• Journal of Families and Better Life
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• v.27 no.1
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• pp.1-16
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• 2009

Using the 2007 Fund Investors Survey, we investigated (1) the differences in economic status in terms of household income, consumption, saving, assets and debts, (2) the differences in financial management behavior, (3) and the differences in confidence in economic status after retirement between households conducting and not-conducting financial preparation for retirement. The major study findings were as follows. First, only 46.4% of the households were financially preparing for retirement. The levels of income, consumption, and saving were higher among households conducting financial preparation for retirement than among those not-conducting such financial preparation. Second, households conducting financial preparation for retirement had a relatively high propensity to save. Their financial asset portfolio had a higher weight in safety assets and investment assets than in retirement assets. Due to their lack of confidence in their economic status after retirement, their demand for financial preparation for retirement remained. Third, the households which did not conduct financial preparation for retirement tended to have a relatively heavy debt burden and not to implement general household financial management practices. Fourth, among the three-pillar retirement income system, the second pillar, of individual retirement account was not well established. Based on these results, various implications were suggested.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.507-518
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• 2017

Volatility plays a crucial role in theory and applications of asset pricing, optimal portfolio allocation, and risk management. This paper proposes a combined model of autoregressive moving average (ARFIMA), generalized autoregressive conditional heteroscedasticity (GRACH), and skewed-t error distribution to accommodate important features of volatility data; long memory, heteroscedasticity, and asymmetric error distribution. A fully Bayesian approach is proposed to estimate the parameters of the model simultaneously, which yields parameter estimates satisfying necessary constraints in the model. The approach can be easily implemented using a free and user-friendly software JAGS to generate Markov chain Monte Carlo samples from the joint posterior distribution of the parameters. The method is illustrated by using a daily volatility index from Chicago Board Options Exchange (CBOE). JAGS codes for model specification is provided in the Appendix.

• Asia-Pacific Journal of Business
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• v.2 no.2
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• pp.61-78
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• 2011

Credit derivative is one kind of arrangement which allows one party to transfer, for a premium, the defined credit risk, computed with reference to a notional value, of a reference asset which may or may not owned by one or more other parties. Credit Default Swaps(CDS) have existed since the early 1990s, but its use has become increasingly popular over time. CDS is the fastest growing segment of the privately negotiated derivatives business as many firms depend on it to efficiently manage the financial market risks inherent in economic activities. The diversification function is especially important for active CDS market participants as banks. CDS banks can achieve their loan portfolio diversification which provides them with increased capacity to expand their lending.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1305-1325
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• 2008

As index option markets grow recently, many analysts and investors become interested in forecasting the volatility of KOSPI 200 Index to achieve portfolio's goal from the point of financial risk management and asset evaluation. To serve this purpose, we introduce NN and SVM integrated with other financial series models such as GARCH, EGARCH, and EWMA. Moreover, according to the empirical test, Integrating NN with GARCH or EWMA models improves prediction power in terms of the precision and the direction of the volatility of KOSPI 200 index. However, integrating SVM with financial series models doesn't improve greatly the prediction power. In summary, SVM-EGARCH was the best in terms of predicting the direction of the volatility and NN-GARCH was the best in terms of the prediction precision. We conclude with advantages of the integration process and the need for integrating models to enhance the prediction power.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.258-260
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• 2022

대체 불가능 토큰 (NFT, non-fungible token)은 고유하고 더 이상 분할할 수 없는 특성을 가지고 있다. NFT 는 디지털 콘텐츠에 대한 소유권을 증명해 주지만 현재 1) 소유권 증명 이상의 유틸리티가 명확하지 않고, 2) 토큰이지만 유동성이 거의 없으며, 3) 가격이 예측 불가능하다. 특히, 부동산의 경우 가격이 매우 높은 특징으로 인하여 투자 진입장벽이 매우 높다. NFT 분할을 하면 유동성의 증가, 그리고 접근성 증가에 따른 커뮤니티 볼륨의 증가를 기대해 볼 수 있다. 이러한 특성을 활용하여 기존에 투자하기 어려웠던 부동산을 다양한 기술을 활용하여 쉽게 투자를 할 수 있게 된다. 또한, Black Litterman 모델을 활용하여 보다 여러 종류의 NFT 들에 대한 최적 포트폴리오를 구성할 수 있는 알고리즘을 설계하고 구현하였다.

