• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1017-1028
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• 2014

Well-known Bayes and empirical Bayes estimators have a disadvantage in respecting to overshink the parameter estimator error; therefore, a constrained Bayes estimator is suggested by matching the first two moments. Also traditional loss function such as mean square error loss function only considers the precision of estimation and to consider both precision and goodness of fit, balanced loss function is suggested. With these reasons, constrained Bayes estimators under balanced loss function is recommended for non-life insurance pricing.; however, most studies focus on the performance of estimation since Bayes risk of newly suggested estimators such as constrained Bayes and constrained empirical Bayes estimators under specific loss function is difficult to derive. This study compares the Bayes risk of several Bayes estimators under two different loss functions for estimating the risk in the auto insurance business and indicates the effectiveness of the newly suggested Bayes estimators with regards to Bayes risk perspective through auto insurance real data analysis.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.

• Analyses & Alternatives
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• v.5 no.2
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• pp.77-105
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• 2021

Natural gas consumption in Asia is growing at fast tempo because of various factors such as economic growth in the region, urbanization, coal-to-gas switch at power and industry sector. Due to geographical characteristics and lack of international pipeline connections between countries in the continent, majority of natural gas exported to Asian consumers is transported by tankers on the sea in the form of liquefied natural gas. As Asian market is the most lucrative market with the fastest demand growth, the competitions between LNG sellers for market share in Asian market are strengthening. The competitions accelerated, especially after the introduction of large volume of incremental supply into the market by new exporters from the U.S., Australia, and Russia. Cheniere Energy, the first exporter of liquefied natural gas (LNG) in the lower 48 states of U.S. has not adopted the traditional price formation mechanism and business model. Traditionally, prices of long-term LNG contracts have been indexed to the price of competing fuels, such as crude oil. The company adopted a pricing mechanism and business model based on a cost-plus system. Cheniere Energy opted for the safer and the risk-free pricing system, that annually guarantees a fixed amount of revenue to the seller. The company earns the same amount of money, regardless of natural gas price dynamics in the domestic and international market, but possibly with less revenue. However, by introducing and successfully implementing the safer and risk- free business model, Cheniere Energy, a company of a relatively smaller size in comparison with major oil and gas companies, became an example to other smaller-sized companies in the U.S. The company's business model demonstrated how to enter and operate LNG business amid increasing competitions among sellers in the U.S. and international market.

• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.209-237
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• 2010

This paper examines the relationship between information risk and equity premium in the Korean stock market. We use accruals quality as a proxy of information risk. Accruals quality (AQ) is estimated by Dechow and Dichev (2002) model, and then AQfactor is constructed based on the estimated AQ. Time-series and cross-sectional regression models are used to examine the relationship between information risk and equity premium, reflecting the critics of Core et al. (2008). The result of the paper shows that information risk proxied by accruals quality is not priced in equity premium in the Korean stock market. This result is consistent with Core et al. (2008) for US firms, but different with Francis et al. (2005) for US firms and Gray et al. (2008) for Australia firms. Also, the result shows that AQfactor is closely correlated with firm characteristic variables such as firm size. This implies that the effect of AQ on equity premium is more likely to arise from the pricing error due to firm characteristics rather than from an unknown risk factor.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.98-105
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• 2021

Using the frequency-based decomposition, I decompose the consumption growth to explain well-known patterns of stock returns in the Korean market. To be more specific, the consumption growth is decomposed by its half-life of shocks. The component over four years of half-life is called the business-cycle consumption component, and the components with half-lives under four years are short-run components. I compute the long-run and short-run components of stock excess returns as well and use component-by-component sensitivities to price stock portfolios. As a result, the business-cycle consumption risk with half-life of over four years is useful in explaining the cross-section of size-book-to-market portfolios and size-momentum portfolios in the Korean stock market. The short-run components have their own pricing abilities with mixed direction, so that the restricted one short-term factor model is rejected. The explanatory power with short- and long-run components is comparable to that of the Fama-French three-factor model. The components with one- to four-year half-lives are also helpful in explaining the returns. The results about the long-run components emphasize the importance of long-run component in consumption growth to explain the asset returns.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.45-52
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• 2021

Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009-2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.563-585
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• 2008

