• International Journal of Highway Engineering
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• v.16 no.1
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• pp.75-89
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• 2014

PURPOSES : This study evaluates the economic value of national highway construction projects using Real Option Pricing Models. METHODS : We identified the option premium for uncertainties associated with flexibilities according to the future's change in national highway construction projects. In order to evaluate value of future's underlying asset, we calculated the volatility of the unit price per year for benefit estimation such as VOTS, VOCS, VICS, VOPCS and VONCS that the "Transportation Facility Investment Evaluation Guidelines" presented. RESULTS : We evaluated the option premium of underlying asset through a case study of the actual national highway construction projects using ROPM. And in order to predict the changes in the option value of the future's underlying asset, we evaluated the changes of option premium for future's uncertainties by the defer of the start of construction work, the contract of project scale, and the abandon of project during pre-land compensation stages that were occurred frequently in the highway construction projects. Finally we analyzed the sensitivity of the underlying asset using volatility, risk free rate and expiration date of option. CONCLUSIONS : We concluded that a highway construction project has economic value even though static NPV had a negative(-) value because of the sum of the existing static NPV and the option premium for the future's uncertainties associated with flexibilities.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.121-134
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• 2021

Purpose - This study examines whether flight-to-liquidity (FTL) explains the dynamic liquidity risk on stock returns, and whether it has a significant influence on determinants the cross-section of stock returns. Design/methodology/approach - This study suggests a new risk factor, dynamic liquidity hedge portfolio (DLP), to reflect the dynamic impact of liquidity risk on stock returns and the Fama-MacBeth 2 stage regression analysis is employed in order to analyze the data. Findings - First, the DLP factor shows more positive and significant beta for the small or illiquidity stocks. Second, the DLP shows a different influence than SMB (size risk factor), HML (value risk factor), NMP (liquidity risk factor), FTVOL (total volatility factor) in determining the cross-section of stock returns. In addition, the DLP has a statistically significant risk premium of around 5%, which is relatively larger than other risk factors. Research implications or Originality - This study has academic value in terms of newly confirming that the DLP factor has a more significant impact on cross-sectional determination of stock returns than other risk factors by proposing a conditional liquidity factor that can explain the FTL phenomenon.

• The Korean Journal of Financial Studies
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• v.3 no.2
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• pp.329-364
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• 1996

Writing naked put options is a strategy employed either as a speculation to capture premium income, or as a method of placing a limit order to buy the underlying at the strike price in return for premium received. Using a Monte Carlo simulation, twenty thousand equity prices are generated under known volatility and return parameters. A binomial tree is constructed using the same volatility and return parameters. Put options on these 'equities' are valued with the binomial methodology. The performance of various put writing strategies is evaluated on a risk-adjusted basis. Evidence presented suggests that the judicious use of put options may enhance returns during portfolio construction.

• Economic Analysis
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• v.25 no.1
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• pp.1-33
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• 2019

This paper examines the economic factors that are related to the dynamics of the variance risk premium, and specially, which economic factors are related to the forecasting power of the variance premium regarding future index returns. Eleven general economic variables, eight interest rate variables, and eleven sentiment-associated variables are used to figure out the relevant economic variables that affect the variance risk premium. According to our empirical results, the won-dollar exchange rates, foreign reserves, the historical/implied volatility, and interest rate variables all have significant coefficients. The highest adjusted R-squared is more than 65 percent, indicating their significant explanatory power of the variance risk premium. Next, to verify the economic variables associated with the predictability of the variance risk premium, we conduct forecasting regressions to predict future stock returns and volatilities for one to six months. Our empirical analysis shows that only the won-dollar exchange rate, among the many variables associated with the dynamics of the variance risk premium, has a significant forecasting ability regarding future index returns. These results are consistent with results found in previous studies, including Londono (2012) and Bollerslev et al. (2014), which show that the variance risk premium is related to global risk factors.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.203-215
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• 2022

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

• The Korean Journal of Financial Management
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• v.26 no.4
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• pp.191-234
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• 2009

This study examined on the volatility feedback hypothesis through the use of threshold GARCH-in-Mean (GJR-GARCH-M) model developed by Glosten, Jaganathan, and Runkle (1993) in the stock markets of 14 emerging countries during the period of January, 1996 to May, 2009. On this study, I found successful evidences which can support the volatility feedback hypothesis through the following three estimation procedures. First, I found relatively strong positive relationship between the expected market risk premiums and their conditional standard deviations from the GARCH-M model in the basis of daily return on each representative stock market index, which is appropriate to investors' risk-averse preferences. Second, I can also identify the significant asymmetric time-varying volatility originated from the investors' differentiated reactions toward the unexpected market shocks by applying the GJR-GARCH-M model and further find the lasting positive risk aversion coefficient estimators. Third, I derived the negative signs of the regression coefficient of unpredicted volatility on the stock market return by re-applying the GJR-GARCH-M model after I controlled the positive effect of predicted volatility through including the conditional standard deviations from the previous GARCH-M model estimation as an independent explanatory variable in the re-applied new GJR-GARCH-M model. With these consecutive results, the volatility feedback effect was successfully tested to be effective also in the various emerging stock markets, although the leverage hypothesis turned out to be insufficient to be applied to another source of explaining the negative relationship between the unexpected volatility and the ex-post stock market return in the emerging countries in general.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.320-332
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• 2021

