• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.137-145
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• 2007

In traditional financial theory, the discount cash flow model(DCF or NPV) operates as the basic framework for most analyses. In doing valuation analysis, the conventional view is that the net present value(NPV) of a project is the measure of the present value of expected net cash flows. Thus, investing in a positive(negative) NPV project will increase(decrease) firm value. Recently, this framework has come under some fire for failing to consider the options of the managerial flexibilities. Real option valuation(ROV) considers the managerial flexibility to make ongoing decisions regarding the implementation of investment projects and the deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real assets based on the Black-Sholes option pricing model, the binomial option pricing model, and the Monte Carlo simulation. This paper uses those models to obtain point estimates of real option value with the G7- HSR350X(high-speed train).

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.189-204
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• 2018

This study is on forecasting the electricity consumption of an industrial manufacturing building called GGM from January 2014 to April 2017. We fitted models using SARIMA, SARIMA + GARCH, Holt-Winters method and ARIMA with Fourier transformation. We also forecasted electricity consumption for one month ahead and compared the predicted root mean square error as well as the predicted error rate of each model. The electricity consumption of GGM fluctuates weekly and annually; therefore, SARIMA + GARCH model considering both volatility and seasonality, shows the best fit and prediction.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.189-200
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• 2015

Stationary bootstrapping is applied to a Lagrangian multiplier (LM) test to test market microstructure noise (MMN) in financial asset prices. A Monte-Carlo experiment shows that the bootstrapping method improves the size of the original LM test which has some size distortion for conditional heteroscedastic models. The proposed test is illustrated for real data sets like KOSPI index and Won-Dollar exchange rate.

• Safety and Health at Work
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• v.2 no.2
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• pp.97-104
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• 2011

N,N-Dimethylformamide (DMF) is globally used as an organic solvent in the production of synthetic leather and resins because of its low volatility, making it an attractive industrial material. Despite its excellent property as a chemical solvent, utilization of DMF is somewhat controversial nowadays due to its hazardous effects on exposed workers in work places. Many toxification cases are being reported globally and the number of cases of liver damage is still increasing in developing countries. On account of this, a series of epidemiologic surveys are being conducted to understand the degrees of liver damage caused by DMF exposure. Furthermore, many investigations have been performed to clarify the mechanism of DMF-induced liver toxicity using both human and experimental animal models. This review summarizes the current occupational cases reported on liver damage from workers exposed to DMF in industrial work places and the research results that account for DMF-induced liver failure and possible carcinogenesis. The findings reviewed here show the synergistic toxicity of DMF exposure with other toxicants, which might occur through complicated but distinct mechanisms, which may extend our knowledge for establishing risk assessments of DMF exposure in industrial work places.

• Journal of the Korean Mathematical Society
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• v.61 no.5
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• pp.875-898
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• 2024

This study estimates the true price of an asset and finds the optimal bid/ask prices for market makers. We provide a novel state-space model based on the exponential Ornstein-Uhlenbeck volatility and the Heston models with Gaussian noise, where the traded price and volume are available, but the true price is not observable. An objective of this study is to use Bayesian filtering to estimate the posterior distribution of the true price, given the traded price and volume. Because the posterior density is intractable, we employ the guided particle filtering algorithm, with which adaptive rejection metropolis sampling is used to generate samples from the density function of an unknown distribution. Given a simulated sample path, the posterior expectation of the true price outperforms the traded price in estimating the true price in terms of both the mean absolute error and root-mean-square error metrics. Another objective is to determine the optimal bid/ask prices for a market maker. The profit-and-loss of the market maker is the difference between the true price and its bid/ask prices multiplied by the traded volume or bid/ask size of the market maker. The market maker maximizes the expected utility of the PnL under the posterior distribution. We numerically calculate the optimal bid/ask prices using the Monte Carlo method, finding that its spread widens as the market maker becomes more risk-averse, and the bid/ask size and the level of uncertainty increase.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.43-69
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• 2005

