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This paper tries to empirically investigate whether the jump risk of Korean stock market may be statistically useful in explaining the Korean CDS (5Y) premium rate. This paper uses the jump-diffusion model with heteroscedasticity to estimate the conditional volatility of KOSPI from 7/2/2007 to 7/30/2010.

The total volatility of Korean stock market is decomposed into a heteroscedasticity and a jump risk by using the jump-diffusion model. The finding is that the jump risk in stead of heteroscedasticity in Korean stock market can explain the Korean CDS premium rate.

In this paper, we try to extend the work of Kim and Chang (2000) and to estimate exponential-affine term structure models for Korean monetary stabilization bond (MSB) using trading data as an alternative of traditional curve-fitting methodology. We estimate both one factor CIR model and two factor CIR model. Using the daily trading data instead of quoted data of Korean monetary stabitization bond from February 10 1992 to September 8 2000, this paper estimates one factor successfully, which is consistent result with quoted data. But it seems that the result of two factor model from the trading data is not the same as that from the quoted data.

This paper examines the inflation hedging performance separated into expected and unexpected inflation in Korean equity funds. In particular, using the bootstrap approach, we identify whether the inflation hedging performance is based on skill or luck. We use the equity funds of the average net asset value (NAV) over 5 billion Korean won and over the 80% stock position. The sample data cover the period from January 2002 to March 2015. The main findings are as follows. First, most equity funds demonstrate a hedging performance against the unexpected inflation shock and this hedging performance seems to come from the fund manager’s skill. Second, our findings are robust across the sieve bootstrap results for the serial dependence and heteroscedasticity. Third, the equity funds have slightly different inflation hedging performances depending on their investment style. Among the investment styles, small-cap, growth, or small and growth style funds demonstrate more hedging performance against unexpected inflation shock. This hedging performance seems to come from the fund manager’s skill. Finally, in the case of the funds separated by winner and loser, the winner funds have more hedging performance for unexpected inflation shock than the loser funds.

This study examines whether KOSPI200 intra-day return has jump risk and heteroscedasticity and we compare the estimation result of intra-day return and that of daily return. The sample covers from January 2, 2004 to July 31, 2014. We use 30-minute intervals for measuring KOSPI200 intra-day return. It seems this study finds the importance of the consideration of the intra-day data in Korean Stock Market. While some of the parameters of the daily returns for the jump are not significant, but those of intra-day returns are significant over the sample period. Also, the intra-day volatility has shown U-shaped or reverse J-shaped curve. In particular the pattern of intra-day volatility seems to come from the jump risk, which is interpreted as the information inflow in the market.

This paper tries to empirically investigate whether the information contained in trading volume, volume volatility of Won/Dollar currency futures may be statistically useful in forecasting currency spot return. This paper uses both the jump-diffusion GARCH model and the bivariate GARCH type BEKK model to estimate the trading volume volatility of currency futures and the volatility of currency spot, sampled daily during 1/4/2000~12/30/2009 period. According to the findings of this study, previous information contained in both trading volume and the volume volatility of Won/Dollar currency futures might be useful in explaining the future return of the currency spot.

This paper discusses theoretical extensions of the implied volatility method of Dupire (1994) when the stock prices follow the Geometric Levy process. For the extensions of Kolmogorov forward equation for Levy process, this paper uses adjoint operator in L² spaces. This paper obtains similar results of Dupire (1994) and Andersen and Andreasan (2001). However, our results can be applied to more general semi-martingale processes such as well-known VG (Variance Gamma) model and NIG (Normal Inverse Gaussian) model with diffusion processes. This paper also applies the approach to the case of stochastic time changed Levy process, which generates the stochastic volatility models.

In this paper, we examine which volatility estimation model best explains KOSPI200-realized volatility in the Korean stock market, which has both heteroscedasticity and jump risk. The sample covers from July 1, 2010 to July 31, 2014, which is a low-volatility period in Korean stock market by which time the effects of the global crisis had almost vanished. We use the intra-day return of KOSPI200, which has been measured by 5-minute intervals. This study finds GARCH-family models are efficient estimators compared to historical volatility and EWMA. Also, among the GARCH-family models, Jump-Diffusion GARCH has shown comparatively good results. Especially this study finds that VKOSPI200 is the most efficient model with the largest adj. R2 and the smallest evaluation statistics during the sample period. Meanwhile, it seems to be necessary to consider jump risk when we estimate volatility in Korean stock market.

This paper tries to estimate multivariate latent factor model with jump in order to find common factor and jump risk of KOSDAQ markets. Using five major daily KOSDAQ indexes such as construction, wholesale, transportation, finance, and IT/SW/SVC from January 2 2003 to August 29 2008, this study finds the evidence of significant systematic jump risk in addition to industry-specific idiosyncratic risk. According to the main estimated results of this paper, jump risk comes every 31 trading days in KOSDAQ markets and approximately twenty percent of the common factor of the KOSDAQ market can be explained by the KOSPI market risk.

This paper tries to empirically investigate whether macroeconomic risk may be statistically useful in explaining long-term volatility of interest rate swap (IRS) in korean market. This paper uses the component-jump model to estimate long-term volatility of IRS from 1/2/2003 to 1/31/2013.

By using the component-jump model, the IRS volatility is decomposed into a long-term and a short-term component. According to this study, slope of yield curve and foreign exchange volatility as a proxy of macroeconomic risk have been significant in explaining long-term volatility of IRS.

This paper tries to estimate the dynamic linear latent factor model (DLLFM) with jump in order to find jump risk, heteroscedasticity and time varying correlations in Global REITs Markets.

Using five major Global Reits rates such as the United States, Japan, the United Kingdom, Australia and Hong Kong form January 4, 2000 to June 29, 2018, this study finds the evidence of common factor and time-varying correlations in addition to the country-specific idiosyncratic risk.

According to the main estimated results of this paper, approximately 60% of the common factors of global REITs market risk. Can be explained by global stock markets.

Second, REITs market integration among five countries seems to have been increasing gradually since Global Financial Crisis.