This paper presents how to improve the efficiency and accuracy in the pricing and sensitivity evaluation for derivatives, since the need for the evaluation of complicated derivatives is increased. The Monte Carlo(MC) simulation using the quasi random number instead of pseudo random number can improve the elapsed time and accuracy for the valuation of European-type derivatives. However, the quasi MC simulation method has its limit for applying it in the multi-dimensional case such as American-type and path-dependent options due to the increased correlation between dimensions as the dimension of random numbers is increased. In order to complement this problem, we develop a modified method in which correlation values are controlled to be below a pre-specified value. Thus, this method is applicable for the pricing of either derivatives ill which underlying assets or risk factors are several or derivatives having path-dependent or early redemption property. Furthermore, we illustrate that it is important to take an appropriate grid interval for the use of finite difference method(FDM) by applying the FDM to one example of non-symmetrical butterfly spreads.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.85-101
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• 2022

Derivative-linked securities (DLS) is a type of derivatives that offer an agreed return when the underlying asset price moves within a specified range by the maturity date. The underlying assets of DLS are diverse such as interest rates, exchange rates, crude oil, or gold. A German 10-year bond rate-linked DLS and a USD-GBP CMS rate-linked DLS have recently become a social issue in Korea due to a huge loss to investors. In this regard, this paper accounts for the payoff structure of these products and evaluates their prices and fair coupon rates as well as risk measures such as Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). We would like to examine how risky these products were and whether or not their coupon rates were appropriate. We use Hull-White Model as the stochastic model for the underlying assets and Monte Carlo (MC) methods to obtain numerical results. The no-arbitrage prices of the German 10-year bond rate-linked DLS and the USD-GBP CMS rate-linked DLS at the center of the social issue turned out to be 0.9662% and 0.9355% of the original investment, respectively. Considering that Korea government bond rate for 2018 is about 2%, these values are quite low. The fair coupon rates that make the prices of DLS equal to the original investment are computed as 4.76% for the German 10-year bond rate-linked DLS and 7% for the USD-GBP CMS rate-linked DLS. Their actual coupon rates were 1.4% and 3.5%. The 95% VaR and TVaR of the loss for German 10-year bond rate-linked DLS are 37.30% and 64.45%, and those of the loss for USD-GBP CMS rate-linked DLS are 73.98% and 87.43% of the initial investment. Summing up the numerical results obtained, we could see that the DLS products of our interest were indeed quite unfavorable to individual investors.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.665-680
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• 2009

This study aims at analyzing the performance of Real Estate Investment Trusts(REITs) by Risk Adjustment Model. The main results are as follows. Firstly, most property types of REITs gain positive(+) excess overall returns at first and second period. On the contrary, most property types of REITs gain negative(-) excess overall returns and their standard deviations are larger at financial crisis period. Secondly, lodging, regional mall and commercial mortgage show lower risk-lower return, and freestanding, apartment and specialty show higher risk-higher return than average REITs, according to the CAPM results of . Moreover CAPM results of show the characteristics of REITs as investment commodities changes into higher risk-higher return for financial crisis period. Lastly, risk adjusted demanded returns of REITs are affected positively(+) by systemic risks and negatively(-) by unsystemic risks, according to the Risk Adjustment Model results of both and . Comparing risk adjusted demanded returns of REITs with their realized returns, healthcare reveals the largest outperformance.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.3
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• pp.259-266
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• 2015

Among many energy resources, natural gas has recently received a remarkable amount of attention, particularly from the electrical generation industry. This is in part due to increasing shale gas production, providing an environment-friendly fossil fuel, and high risk of nuclear power. Because South Korea, the world's second largest LNG importing nation after Japan, has no international natural gas pipelines and relies on imports in the form of LNG, the natural gas has been traditionally procured by long term LNG contracts at relatively high price. Thus, there is a need of developing an Asian LNG trading hub, where LNG can be traded at more competitive spot prices. In a natural gas spot market, the amount of natural gas to be bought should be carefully determined considering a limited storage capacity and future pricing dynamics. In this work, the problem to find the optimal amount of natural gas in a spot market is formulated as a Markov decision process (MDP) in risk neutral environment and the optimal base stock policy which depends on a stage and price is established. Taking into account price and demand uncertainties, the basestock target levels are simply approximated from dynamic programming. The simulation results show that the basestock policy can be one of effective ways for procurement of LNG in a spot market.