• Analyses & Alternatives
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• v.3 no.1
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• pp.135-157
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• 2019

The linkages between asset prices and macroeconomic outcomes are long-standing issue to both economists and monetary authorities. This paper explores the impact of asset prices on output and price in China. It focuses on the impacts of asset prices on the low quantiles of GDP gap and high quantiles of price gaprespectively. The main findings are the following: the influence of stock price gap, stock returns, and money growth on the different quantile of GDP gap and price gap are noticeable different, and there are significant impacts on the left tail of GDP gap distribution and on the right tail of price gap distribution. This implies that the results coming from simple regression will underestimate the economic risk imposed by asset price volatility. Moreover, these results also provide the caveat that one should cautiously distinguish the meaning of asset price gap and asset price growth rate and use them, through their contents are similar in some sense. One implication for monetarypolicy is that authority should interpret the relationship between asset prices and macro-economy in wider perspectives, and make the policy decision taking the impacts of asset prices on the tails of economy.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.432-439
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• 2013

In this study, we evaluate the volatility of housing prices by using literature review and empirical analysis and furthermore we suggest how to improve. In order to diagnose housing market, the KB Bank's House Price Index, Real estate 114;s materials were compared. In addition, to examine the volatility, GARCH (Generalized Autoregressive Conditional Heteroskedasticity) and EGARCH (Exponential GARCH) model are used. By analysis of this research, we found the volatility of housing price also was reduced in the medium and the large houses since 1998, while the volatility of small housing price relatively was large. We proved that the price change rate of small housing was higher than the medium's. On the order hand, the supply of small apartments fell down sharply. The short-term oriented policy should be avoided, and the efficiency and credibility of policy should be increased. Furthermore, the long-term policy system should be established. and rental market's improvement is necessary for stabilization of housing market.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.683-692
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• 2020

The primary purpose of the study is to investigate the volatility spillovers from global economic policy uncertainty and macroeconomic factors to the Islamic stock market returns. The study focuses on the Islamic stock indices of emerging economies including Indonesia, Malaysia, and Turkey. The Macroeconomic factors are industrial production, consumer price index, exchange rate. EGARCH model is employed for investigation of volatility spillovers. The results show that the global economic policy uncertainty has a significant spillover effect only on the returns of Turkish Islamic stock index. Similarly, the shocks in macroeconomic factors have little influence on the volatility of Islamic indices returns. The volatility of Indonesian and the Turkish Islamic stock indices returns is not influenced from the fluctuations in macroeconomic factors. However, there is significant volatility spillover only from industrial production to the returns of Malaysian Islamic index. The results suggest that the Islamic stock markets are less likely to influence from the global economic policies and macroeconomic factors. The stability of Islamic stocks provide opportunity for diversification of portfolios, particularly in stressed market conditions. The major price factors of Islamic markets could be firms' specific factors or investors' behaviors. The findings are helpful for policy makers and investors in formulating policies and portfolios.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.85-100
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• 2023

The stochastic volatility (SV) model is one of the main methods of modeling time-varying volatility. In particular, SV model is actively used in estimation and prediction of financial market volatility and option pricing. This paper attempts to model the time-varying volatility of the bitcoin market price using SV model. Hidden Markov model (HMM) is combined with the SV model to capture characteristics of regime switching of the market. The HMM is useful for recognizing patterns of time series to divide the regime of market volatility. This study estimated the volatility of bitcoin by using data from Upbit, a cryptocurrency trading site, and analyzed it by dividing the volatility regime of the market to improve the performance of the SV model. The MCMC technique is used to estimate the parameters of the SV model, and the performance of the model is verified through evaluation criteria such as MAPE and MSE.

• Korean Journal of Mathematics
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• v.23 no.1
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• pp.81-91
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• 2015

This paper is about the local volatility for the price of a European quanto call option. We derive the explicit formula of the local volatility with constant foreign and domestic interest rates by adapting the methods of Dupire and Derman & Kani. Furthermore, we obtain the Dupire equation for the local volatility with stochastic interest rates.

• Communications of the Korean Mathematical Society
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• v.29 no.3
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• pp.489-496
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• 2014

We drive a closed-form expression for the price of a European quanto call option in the double square root stochastic volatility model.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.305-308
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• 2009

According to the returns of Housing and business cycle over the period 1992 to 2007, it is a measure of the total volatility faced by investors in Housing properties. First, it isn't a distinct difference from business cycle contrary to U.S. Second, the rise of purchase price in total apartments moves up the consumer price index. According to the cross-sectional dispersion of returns and growth in net operating income (NOI) of apartments, industrial, retail and office properties using panel data for U.S. metropolitan areas over the period 1986 to 2002, it is a measure of the total volatility faced by investors in commercial real estate. To the extent that most of that volatility is difficult to diversify, cross-sectional dispersion may be an appropriate measure of risk.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.2
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• pp.123-135
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• 2016

This article deals with the pricing of Asian options under a constant elasticity of variance (CEV) model as well as a stochastic elasticity of variance (SEV) model. The CEV and SEV models are underlying asset price models proposed to overcome shortcomings of the constant volatility model. In particular, the SEV model is attractive because it can characterize the feature of volatility in risky situation such as the global financial crisis both quantitatively and qualitatively. We use an asymptotic expansion method to approximate the no-arbitrage price of an arithmetic average Asian option under both CEV and SEV models. Subsequently, the zero and non-zero constant leverage effects as well as stochastic leverage effects are compared with each other. Lastly, we investigate the SEV correction effects to the CEV model for the price of Asian options.

• Journal of Integrative Natural Science
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• v.4 no.2
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• pp.121-129
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• 2011

The purpose of this paper is to estimate the fluctuation of an earning rate and risk management using the price index of Korea stocks. After an observation of conception of fluctuation, we can show volatility clustering and fluctuation phenomenon in the Korea stock price index using GARCH model with heteroscedasticity. In addition, the effects of fluctuation on the time-series was evaluated, which showed the heteroscedasticity. MCMC method and Winbugs as Bayesian computation were used for analysis.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.175-194
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• 2004

Volumes of research have been implemented to estimate and predict the oil price. These models, however, fail in accurately predicting oil price as a model composed of only a few observable variables is limiting. Unobservable variables and news that have been overlooked in past research, yet have a high likelihood of affecting the oil price. Hence, this paper analyses the news impact on the price. The standard GARCH model fails in capturing some important features of the data. The estimated news impact curve for the GARCH model, which imposes symmetry on the conditional variances, suggests that the conditional variance is underestimated for negative shocks and overestimated for positive shocks. Hence, this paper introduces the asymmetric or leverage volatility models, in which good news and bad news have different impact on volatility. They include the EGARCH, AGARCH, and GJR models. The empirical results showed that negative shocks introduced more volatility than positive shocks. Overall, the AGARCH and GJR were the best at capturing this asymmetric effect. Furthermore, the GJR model successfully revealed the shape of the news impact curve and was a useful approach to modeling conditional heteroscedasticity.