• Journal of the Korean Society of Food Culture
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• v.29 no.6
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• pp.593-598
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• 2014

Brands play a critical role as a core asset and the primary driver for corporate growth because of their power of identity and influence on customers' perceptions in restaurant industry. However, in spite of diverse and dynamically changing recent brand portfolio strategies of restaurants, a study on the effect of brand diversification on financial performance has been rarely conducted in the restaurant industry context. Considering competing viewpoints regarding diversification's influence on financial performance, the purpose of this study is, therefore, to examine the effect of brand diversification on firm performance of restaurants. The results indicated that brand diversification is positive effect to profitability. Brand diversification seems to be attractive and might be a reasonable growth strategy to expand market power by satisfying diverse consumer needs. Therefore, restaurant managers should be consider in implementing brand diversification strategy especially in dynamically changing trend of brand diversification in the current restaurant industry.

• Korean journal of food and cookery science
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• v.28 no.4
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• pp.451-461
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• 2012

The purposes of this study were to examine the financial statements and analyze the financial soundness of contract foodservice management companies(CFMC) using the financial ratio. The statistical data analysis was completed using Microsoft Excel(ver.2007) for the trend line equation and using SPSS Win(ver.18.0) for wilcoxon-rank sum test. Increased asset, debt, capital and sales occurred in most of the CFMCs, but the financial trend of firm D decreased for operating profit and net profit. The financial ratio for investigating a firm's financial soundness was based on liquidity, stability, profitability, activity, and growth through financial statements. Most of the CFMCs had maintained outstanding financial soundness from 1999 to 2011. The financial statements during the decade were verified and fluctuated. The directly affected CFMCs by a school foodservice' sanitation accident had maintained better financial statements than those of other CFMCs. Therefore, there was opportunity for directly affecting CFMCs involved in school foodservice' sanitation accident to diversify the business portfolio of the firms.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.623-635
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• 2021

The purpose of this research is to examine the impact of information risk on the Cost of Equity (COE) and whether the risk of a stock price crash mediates the relation between information risk and COE. To test the dynamic nature of the proposed model, the two-step system GMM dynamic panel estimators are applied to all the non-financial firms listed on the Pakistan Stock Exchange (PSX) from 2007- 2018. The results of this study show that all three types of information risk, as well as the risk of the share price crash, increases the COE. The crash risk strengthens the impact of information risk on the COE. Moreover, these three information risks are correlated with each other and an increase in information quality reduces the effect of asymmetric information and improves the investor interpreting ability, while an increase in private information decreases the transparency. The finding is crucial for asset pricing, portfolio management, and information disclosure. This study contributes to the literature by providing novel findings on the impact of three different types of information risk, i.e. private information, quality of information, and transparency of information on the COE as well as whether crash risk mediates the relationship.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.459-466
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• 2013

Risk exists in all construction projects and resides among the collection of subcontractors and their array of individual activities. Wherever risk resides, the interrelation of participants to one another becomes paramount for the way in which risk is measured. Inherent risk becomes recognizable and quantifiable within network schedules in the form of consuming float - the flexibility to absorb delays. Allocating, owning, valuing, and expending such float in network schedules has been debated since the inception of the critical path method itself. This research investigates the foundational element of a three-part approach that examines how float can be traded as a commodity, a concept whose promise remains unfulfilled for lack of a holistic approach. The Capital Asset Pricing Model (CAPM) of financial portfolio theory, which describes the relationship between risk and expected return of individual stocks, is explored as an analogy to quantify the inherent risk of the participants in construction projects. The inherent relationship between them and their impact on overall schedule performance, defined as schedule risk -the likelihood of failing to meet schedule plans and the effect of such failure, is matched with the use of CAPM's beta component - the risk correlation measure of an individual stock to that of the entire market - to determine parallels with respect to the inner workings and risks represented by each entity or activity within a schedule. This correlation is the initial theoretical extension that is required to identify where risk resides within construction projects, allocate and commoditize it, and achieve actual tradability.

• 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.