This study provides empirical evidence that the stochastic beta model based on Bayesian analysis outperforms the existing conditional beta model and GARCH model in terms of the estimation accuracy and the explanatory power in the cross-section of stock returns in Korea. Betas estimated by the stochastic beta model explain $30{\sim}50%$ of the cross-sectional variation in stock-returns, whereas other time-varying beta models account for less than 3%. Such a difference in explanatory power across models turns out to come from the fact that the stochastic beta model absorbs the variation due to the market anomalies such as size, BE/ME, and idiosyncratic volatility. These results support the rational asset pricing model in that market anomalies are closely related to the variation of expected returns generated by time-varying betas.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.42-52
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• 2009

From the beginning of 2000, Korean housing market has experienced cyclical volatility because of the global economic fluctuation such as steady decline in the interest rate and the house price bubble. In response to these state Korean Government announced policies about housing sales system kinds of Sales Unit Price Restraint and Post-Sales System to stabilize housing market. But such policies has brought unprecedented arguments both for and against, most of whom still seem to stick to self-centered judgement ahead of impact on housing market. In an integrated point of view, applying the system dynamics modeling, the paper aims at proposing basic Korean housing market dynamics models based on basis principles of housing market determined by supply and demand. And then, after research policies about housing sales system, analyze Impact on Korean Housing Market by change of Sales Systems applying policies to basic Korean housing market dynamics models.

• International Area Studies Review
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• v.20 no.1
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• pp.3-22
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• 2016

In this study, I examine mutual shock spillover effects among interest rate differences, won-dollar foreign exchange change rates, and stock market returns in Korea during the daily sample period from the beginning of 1995 to the October 16, 2015, using the multivariate GARCH (generalized autoregressive conditional heteroscedasticity) BEKK (Baba-Engle-Kraft-Kroner) model framework. Major findings are as follows. Throughout the 6 model estimation results of variance equations determining return spillovers covered from symmetric and asymmetric models of total sample period and two crisis sub-sample periods composed of Korean FX Crisis Times and Global Financial Crisis Times, shock spillovers are shown to exist mainly from stock market return shocks. Stock market shocks including down-shocks from the asymmetric models are shown to transfer to those other two markets most successfully. Therefore it is most important to maintain stable financial markets that a policy design for stock market stabilization such as mitigating stock market volatility.

• Journal of the Korea Society for Simulation
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• v.28 no.3
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• pp.49-56
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• 2019

In this paper, we deal with two pricing of bond options using the relationship between the forward rate model and the Libor rate model. First, we derive a formula for obtaining discounted bond prices using the restrictive condition of the Ritchken and Sankarasubramanian (RS), and then use the volatility function relationship of the forward rate and the Libor rate models to find the analytic solution (AS) of bond options pricing. Second, the price of the bond options is calculated by simulating several scenarios from the presented condition using Monte Carlo Simulation (MCS). Comparing the results of the implementation of the above two pricing methods, the relative error (RE) is obtained, which means the ratio of AS and MCS. From the results, we can confirm that the RE is around 3.9%, which means that the price of the bond options can be predicted very accurately using the MCS as well as AS.

• Journal of the Economic Geographical Society of Korea
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• v.13 no.2
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• pp.234-252
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• 2010

This paper examines the tendency of housing assets to become increasingly quasi-financial assets by analyzing the relationships between risks and returns in three Gangnam districts (Gangnam-gu, Seocho-gu and Songpa-gu) apartment markets in Seoul, especially for the apartments to be reconstructed, capitalizing upon some capital asset pricing models (CAPM). A single factor CAPM model shows positive relationships between risks and returns regardless of the types of apartments in three Gangnam districts. Multi-factors CAPM models also confirm that the market and SMB (small minus big) factors are positively related to the rate of returns regardless of the types of apartments. However, the unsystematic risk factor is found to be statistically positive especially for the apartments to be reconstructed, while the momentum factor is dependent upon the regression models used. An analysis on some portfolios classified by the size of apartments and price volatility and/or beta values suggests that there are the positive linear relationships between risks and returns and the SMB factor is clearly found to be significant in determining the rate of returns. In particular, housing assets are highly highlighted as investment goods and/or quasi financial assets for the apartments to be constructed in the Gangnam housing.