics; we investigate correlation dynamics among slope, curvature, and level of the implied volatility curve to capture market information embodied therein. Our study may provide useful implications for investors to utilize current market expectations in managing portfolios dynamically and efficiently. Research design, data, and methodology - For our empirical purpose, we gathered daily KOSPI200 index option prices executed at 2:50 pm in the Korean Exchange distribution market during the period of January 2, 2004 and January 31, 2012. In order to measure slope and curvature of the volatility curve, we use approximated delta distance; the slope is defined as the difference of implied volatilities between 15 delta call options and 15 delta put options; the curvature is defined as the difference between out-of-the-money (OTM) options and at-the-money (ATM) options. We use generalized method of moments (GMM) and the seemingly unrelated regression (SUR) method to verify correlations among level, slope, and curvature of the implied volatility curve with statistical support. Results - We find that slope as well as curvature is positively correlated with volatility level, implying that put option prices increase in a downward market. Further, we find that curvature and slope are positively correlated; however, the relation is weakened at deep moneyness. The results lead us to examine whether slope decreases monotonically as the delta increases, and it is verified with statistical significance that the deeper the moneyness, the lower the slope. It enables us to infer that when volatility surges above a certain level due to any tail risk, investors would rather take long positions in OTM call options, expecting market recovery in the near future. Conclusions - Our results are the evidence of the investor's increasing hedging demand for put options when downside market risks are expected. Adding to this, the slope and curvature of the volatility curve may provide important information regarding the timing of market recovery from a nosedive. For financial product distributors, using the dynamic relation among the three key indicators of the implied volatility curve might be helpful in enhancing profit and gaining trust and loyalty. However, it should be noted that our implications are limited since we do not provide rigorous evidence for the predictability power of volatility curves. Meaning, we need to verify whether the slope and curvature of the volatility curve have statistical significance in predicting the market trough. As one of the verifications, for instance, the performance of trading strategy based on information of slope and curvature could be tested. We reserve this for the future research.