• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.82-89
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• 2021

The objective of this study is to propose a new Glide Path that dynamically adjusts the risky asset inclusion ratio of the Target Date Fund by simultaneously considering the market's forecast volatility as well as the time of investor retirement, and to compare the investment performance with the traditional Target Date Fund. Forecasts of market volatility utilize historical volatility, time series model GARCH volatility, and the volatility index VKOSPI. The investment performance of the new dynamic Glide Path, which considers stock market volatility has been shown to be excellent during the analysis period from 2003 to 2020. In all three volatility prediction models, Sharpe Ratio, an investment performance indicator, is improved with higher returns and lower risks than traditional static Glide Path, which considers only retirement date. The empirical results of this study present the potential for the utilization of the suggested Glide Path in the Target Date Fund management industry as well as retirees.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.109-140
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• 2008

The primary objective of this paper investigates whether asymmetric volatility phenomenon is caused by differences of opinion among investors and analyses information availability has an effect on asymmetric volatility. The empirical test period covers recent 6 years from January 4, 2000 to December 29, 2005. Five portfolios have been formed according to information availability(volume and market value). For the purpose of this study, We use TGARCH model, TGARCH-M model and adjusted model which include trading volume as a proxy differences of opinion among investors. The results are summarized as follows ; First, adjusted model analysis shows that asymmetric volatility phenomenon is disappeared or asymmetric coefficient and ratio is decreased than basis model. Second, portfolio analysis shows that the higher volume and market value, the more prominent asymmetric volatility phenomenon. And adjusted model analysis shows the higher volume and market value, the more decrease asymmetric ratio. Over all, assertion that differences of opinion among investors has caused asymmetric volatility phenomenon is regarded as reasonable. And, We see that information availability have great effect on asymmetric volatility phenomenon. We think that theses results can also occur opinion adjustment of optimistic investors. Namely, asymmetric volatility phenomenon can occur difference of information authenticity.

• Journal of Korea Port Economic Association
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• v.23 no.1
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• pp.1-18
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• 2007

The purpose of this study is to examine the effect of exchange rate volatility on Trading Volume of Container of Korea, and to induce policy implication in the contex of GARCH and regression model. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply impulse response functions and variance decomposition to the structural model to estimate dynamic short run behavior of variables. The major empirical results of the study show that the increase in exchange rate volatility exerts a significant negative effect on Trading Volume of Container in long run. The results Granger causality based on an error correction model indicate that uni-directional causality between trading volume of container and exchange rate volatility is detected. This study applies impulse response function and variance decompositions to get additional information regarding the Trading Volume of Container to shocks in exchange rate volatility. The results indicate that the impact of exchange rate volatility on Trading Volume of Container is negative and converges on a stable negative equilibrium in short-run. Th exchange rate volatility have a large impact on variance of Trading Volume of Container, the effect of exchange rate volatility is small in very short run but become larger with time. We can infer policy suggestion as follows; we must make a stable policy of exchange rate to get more Trading Volume of Container

• Bulletin of the Korean Mathematical Society
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• v.60 no.2
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• pp.361-388
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• 2023

In this study, we deal with American lookback option prices on dividend-paying assets under a stochastic volatility (SV) model. By using the asymptotic analysis introduced by Fouque et al. [17] and the Laplace-Carson transform (LCT), we derive the explicit formula for the option prices and the free boundary values with a finite expiration whose volatility is driven by a fast mean-reverting Ornstein-Uhlenbeck process. In addition, we examine the numerical implications of the SV on the American lookback option with respect to the model parameters and verify that the obtained explicit analytical option price has been obtained accurately and efficiently in comparison with the price obtained from the Monte-Carlo simulation.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.157-169
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• 2018

