Volatility transmission between Dow Jones Stock Index and Emerging Bond Index

In this paper, we use a bivariate GARCH model to estimate simultaneously of the mean and the conditional variance between the Dow Jones stock index and some emerging bond indices. We used the DCC-GARCH model to graphically demonstrate the peaks of the volatility transmission. We examined this transmission using daily returns between July, 30, 2009 and January, 18, 2011 extracted from Datastream. Our results demonstrate that there is a significant transmission of shocks and volatility between the Dow Jones stock index and bond indices of the emerging countries. The results also confirm the idea that the crisis was transmitted from the United States to the emerging countries due to foreign investment made in these countries

Should Stock Market Indexes Time Varying Correlations Be Taken Into Account? A Conditional Variance Multivariate Approach

The episodes of stock market crises in Europe and the U.S.A.since the year 2000,and the fragility of the international stock markets,have sparked the interest of researchers in understanding and in modeling the marketsâ rising volatilities in order to prevent against crises.Portfolio managers typically rely on estimates of correlations between returns on the financial instruments in the portfolio and on the volatility of those returns.This task is relatively simple if the correlations and volatilities do not change over time.But in reality both volatility and stock market indexesâ correlations do change over time. In this paper we examine the major stock market indexesâ rising volatilities, and we show that time varying correlations should be taken into account when modeling those indexes.We find that all of the indexes that we examine exhibit relatively time varying correlations with the other indexes and we find a strong GARCH effect in all of the examined series.Conditional Variance,Time Varying Correlations,Volatility,Conta- gion,VAR.

Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets

This paper analyzes the relationships between local and global securitized real estate markets, but also between securitized real estate and common stock markets. First, the volatility transmissions across markets are examined using an asymmetric t-BEKK (Baba-Engle-Kraft-Kroner) specification of their covariance matrix. Second, correlations from that model and tail dependences estimated using a time-varying copula framework are analyzed to assess whether different dynamics underlie the comovements in the whole distribution and those in the tails. Third, we investigate market contagion by testing for structural changes in the tail dependences. We use data for the U.S., the U.K. and Australia for the period 1990-2010 as a basis for our analyses. Spillover effects are found to be the largest in the U.S., both domestically and internationally. Further, comovements in tail distributions between markets appear to be quite important. We also document different dynamics between the conditional tail dependences and correlations. Finally, we find evidence of market contagion between the U.S. and the U.K. markets following the subprime crisi

Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH

While much research uses multivariate GARCH to model volatility dynamics and risk measures, one particular type of multivariate GARCH model, GO-GARCH, has been underutilized. This paper uses DCC, ADCC and GO-GARCH to model volatilities and conditional correlations between emerging market stock prices, oil prices, VIX, gold prices and bond prices. A rolling window analysis is used to construct out-of-sample onestep-ahead forecasts of dynamic conditional correlations and optimal hedge ratios. In most of the situations we study, oil is the best asset to hedge emerging market stock prices. Hedge ratios from the ADCC model are preferred (most effective) for hedging emerging market stock prices with oil, VIX, or bonds. Hedge ratios estimated from the GO-GARCH are most effective for hedging emerging market stock prices with gold in some instances. These results are reasonably robust to choice of model refits, forecast length and distributional assumptions

Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH

While much research uses multivariate GARCH to model volatility dynamics and risk measures, one particular type of multivariate GARCH model, GO-GARCH, has been underutilized. This paper uses DCC, ADCC and GO-GARCH to model volatilities and conditional correlations between emerging market stock prices, oil prices, VIX, gold prices and bond prices. A rolling window analysis is used to construct out-of-sample onestep-ahead forecasts of dynamic conditional correlations and optimal hedge ratios. In most of the situations we study, oil is the best asset to hedge emerging market stock prices. Hedge ratios from the ADCC model are preferred (most effective) for hedging emerging market stock prices with oil, VIX, or bonds. Hedge ratios estimated from the GO-GARCH are most effective for hedging emerging market stock prices with gold in some instances. These results are reasonably robust to choice of model refits, forecast length and distributional assumptions

How the Quantitative Easing Affect the Spillover Effects between the Metal Market and United States Dollar Index?

This study explores both return and volatility spillover effects, the co-integration relation and the correlative relationship between the metal market in London metal exchange and United States exchange rate market, and the risk premium and leverage effect in each of these two markets for the periods before and during quantitative easing (QE). Empirical results show that, as the QE is executed the risk premium in US exchange rate market will disappear; and the speed and direction of the adjustment back to equilibrium respectively becomes greater and is reversed for the co-integration relation in metal market. Regarding these two markets only the return spillover effect is affected, and the degree of negative correlative relationship becomes more obvious as the QE is executed

Dynamic linkages and propagation mechanisms among Asian stock markets: an analysis of the pre- and post-1997–98 financial crisis

This thesis analyses dynamic interdependence, volatility transmission and market integration across eight selected Asian stock markets from 1992 to 2007. Various methodologies are applied to test such relationships. In particular, the focus is given to the impact of the 1997–98 Asian financial crisis on the dynamic linkages and propagation mechanisms among these selected Asian equity markets. The techniques of unit root testing, cointegration, vector error correction modelling (VECM) and forecast error variance decomposition (VDC) analysis are initially performed in both whole sample period and four sub-sample periods (namely pre-crisis, crisis, post-crisis and recovery periods). The results suggest that Asian stock markets are highly integrated and the crash has brought a greater interaction amongst markets. Japan, Hong Kong and Singapore appear to play the relative leading role over other markets. Furthermore, the characteristics of stock volatility are then examined using univariate TAR-GARCH model. The results show that volatility is time-varying and bad news will generate more volatility than good news. Additionally, the empirical findings show the existence of day of week effects in returns and volatility in emerging markets before but not after the crisis. This suggests improved post-crash market efficiency in Asian emerging markets. [Continues.

Multivariate financial econometrics: with applications to volatility modelling, option pricing and asset allocation

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