This paper investigates the influence of stock-level left-tail risk, which is defined using Value-at-Risk(VaR) estimates of past one-year daily stock returns, in the expected stock returns in the Korean stock market. Our results are summarized as follows: First, monthly-constructed zero-cost portfolios that buy (shortsell) the highest (lowest) left-tail risk decile in the previous month exhibit an average monthly return (called left-tail risk premium) of -2.29%. Second, Fama-MacBeth cross-sectional regressions suggest that left-tail risk in the previous month shows significant and negative explanatory power over return in this month, after controlling for various firm characteristics such as firm size, B/M, market beta, liquidity, maximum daily return, idiosyncratic volatility, and skewness. Third, the stocks with larger recent month loss have lower returns in the next month. Fourth, the magnitude of left-tail risk premium is negatively related with lagged market-level volatility. These results support the hypothesis from a perspective of behavioral finance that the overpricing of stocks with left-tail risk is attributed to the investors' underreaction to it.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.588-597
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• 2021

In Korea, the standard for calculating the profit of a general insurance, which constitutes the loading in the premium, is not specified, and most of the non-life insurance companies reflect 2~5% of the premium as profit margin. Although the transparency of pricing is required due to the nature of insurance products, there are insufficient standards and empirical studies on the determination of insurance price factors in the domestic insurance industry. In this study, we propose a method of calculating the expected profit margin of general insurance. A way for calculating the expected profit margin of the general insurance is to reflect the shareholder demand on the capital that the insurance company should secure against the risk of loss due to the profit/loss volatility, as a ratio to the insurance premium. Shareholders should be compensated for the risks associated with their insurance operations, and the opportunity cost of these shareholders is to be reflected in premiums. In this study, we calculate the amount of capital that the company should accumulate to prepare insurance risk for each product, and insurance risk is defined as the volatility of insurance operating profit/loss. And insurance risk is calculated using stochastic simulation based on Dynamic Financial Analysis (DFA) methodology. Finally, we calculate the expected profit margins for 25 products and analyzed the difference between those and the profit ratio of domestic general insurance.

• The Korean Journal of Financial Management
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• v.25 no.2
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• pp.69-101
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• 2008

We empirically investigate the option leverage property that should be priced under much more general conditions than the Black-Scholes assumptions and the option redundancy property that is based on the assumption that the underlying asset price follows a one-dimensional diffusion process and examine the systematic risk factors implied in the return dynamics of KOSPI 200 index options. We find that the option leverage pattern is similar to the theoretical result but the options are not redundant securities and in the nonlinear structure of option payoffs, the traders of KOSPI 200 index options price the systematic higher-moments and the negative volatility risk premium significantly affects delta-hedged gains, even after accounting for jump fears. But the empirical evidence on jump risk preference is less conclusive.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.75-106
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• 2007

In this study, it is analyzed whether oil price plays a major role in the pricing return on Koran stock market and examined why the covariance risk between oil and return on stock is different in each industry. Firstly, this study explores whether the expected rate of return on stock is pricing due to global oil price factors as a function of risk premium by using a two-factor APT. Also, it is examined whether spill-over effects of oil price volatility affect the beta risk to oil price. Considering the asymmetry of oil price volatility, we use the GJR model. As a result, it shows that oil price is an independent pricing factor and oil price volatility transmits to stock return in only electricity and electrical equipment. Secondly, the two step-analyzing process is introduced to find why the covariance between oil price factor and stock return is different in each industry. The first step is to study whether beta risk exists in each industry by using two proxy variables like size and liquidity as control variables. The second step is to grasp the systematic relationship between the difference of liquidity and size and beta to oil price factor by using the panel-data model which can be analyzed efficiently using the cross-sectional data formed with time series. Through the analysis, we can argue that oil price factor is an independent pricing factor in only electricity and electrical equipment having the greatest market capitalization, and know that beta risk to oil price factor is a proxy of size in the other industries. According to the result of panel-data model, it is argued that the beta to oil price factor augments when market capitalization increases and this fact supports the first assertion. In conclusion, the expected rate of return of electricity and electrical equipment works as a function of risk premium to market portfolio and oil price, and the reason to make beta risk power differentiated in each industry attributes to the size.