The purpose of this study was to examine the volatility of bitcoin, diagnose if bitcoin are a systematic risk asset, and evaluate their effectiveness by estimating market beta representing systematic risk using GARCH (Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that the market beta of Bitcoin using the OLS model was estimated at 0.7745. Second, using GARCH (1, 2) model, the market beta of Bitcoin was estimated to be significant, and the effects of ARCH and GARCH were found to be significant over time, resulting in conditional volatility. Third, the estimated market beta of the GARCH (1, 2), AR (1)-GARCH (1), and MA (1)-GARCH (1, 2) models were also less than 1 at 0.8819, 0.8835, and 0.8775 respectively, showing that there is no systematic risk. Finally, in terms of efficiency, GARCH model was more efficient because the standard error of a market beta was less than that of the OLS model. Among the GARCH models, the MA (1)-GARCH (1, 2) model considering non-simultaneous transactions was estimated to be the most appropriate model.

• East Asian mathematical journal
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• v.33 no.1
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• pp.23-36
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• 2017

We study an optimization problem for HARA utility function under a multi-scale Heston's stochastic volatility model. We investigate a practical strategy that do not depend on the incorporated factor which is unobservable in the market.

• Bulletin of the Korean Mathematical Society
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• v.59 no.2
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• pp.507-528
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• 2022

We propose a path integral method to construct a time stepwise local volatility for the stock index market under Dupire's model. Our method is focused on the pricing with the Monte Carlo Method (MCM). We solve the problem of randomness of MCM by applying numerical integration. We reconstruct this task as a matrix equation. Our method provides the analytic Jacobian and Hessian required by the nonlinear optimization solver, resulting in stable and fast calculations.

• East Asian Journal of Business Economics (EAJBE)
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• v.6 no.3
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• pp.24-36
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• 2018

Purpose - From establishing China-Japan diplomatic relations in 1972, the relations between two states has improved a lot, from which makes the government and the people reap much benefit. Owing to this reason, this paper aims at exploiting the impact of exchange rate volatility of RMB on China's foreign direct investment to Japan. Research design and methodology - The quarterly time series data from 2003 to 2016 will be employed to conduct an empirical analysis under the vector error correction model. Meanwhile, a menu of estimated methods such the Johansen co-integration test and the Granger Causality test will be also used to explore the impact of exchange rate volatility of RMB on China's foreign direct investment to Japan. Results - The empirical analysis results exhibit that the real exchange rate has a positive effect on China's foreign direct investment to Japan in the long run. Conversely, the real exchange rate volatility of RMB, the trade openness and the real GDP have a negative effect on China's foreign direct investment to Japan in the long run. However, in the short run, the China's foreign direct investment to Japan, the real exchange rate, the trade openness and the real GDP in period have a negative effect on China's foreign direct investment to Japan in period. Oppositely, the real exchange rate volatility of RMB in period has a positive effect on China's foreign direct investment to Japan in period. Conclusions - From the empirical evidences in this paper provided, it can be concluded that an increase in the exchange rate volatility of RMB can result in a decrease in the China's foreign direct investment to Japan in the long run. However, an increase in the exchange rate volatility of RMB can lead to an increase in the China's foreign direct investment to Japan in the short run. Therefore, the China's government should have a best control of the real exchange rate volatility of RMB so as to improve China's foreign direct investment to Japan.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6511-6516
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• 2015

This paper examines the relationship between idiosyncratic volatility(IVOL) puzzle and trading volumes by trader types in the Korean stock market. The data set includes all stock in both KRX and KOSDAQ for the period from January 1999 through December 2013. Idiosyncratic volatility is measured by using the Fama-French's three-factor model. Traders are classified into individual, institution, and foreign trader. We construct (5X5) portfolios based on each trader's net buying and idiosyncratic volatility. We find that there are some special portfolios that show the idiosyncratic volatility puzzle. For individual investors, top net buying portfolios show clear the idiosyncratic volatility puzzle. However, for institution and foreign investors, lowest net buying portfolio show the idiosyncratic volatility puzzle. This results imply that the idiosyncratic volatility puzzle in the Korean stock market is mainly caused by individual investors.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.