• 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 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.95-104
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• 2020

This study examines the effect of fintech on retail banks stock return listed in Indonesia Stock Exchange for the period of 2016-2018 as today's new technology lead to the emergence of fintech companies playing the same role as retail banks in the financial industry. This study is conducted quantitatively using monthly data from January 2016 to October 2018 and uses fintech as independent variable, proxied by fintech funding frequency and fintech funding value. Data transformation is conducted due to data volatility. The data of fintech funding, both frequency and value, is transformed into standardized fintech funding and growth of fintech funding. The data is obtained from Crunchbase, while the data of stock returns is obtained from Investing. This study further analyzes the data using Fama French Three-Factor Model and panel data regression. We found that fintech has no significant effect on retail banks' stock returns listed in Indonesia Stock Exchange for the period of 2016-2018. The findings of the study provide some useful insights in understanding fintech companies' current position to retail banks in Indonesia. This study also suggests banking institutions, fintech companies, policy-makers, and others to take advantageous steps in building inclusive financial sectors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.35-48
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• 2011

In this paper, we have studied the impact of adopting XBRL (eXtensible Business Reporting Language) on information asymmetry in capital markets with the additional research on the usefulness of XBRL data how to improve the quality of accounting information. From the Kosdaq XBRL service, the samples are selected including 38 adopted companies and the 30 non-adopted companies for the paired analysis. The daily stock return volatility (VOLA) as independent variable and other several controlling variables have been added for the regression analysis to measure the impact on information asymmetry in capital markets. he analytical result indicated that the asymmetry hypotheses that XBRL data will give a significant impact on the capital market and will reduce the volatility, which are expected in the hypotheses. This is the first analytical research on the capital market and its impacts to the capital market from adopting XBRL based accounting information. Additionally, the analysis showed the impacts on the reporting cycle of accounting information and its usefulness of accounting data itself.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5671-5676
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• 2011

Volatility Index is the index that represents future volatility of underlying asset implied in option price and expected value of market that measures the possibility of stock price's change expected by investors. The Korea Exchange announces a volatility Index, VKOSPI, since April, 13, 2009. This paper used daily data from January, 2002 through December, 2008 and tested power of Volatility index for future returns of portfolios sorted by size, book-to-market equity and beta. As a result, VKOSPI has the predictive power to future returns and then VKOSPI may be determinants of returns. Also if beta is included when sorting portfolio, the predictive power of VKOSPI is stronger for future portfolio returns.

• Korean Management Science Review
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• v.28 no.3
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• pp.61-72
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• 2011

This study suggests a DEA(Data Envelopment Analysis) based model to evaluate the value of corporate stock. The model integrating PER(Price-Earning Ratio), PBR(Price-BookValue Ratio), PSR(Price-Sales Ratio) and volatility in DEA structure has an advantage of overcome the limitation of traditional financial ratio based models. In order to show the effectiveness of the suggested model. we compare the performance of portfolio composed by DEA approach with those of portfolios made by traditional approaches such as PER, PBR, and PSR in terms of stock return and volatility. Specifically, we use the data of all the enterprises listed on the S&P 500 in the U.S. in 2007 and 2009 as the sample data for the experiments. The results of the experiments show that the performance of the DEA approach is clearly better than those of other approaches. Particularly, in sharply plummeting market, the performance of the DEA approach is shown to be prominently better than those of other approaches as the DEA approach reflects investment risk as well as profitability and growth. The DEA score combining the existing investment indices may serve as a useful barometer for selecting a stable and profitable portfolio.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.165-187
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• 2005

This paper tries to investigate the relationships among stock return volatility, time-varying risk premium and Korea Discount. Using Korean Composite Stock Price Index (KOSPI) return from January 4, 1980 to August 31, 2005, this study finds possible links between time-varying risk premium and Korea Discount. First of all, this study classifies Korean stock returns during the sample period by three regime-switching volatility period that is to say, low-volatile period medium-volatile period and highly-volatile period by estimating Markov-Switching ARCH model. During the highly volatile period of Korean stock return (09/01/1997-05/31/2001), the estimated time-varying unit risk premium from the jump-diffusion GARCH model was 0.3625, where as during the low volatile period (01/04/1980-l1/30/1985), the time-varying unit risk premium was estimated 0.0284 from the jump diffusion GARCH model, which was about thirteen times less than that. This study seems to find the evidence that highly volatile Korean stock market may induce large time-varying risk premium from the investors and this may lead to Korea discount.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.165-173
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• 2017

The purpose of this study was to analyze the correlation and volatility of Korea and neighboring East Asia stock markets. East Asian stock markets were selected for Japan, China, Hong Kong and Taiwan by economically and geographically close with Korea. If you understand the volatility and the correlation between Korea and the East Asian stock market, it may be helpful in predicting investment. And It may reduce the risk of investing of asset allocation in global portfolio level. For this using the national monthly return data for the last 163 months, I was calculating and comparison the rate and correlation, and regression analysis. Result of the correlation analysis, Korea have shown a low correlation with China. while showing a high correlation with Taiwan and Hong Kong. China has been forming its own market in East Asia and showing a low correlation with other countries exception Hong Kong. Hong Kong has been determined as the highest harmonization within the East Stock Market.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.320-332
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• 2021

This paper investigates the influence of stock-level left-tail risk, which is defined using Value-at-Risk(VaR) estimates of past one-year daily stock returns, in the expected stock returns in the Korean stock market. Our results are summarized as follows: First, monthly-constructed zero-cost portfolios that buy (shortsell) the highest (lowest) left-tail risk decile in the previous month exhibit an average monthly return (called left-tail risk premium) of -2.29%. Second, Fama-MacBeth cross-sectional regressions suggest that left-tail risk in the previous month shows significant and negative explanatory power over return in this month, after controlling for various firm characteristics such as firm size, B/M, market beta, liquidity, maximum daily return, idiosyncratic volatility, and skewness. Third, the stocks with larger recent month loss have lower returns in the next month. Fourth, the magnitude of left-tail risk premium is negatively related with lagged market-level volatility. These results support the hypothesis from a perspective of behavioral finance that the overpricing of stocks with left-tail risk is attributed to the investors' underreaction to it.

• Journal of Distribution Science
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• v.19 no.1
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• pp.27-35
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• 2021

Purpose: This study is to investigate the effect of managerial ownership level in distribution and service companies on the stock price crash. The managerial ownership level affects the firm's information disclosure policy. If managers conceal or withholds business-related unfavorable factors over a long period, the firm's stock price is likely to plummet. In a similar vein, management's equity affects information opacity, and information asymmetry affects stock price collapse. Research design, data, and methodology: A regression analysis is conducted using the data on companies listed on the Korea Composite Stock Price Index (KOSPI) between 2012-2017 to examine the effect of the managerial ownership level on stock price crash risks. Results: Logistic and regression results indicate that the stock price crash risk was reduced as managerial ownership levels are increased. The managerial ownership level has a significant negative coefficient on stock price crash risk, negative conditional return skewness of firm-specific weekly return distribution, and asymmetric volatility between positive and negative price-to-earnings ratios. Conclusions: As the ownership and management align, the likeliness of withholding business-related information is reduced. This study's results imply that the stock price crash risk reduces as the managerial ownership level increases because shareholder and manager interests coincide, thereby reducing information asymmetry.