• KDI Journal of Economic Policy
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• v.33 no.1
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• pp.93-124
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• 2011

In this paper, we claim the asymmetric response of asset returns on the past asset returns' signs may be explained from the market behavioral portfolio choice of investors. For this, we admit the anchor and adjustment mechanism of investors which partly explains the momentum in the asset prices. We also claim the prospect theory based on the risk aversions may simultaneously work with the anchor and adjustment effect, whenever the lagged asset return was positive and investors accrued the gain. To identify these effects empirically in a threshold autoregressive model, we suppose the risk aversions inducing the volatility effect is related with the past volatility of asset returns. In application of suggested method to Korean stock and real estate markets, we found these effect exist as expected.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.569-579
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• 2005

International capital movement has made progress at global liberalization of finance and foreign exchange, international monetary norm changing into floating exchange rate system, easiness of collection of information and trade at improvement of information communication technology from early of 1970's. Results of empirical test for relation between foreign exchange rate or various determination factors of foreign exchange rate and interest rate are followed by next sentences. First, according to relation between foreign exchange rate and interest rate, correlation for each of variables after OECD entrance is increased. 'But, long-term & short-term interest rate is affected by Hanbo & Kia's bankruptcy, continuous large scale coporates bankruptcy and crisis of foreign exchange. Therefore, financial instability is occured. If portfolio investment fund has been inflow as it is mollified by continuous shortage of foreign exchange and fall of country's credit rating, it is expected to have positive effect for long-term & short-term interest rate from appreciation of won against dollar. Second, results from relation between determination factor of foreign exchange rate and interest rate are followed by next sentences. If surplus of current account and goods account is continued, yield of corporate bond is to be stable. But, margin of surplus is expected to diminish after second quarter 98, and difference between external and domestic interest (after adjusting foreign exchange rate) is to be diminished. And if net inflows of foreign investor's fund (stock and bond) is diminished, it is to have negative effect for yield of corporate bond. According to foreign investor's investment movement of previous years, hedge fund were stayed at least during two years in Mexico. It means that sudden capital outflow is not to be happened at Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.133-144
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• 1998

International capital movement has made progress at global liberalization of finance and foreign exchange, international monetary norm changing into floating exchange rate system, easiness of collection of information and trade at improvement of information communication technology from early of 1970's. Results of empirical test for relation between foreign exchange rate or various determination factors of foreign exchange rate and interest rate are followed by next sentences. First, according to relation between foreign exchange rate and interest rate, correlation for each of variables after OECD entrance is increased. But, long-term & short-term interest rate is affected by Hanbo & Kia's bankruptcy, continuous large scale corporates bankruptcy and crisis of foreign exchange. Therefore, financial instability is occured. If portfolio investment fund has been inflow as it is mollified by continuous shortage of foreign exchange and fall of country's credit rating, it is expected to have positive effect for long-term & short-term interest rate from appreciation of won against dollar. Second, results from relation between determination factor of foreign exchange rate and interest rate are followed by next sentences. If surplus of current account and goods account is continued, yield of corporate bond is to be stable. But, margin of surplus is expected to diminish after second quarter 98, and difference between external and domestic interest (after adjusting foreign exchange rate) is to be diminished. And if net inflows of foreign investor's fund (stock and bond) is diminished, it is to have negative effect for yield of corporate bond. According to foreign investor's investment movement of previous years, hedge fund were stayed at least during two years in Mexico. It means that sudden capital outflow is not to be happened at Korea. But if external factors from depreciation of yen and China's renminbi are instable, interest rate is expected to increase from capital's outflows. Third, if it is to decrease instability of foreign exchange rate from increase in surplus of future current account, credit rating's upwardness, stability of yen and renminbi, foreign exchange rate is expected to be stable. It is expected to have continuous stability from short-term interest rate to long-term interest rate in this empirical test.

