• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.651-668
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• 2010

Various estimators of two risk measures of a specific financial portfolio, Value-at-Risk and Expected Shortfall, are compared for each case of 1-day and 10-day horizons. We use the Korea Composite Stock Price Index data of 20-year period including the year 2008 of the global financial crisis. Indexes of five foreign stock markets are also used for the empirical comparison study. The estimator considering both the heavy tail of loss distribution and the conditional heteroscedasticity of time series is of main concern, while other standard and new estimators are considered too. We investigate which estimator is best for the Korean stock market and which one shows the best overall performance.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.757-773
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• 2012

Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.

• The Korean Journal of Financial Management
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• v.16 no.2
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• pp.337-364
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• 1999

본 연구에서는 국내 주가지수선물시장과 현물시상간의 일중 가격 및 가격변동성의 선-후행관계를 실증적으로 분석함으로써 양 시장간의 동적관련성을 살펴보고자 하였다. 먼저, 상관관계분석의 결과는 KOSPI 200 주가지수선물수익률과 현물수익률, 그리고 주가지수선물수익률자승과 현물수익률 자승간에 유의한 교차상관관계가 존재하는 것으로 나타났다. 수익률의 선-후행관계를 살펴보기 위한 주가지수선물수익률의 시차변수들과 현물수익률간의 다중회귀분석의 결과는 주가지수선물수익률이 현물수익률을 약 15분 정도 선행하는 것으로 나타났으며, 이러한 현상은 현물수익률에 존재할 수 있는 비동시적 거래의 영향을 통제한 경우에도 비록 그 강도가 약하기는 하지만 여전하였다. 다음으로, 수익률 변동성의 선-후행관계를 살펴보기 위해 Grammatikos-Saunders (1986)가 제시한 무조건부 변동성의 추정치인 로그수익률자승을 사용하여 분석한 결과 주가지수선물수익률의 변동성이 현물수익률의 변동성을 약 10분 정도 선행하는 것으로 나타났으며, 이러한 결과는 비동시적 거래의 영향을 통제한 경우에도 동일하였다. 또한, Nelson(1991)의 EGARCH모형을 사용하여 수익률의 변동성을 추정한 후 이를 갖고 분석한 결과, 특히 비동시적 거래의 영향을 통제한 경우에는 주가지수선물시장과 현물시장의 수익률 변동성간에 선-후행관계가 존재한다는 것을 부정할 수 없었다.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.23-30
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• 2019

As deep learning with the network-based algorithms evolve, artificial intelligence is rapidly growing around the world. Among them, finance is expected to be the field where artificial intelligence is most used, and many studies have been done recently. The existing financial strategy using deep-run is vulnerable to volatility because it focuses on stock price forecasts for a single stock. Therefore, this study proposes to construct ETF products constructed through portfolio methods by calculating the stocks constituting funds by using deep learning. We analyze the performance of the proposed model in the KOSPI 100 index. Experimental results showed that the proposed model showed improved results in terms of returns or volatility.

• KDI Journal of Economic Policy
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• v.40 no.4
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• pp.1-22
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• 2018

We estimate three continuous-time stochastic volatility models following the approach by Aït-Sahalia and Kimmel (2007) to compare the Korean and US stock markets. To do this, the Heston, GARCH, and CEV models are applied to the KOSPI 200 and S&P 500 Index. For the latent volatility variable, we generate and use the integrated volatility proxy using the implied volatility of short-dated at-the-money option prices. We conduct MLE in order to estimate the parameters of the stochastic volatility models. To do this we need the transition probability density function (TPDF), but the true TPDF is not available for any of the models in this paper. Therefore, the TPDFs are approximated using the irreducible method introduced in Aït-Sahalia (2008). Among three stochastic volatility models, the Heston model and the CEV model are found to be best for the Korean and US stock markets, respectively. There exist relatively strong leverage effects in both countries. Despite the fact that the long-run mean level of the integrated volatility proxy (IV) was not statistically significant in either market, the speeds of the mean reversion parameters are statistically significant and meaningful in both markets. The IV is found to return to its long-run mean value more rapidly in Korea than in the US. All parameters related to the volatility function of the IV are statistically significant. Although the volatility of the IV is more elastic in the US stock market, the volatility itself is greater in Korea than in the US over the range of the observed IV.

• The Journal of Economics, Marketing and Management
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• v.9 no.4
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• pp.1-8
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• 2021

Purpose: This study empirically investigates what factors contribute to corporate value in the Korea New Exchange (KONEX) market and determines whether financial constraints contribute any effect on it. Research design, data and methodology: A fixed-effect panel regression model was utilized to analyze financial constraints on firm value for KONEX listed firms through the fiscal period from 2013 to 2020. Results: we find that firms' research and development, volatility, size, and sales growth give significant impacts to firm value, but the significance and direction are different. In addition, no significant relationship exists between the largest shareholder's equity ratio and firm value in all models. The debt-to-equity ratio did not show a significant relationship with corporate value. A significant negative relationship was found between R&D and corporate value in the entire sample. Volitility exhibited a positive relationship with corporate value in the entire sample and financially unconstrained companies. Firm size presented a significant negative relationship with company value in all models. Sales growth showed a significant negative relationship with corporate value in financially constrained companies. Conclusions: No difference is found between financially constrained and unconstrained companies in the KONEX market. We can infer that KONEX companies have a large difference with KOSPI or KOSDAQ. Further analysis is needed on the differences among these markets.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.251-265
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• 2021

It seems a common sense that corporate social responsibility (CSR) is a key driver to attain business sustainability. Nevertheless, there has been little research on the performance of socially responsible activities, including economic and environmental responsibility activities in internationally diversified firms. The purpose of this study was to evaluate the effects of CSR activities on management performance. For this evaluation, an empirical analysis was conducted with a total of 2,520 cases, selected from companies listed on the Korea Composite Stock Price Index market for six years from 2013 to 2018. As proxies for management performance, financial date such as a total asset net profit ratio and a total asset-operating ratio were used. A multivariate regression analysis was conducted to test hypotheses. The results of this analysis indicated that firms in the CSR outstanding group are significantly higher than other groups in management performances. In addition, CSR activities of internationally diversified firms positively influence their total asset net profit ratio and total asset-operating ratio. The results suggested that CSR activities of these firms can play a significant role in enhancing management performances amid the economic status of Korea, where a degree of export dependency is high.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.525-532
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• 2021

This study examines the association between a firm's business strategy and audit report lags. This study employs 5,072 firm-year observations from 2015 to 2019. Our sample comprises all of the firms listed on the Korea Composite Stock Price Index (KOSPI) market and Korea Securities Dealers Automated Quotation (KOSDAQ). We perform OLS regression analysis to test our hypothesis. The OLS regression analysis was conducted through the SAS and STATA programs. We find that business strategy is positively associated with audit report lags. Especially, we find that defender firms are negatively associated with audit report lags. The findings of this study suggest that prospector-like firms would increase their performance uncertainty as well as audit risk. Therefore, prospector-like firms interfere with the efficient audit procedures of auditors. On the other hand, our findings indicate that defender-like firms would decrease their performance uncertainty as well as an audit risk because they focus on simple product lines and cost-efficiency. For this reason, auditors will be able to carry out the audit procedures much more easily. Our results present that a prospector-like business strategy degrades audit effectiveness as it exacerbates a company's financial risk, willingness to accept uncertainty, and the complexity of organizational structure.