• 대한수학회지
• /
• 제57권5호
• /
• pp.1167-1186
• /
• 2020

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

• 응용통계연구
• /
• 제33권3호
• /
• pp.297-308
• /
• 2020

본 논문에서는 고빈도 함수적 ARCH 모형을 소개하고 근사모형으로써 다변량 변동성 모형을 고려하였다. 이를 기반으로 함수형 변동성 분석에서 중요한 요소인 일중 로그 수익률의 적절한 시간 간격을 찾아보았다. 또한 함수적 ARCH 모형에서 l-시차 후 변동성 예측식을 제시하고 고빈도 KOSPI 자료에 적합하여 예시하였다.

• 응용통계연구
• /
• 제30권5호
• /
• pp.747-757
• /
• 2017

본 논문은 다변량 실현 변동성 계산에서 주기 선택 방안에 대해 연구하고 있다. 고빈도(high frequency) 시계열 자료에 기초한 일간 변동성인 실현변동성을 계산하고 차원 축소 방법인 주성분을 도입하였다. Cholesky 모형을 포함한 다양한 다변량 변동성모형을 주성분을 통해 비교하였으며 KOSPI/삼성전자/현대차 고빈도 수익률 자료를 이용하여 예시하였다.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권11호
• /
• pp.83-93
• /
• 2020

This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권3호
• /
• pp.31-38
• /
• 2021

The study investigates the diversification behavior of Islamic stocks against US financial uncertainty. Considering limitations found in the literature, a comprehensive index of financial uncertainty (FU) is used, developed by Jurado, Ludvigson, and Ng (2015). The empirical analysis uses monthly data from four Islamic markets - Saudi Arabia, Malaysia, Indonesia, and Turkey - for the period from January 2010 to September 2019. Results of the bivariate EGARCH models show that Islamic stocks can be used for diversification purpose against the financial uncertainty of the US because the volatility of US uncertainty does not propagate in the Islamic stock markets. Moreover, findings show that the spillover effect of financial uncertainty varies with the FU forecast horizon. The spillover effect of FU increases with an increase in the FU forecast horizon and becomes significant over 3-month and 12-month periods in the case of Saudi Arabia. The current volatility of Islamic stock returns is independent of the size of shocks in past volatility. The leverage effect and asymmetry have been found in Saudi Arabia and Malaysia. The findings validate the arguments of the literature that Islamic markets are resilient facing uncertainties and perform well during crisis periods. The findings are important for investors in making better portfolio decisions.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권1호
• /
• pp.15-22
• /
• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2022년도 학술발표회
• /
• pp.437-437
• /
• 2022

The prediction of dam inflow rate is crucial for the management of the largest multi-purpose dam in South Korea, the Soyang Dam. The main issue associated with the management of water resources is the stochastic nature of the reservoir inflow leading to an increase in uncertainty associated with the inflow prediction. The Autoregressive (AR) model is commonly used to provide the simulation and forecast of hydrometeorological data. However, because its estimation is based solely on the time-series data, it has the disadvantage of being unable to account for external variables such as climate information. This study proposes the use of the Autoregressive Exogenous Stochastic Volatility (ARXSV) model within a Bayesian modeling framework for increased predictability of the monthly dam inflow by addressing the exogenous and stochastic factors. This study analyzes 45 years of hydrological input data of the Soyang Dam from the year 1974 to 2019. The result of this study will be beneficial to strengthen the potential use of data-driven models for accurate inflow predictions and better reservoir management.

• 한국도로학회논문집
• /
• 제16권1호
• /
• pp.75-89
• /
• 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.

• Communications for Statistical Applications and Methods
• /
• 제30권2호
• /
• pp.163-178
• /
• 2023

GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

• Journal of the Korean Data and Information Science Society
• /
• 제28권2호
• /
• pp.251-260
• /
• 2017

Black와 Scholes (1973)와 Merton (1973)의 옵션 가격결정이론에 대한 논문이 발표 된 이후 다양한 실증 분석 결과에 의하여 시간의 흐름에 따라 변동성이 불변한다고 가정하는 Black-Scholes 모형이 시장의 옵션 가격을 적절히 설명하지 못하고 있다는 것이 밝혀지면서 많은 대안적인 연구들이 진행되어 왔다. 예를 들어, Duan (1995)은 위험중립측도 하에서의 몬테카를로 시뮬레이션을 통해 GARCH 모형을 따르는 기초 자산의 옵션가격을 도출하는 방법을 제시하였다. 그러나 실제 주식이나 환율 등의 금융자료에 수익률분포는 정규분포에 비해 꼬리가 두껍고, 급첨의 형태를 보이는 데 Duan (1995)의 옵션가격 결정 방법은 이를 적절히 반영하지 못하고 있다. 이를 해결하기 위해 본 논문에서는 정규혼합모형의 오차를 갖는 GARCH 모형을 이용한 옵션가격 결정 방법을 제안하고자 한다. KOSPI200 옵션가격 자료를 이용하여 본 논문에서 제시된 옵션가격과 정규분포를 가정한 GARCH 모형에 의해 결정된 옵션가격과 비교한 결과, 금융 자료의 급첨의 성질이 뚜렷한 불안정한 시기인 경우에 오차가 정규혼합모형이라고 가정한 GARCH 모형에 의한 옵션가격 결정의 성과가 월등히 좋아지는 것을 확인할 수 있었다.