• Proceedings of the Safety Management and Science Conference
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• 2002.11a
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• pp.305-319
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• 2002

International capital movement has made progress at global liberalization of finance and foreign exchange, international monetary norm changing into floating exchange rate system, easiness of collection of information and trade at improvement of information communication technology from early of 1970's. Results of empirical test for relation between foreign exchange rate or various determination factors of foreign exchange rate and interest rate are followed by next sentences. First, according to relation between foreign exchange rate and interest rate, correlation for each of variables after OECD entrance is increased. But, long-term ＆short-term interest rate is affected by Hanbo ＆ Kia's bankruptcy, continuous large scale coporates bankruptcy and crisis of foreign exchange. Therefore, financial instability is occured. If portfolio investment fund has been inflow as it is mollified by continuous shortage of foreign exchange and fall of country's credit rating, it is expected to have positive effect for long-term & short-term interest rate from appreciation of won against dollar. Second, results from relation between determination factor of foreign exchange rate and interest rate are followed by next sentences. If surplus of current account and goods account is continued, yield of corporate bond is to be stable. But, margin of surplus is expected to diminish after second quarter 98, and difference between external and domestic interest (after adjusting foreign exchange rate) is to be diminished. And if net inflows of foreign investor's fund (stock and bond) is diminished, it is to have negative effect for yield of corporate bond. According to foreign investor's investment movement of previous years, hedge md were stayed at least during two years in Mexico. It means that sudden capital outflow is not to be happened at Korea. But if external factors from depreciation of yen and China's renminbi are instable, interest rate is expected to increase from capital's outflows. Third, if it is to decrease instability of foreign exchange rate from increase in surplus of future current account, credit rating's upwardness, stability of yen and renminbi, foreign exchange rate is expected to be stable. It is expected to have continuous stability from short-term interest rate to long-term interest rate in this empirical test.

• 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.

• Asia Pacific Journal of Business Review
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• v.1 no.2
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• pp.37-62
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• 2017

To analyze the effects of R&D expenditure on the firm value of Korean firms, we classified portfolios based on R&D activity levels. After that, we conducted a time-series analysis to assess excess returns from the portfolios. To carry out such an analysis, an empirical analysis of excess returns in the capital market was performed by using the monthly earning rate of stocks from 2000 to 2013. The purpose of this research is to provide basic data on investment to stakeholders in the capital market by analyzing the effects of R&D on the firm value and to overcome scholarly limitations by offering a new model of analysis. The criteria for classifying the portfolios were based on R&D expenditure levels. The analysis models follow the Fama-French Three-Factor Model and the Carhart Four-Factor Model. The analyses results are as follows. Extrapolating monthly profit rates based on R&D expenditure levels, portfolios with low R&D expenditures showed higher earning rates than those with high R&D expenditures. This suggests that high R&D expenditures did not translate into high earning rates. The investor depreciates the R&D expenditures related profitability and the possibility of success in the market, leading to falls in stock prices and a failure to give a positive effect on the firm value. Our research differs from the previous investigations as we carried out an empirical analysis based on the actual investors' attitudes about R&D expenditures and how these can generate excess earnings. Our research results show that the data related to R&D expenditure are not reflected fully in the market.

• International Area Studies Review
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• v.14 no.3
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• pp.62-84
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• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• Economic Analysis
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• v.27 no.4
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• pp.43-69
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• 2021

As the trade linkages and the financial relationship between China and Korea grow stronger, China's influence on Korea is also growing larger. Therefore, it is meaningful to examine key features of Chinese monetary policy operations and the current situation, and to analyze the transmission mechanism of China's monetary policy shocks onto the Korea economy. China's monetary policy shocks can have an impact on the Korea economy through the trade, financial and oil-price channels. In the trade channel, an expansionary Chinese monetary policy can increase Korea's exports of intermediate goods to China under the vertical trade structure, via the vertical trade integration effect. Meanwhile, the expenditure switching effect and the income demand effect show no statistical significance. In the financial and oil-price channels, expansionary Chinese monetary policy shocks can decrease the interest rate and increase both stock prices and the consumer price index in Korea through changes in global portfolio capital flows, interest rates, and raw material prices.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.