• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.5
• /
• pp.465-474
• /
• 2022

Using structural equation modeling, the study aims to investigate the causal relationship between working capital policies and working capital indicators on firm performance, including profitability and market value (SEM). The samples of 381 firms were selected from various industries listed on the Stock Exchange of Thailand (SET) from 2016 to 2020. The results showed that 1) there is an effect of working capital policies on profitability and market value; 2) there is an effect of working capital indicators on profitability and market value and 3) there is the effect of profitability on market value. From the results, it is suggested that conservative working capital investment policy (CIP) and conservative working capital financing policy (CFP) affect a company's performance in the Thailand context. In addition, shortening the cash conversion cycle (CCC) should be applied in management to increase profitability by reducing the receivables collection period (RCP) and inventory conversion period (ICP) while increasing the payables deferral period (PDP). The practical implications of the study provide the evidence that meeting the dues according to short CCC management can represent healthy liquidity in cash flow that helps gain investor confidence and the investment interest that further increases the market value.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.10
• /
• pp.6511-6516
• /
• 2015

This paper examines the relationship between idiosyncratic volatility(IVOL) puzzle and trading volumes by trader types in the Korean stock market. The data set includes all stock in both KRX and KOSDAQ for the period from January 1999 through December 2013. Idiosyncratic volatility is measured by using the Fama-French's three-factor model. Traders are classified into individual, institution, and foreign trader. We construct (5X5) portfolios based on each trader's net buying and idiosyncratic volatility. We find that there are some special portfolios that show the idiosyncratic volatility puzzle. For individual investors, top net buying portfolios show clear the idiosyncratic volatility puzzle. However, for institution and foreign investors, lowest net buying portfolio show the idiosyncratic volatility puzzle. This results imply that the idiosyncratic volatility puzzle in the Korean stock market is mainly caused by individual investors.

• The Korean Journal of Financial Management
• /
• v.26 no.1
• /
• pp.221-263
• /
• 2009

This paper studies the behaviour of stock prices on the ex-dividend day in the Korean stock market. Since a majority of listed Korean firms are December firms whose fiscal year end in December and whose ex-dividend day falls on the same calendar day in the year, we use stock prices of Non-December firms to estimate the general stock price movements not related to cash dividends. We estimate excess returns on days around the ex-dividend day. Our major findings are (a) there is no tax clientele effect in Korea, (b) the opening price stock prices fell by the amount of the current cash dividend per share until 2001, but it does not fall as much as the current dividend per share since 2001. Furthermore, in contrast to the U.S. and the Japanese findings, (c) stocks earned negative excess returns on the ex-dividend day until 2001, after which all stocks are earning positive excess returns on the ex-dividend day, and (d) the closing stock price on the ex-dividend day that used to be even higher than the cum-dividend price until 2001 is lower than the opening stock price since 2001. The evidence suggests a structural break has happened around the year 2001.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.4
• /
• pp.503-509
• /
• 2022

The purpose of this study is to set the rate of change between the market price of the next day and the previous day to be predicted as the predicted value, and the market price for each section is generated by dividing the stock price ranking of the next day to be predicted at regular intervals, which is different from the previous papers that predict the market price. We would like to propose a new time series data prediction method that predicts the market price change rate of the final next day through a model using the rate of change as the predicted value. The change in the performance of the model according to the degree of subdivision of the predicted value and the type of input data was analyzed.

• KDI Journal of Economic Policy
• /
• v.25 no.2
• /
• pp.137-170
• /
• 2003

Despite the great success of the derivatives market, several concerns were expressed regarding the additional volatilitystemming from program trading during the expiration of derivatives. This paper examines the impact of the expiration of the KOSPI 200 index derivatives on cash market of Korea Stock Exchange(KSE). The KOSPI 200 index derivatives market has a unique settlement price determination process. The settlement price for the expiration of derivatives is determined by call auction during the last 10 minutes after the trades for matured derivatives are finalized. We analyze typical expiration day effects such as price, volatility, and volume effects. With high frequency data, we find that there are strong expiration day effects in the KSE and try to interpret the results with the unique settlement procedures of the KOSPI 200 cash and derivatives markets.

• The Journal of Information Systems
• /
• v.2
• /
• pp.127-140
• /
• 1993

• The Korean Journal of Financial Studies
• /
• v.1 no.2
• /
• pp.185-214
• /
• 1994

• The Journal of the Korea Contents Association
• /
• v.16 no.3
• /
• pp.81-90
• /
• 2016

This study aims to investigate the association between stock performance and credit ratings, and credit rating changes using a sample of 1,691 KRX firm-years that acquire equity in the form of long-term bonds from 2002 to 2013. Previous U.S. literature is mixed with regard to the relation between credit ratings and stock price. On one hand, there is evidence of a positive relation between credit ratings and stock prices, an anomaly established in U.S. studies. On the other hand, the CAPM model suggests a negative relation between stock prices and credit ratings, implying that investors expect financial rewards for bearing additional risk. To our knowledge, we are the first to examine the relationship between stock price and default risk proxied by credit ratings in period t+1. We find a negative (positive) relation between credit ratings (risk) in period t+1 and stock returns in period t, suggesting that credit rating agencies do not consider stock returns as a metric with the potential to influence default risk. Our results suggest that market participants may prefer firms with higher credit risk because of expected higher returns.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.6
• /
• pp.9-19
• /
• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.51-59
• /
• 2024

This study examines the relationship between the release of the news and the individual stock returns. Investors utilize a variety of information sources to maximize stock returns when establishing investment strategies. News companies publish their articles based on stock recommendation reports of analysts, enhancing the reliability of the information. Defining release of a stock-recommendation news article as an event, we examine its economic impacts and propose a binary classification model that predicts the stock return 10 days after the event. XGBoost and LightGBM models are applied for the study with accuracy of 75%, 71% respectively. In addition, after categorizing the recommended stocks based on the listed market(KOSPI/KOSDAQ) and market capitalization(Big/Small), this study verifies difference in the accuracy of models across four sub-datasets. Finally, by conducting SHAP(Shapley Additive exPlanations) analysis, we identify the key variables in each model, reinforcing the interpretability of models.