Volatility spillovers between oil prices and the stock market under structural breaks

This paper employs univariate and bivariate GARCH models to examine the volatility of oil prices and US stock market prices incorporating structural breaks using daily data from July 1, 1996 to June 30, 2013. We endogenously detect structural breaks using an iterated algorithm and incorporate this information in GARCH models to correctly estimate the volatility dynamics. We find no volatility spillover between oil prices and US stock market when structural breaks in variance are ignored in the model. However, after accounting for structural breaks in the model, we find strong volatility spillover between the two markets. We compute optimal portfolio weights and dynamic risk minimizing hedge ratios to highlight the significance of our empirical results which underscores the serious consequences of ignoring these structural breaks. Our findings are consistent with the notion of cross-market hedging and sharing of common information by financial market participants in these markets.     

Detecting structural breaks and identifying risk factors in hedge fund returns: A Bayesian approach

Extending previous work on asset-based style factor models, this paper proposes a model that allows for the presence of structural breaks in hedge fund return series. We consider a Bayesian approach to detecting structural breaks occurring at unknown times and identifying relevant risk factors to explain the monthly return variation. Exact and efficient Bayesian inference for the unknown number and positions of the breaks is performed by using filtering recursions similar to those of the forward–backward algorithm. Existing methods of testing for structural breaks are also used for comparison. We investigate the presence of structural breaks in several hedge fund indices; our results are consistent with market events and episodes that caused substantial volatility in hedge fund returns during the last decade.     

IDENTIFYING REGIME CHANGES IN MARKET VOLATILITY

A casual inspection of a graph of volatility indexes over time indicates that volatility has undergone infrequent, but significant, shifts in its average level. The purpose of this article is to test for multiple structural breaks in the mean level of market volatility measured by the VIX and VXO, and to identify statistically the dates of these mean shifts. We find evidence of three distinct periods: pre‐1992, 1992–1997, and post‐1997. We find that the mean volatility, as well as its standard deviation, was lowest during 1992–1997. Our findings provide statistical evidence consistent with popular beliefs that market volatility changes over time.     

Sovereign CDS Spreads,Volatility, and Liquidity: Evidence from 2010 German Short Sale Ban

The paper examines global impact of 2010 German short sale ban on sovereign credit default swap (CDS) spreads, volatility, and liquidity across 54 countries. We find that CDS spreads continue rising after the ban in the debt crisis region, which suggests that the short selling ban is incapable of suppressing soaring borrowing costs in these countries. However, we find that the ban helps stabilize the CDS market by reducing CDS volatility. The reduction in CDS volatility is greater in the eurozone than that in the non‐eurozone. Furthermore, we find that the CDS market liquidity has been impaired during the ban for the PIIGS (Portugal, Ireland, Italy, Greece, and Spain) countries. In contrast, there are no dramatic changes in the market liquidity for non‐PIIGS eurozone and non‐eurozone samples. The findings suggest that the short sale ban is ineffective to reduce sovereign borrowing costs in the debt crisis region if the underlying economy has not been significantly improved.     

World War II events and the Dow Jones industrial index

This paper investigates which events of World War II (WWII) the US investors (at that time) considered as turning points (structural breaks) of the war. The empirical study employs daily Dow Jones industrial average stock index and volatility from January 1939 to December 1945 and applies structural shift oriented test to determine endogenously the structural breaks during the WWII period. Results show that the majority of the wartime events (on and off the battlefield) labelled important by historians did result in structural breaks in both price movement and stock returns volatility (risk). These results have major implications for investors of the present and future.     

Long memory versus structural breaks in modeling and forecasting realized volatility

We explore the possibility of structural breaks in the daily realized volatility of the Deutschemark/Dollar, Yen/Dollar and Yen/Deutschemark spot exchange rates with observed long memory behavior. We find that structural breaks in the mean can partly explain the persistence of realized volatility. We propose a VAR-RV-Break model that provides superior predictive ability when the timing of future breaks is known. With unknown break dates and sizes, we find that a VAR-RV-I(d) long memory model provides a robust forecasting method even when the true financial volatility series are generated by structural breaks.     

Modelling sovereign credit spreads with international macro-factors: The case of Brazil 1998–2009

This paper develops a macro-finance model of the Brazilian economy and its sovereign debt markets that allows for domestic and international macroeconomic influences as well as swings in investor confidence. It finds significant evidence of common trends in the US and Brazilian economies and bond markets as well as spillover effects from US inflation and business cycles to the Brazilian economy. The US Fed Funds rate influences Brazilian sovereign spreads, as do Brazilian inflation and policy rates. The Brazilian confidence factor dominates the behavior of the spreads during periods of crisis and we find that it also has a powerful effect on the level and volatility of macroeconomic variables. These results suggest that the macro-finance approach could throw light upon the behavior of other economies that are troubled by sovereign risk.     

Estimating Volatility Persistence in Oil Prices Under Structural Breaks

Policy makers and financial market participants are interested in knowing how shocks affect the volatility of oil prices over time. We accurately compute the volatility persistence by incorporating endogenously determined structural breaks into a GARCH model. Contrary to previous findings, we find that oil shocks dissipate very quickly but have a strong initial impact. Understanding this behavior is not only important for derivative valuation and hedging decisions but for broader financial markets and the overall economy, for which there are significant consequences.     

Has the CDS market influenced the borrowing cost of European countries during the sovereign crisis?

This paper assesses the potential influence of the growing CDS market on the borrowing cost of sovereign states during the European sovereign crisis. We analyze the sovereign debt market to ascertain the pattern of information transmission between the CDS and corresponding bond markets. Our methodological innovation is the use of a non-linear specification rather than the linear VECM specification customarily employed. Using a panel smooth transition model during the 2008–2010 period, we find that: 1) linearity tests clearly reject the null hypothesis of a linear transmission mechanisms between the bond and the CDS markets; 2) market distress alters the mutual influence and 3) the higher the distress the more the CDS market dominates the information transmission between CDS and bond markets.     

Treasury Bond Volatility and Uncertainty about Monetary Policy

We show that dispersion‐based uncertainty about the future course of monetary policy is the single most important determinant of Treasury bond volatility across all maturities. The link between Treasury bond volatility and uncertainty about macroeconomic variables is much stronger than for the more traditional time series measures of macroeconomic volatility and adds beyond the information contained in lagged bond market volatility. Uncertainty about monetary policy subsumes the uncertainty about future inflation (consumer price index and the deflator) and economic activity (unemployment, real and nominal gross domestic product and industrial production). In addition, causality clearly runs one way: from monetary policy uncertainty to Treasury bond volatility.     

Can Managers Successfully Time the Maturity Structure of Their Debt Issues?

This paper provides a rational explanation for the apparent ability of managers to successfully time the maturity of their debt issues. We show that a structural break in excess bond returns during the early 1980s generates a spurious correlation between the fraction of long‐term debt in total debt issues and future excess bond returns. Contrary to Baker, Taliaferro, and Wurgler (2006) , we show that the presence of structural breaks can lead to nonsense regressions, whether or not there is any small sample bias. Tests using firm‐level data further confirm that managers are unable to time the debt market successfully.     

Cross‐Border Auction Cycle Effects of Sovereign Bond Issuance in the Euro Area

We provide evidence for the euro area of spillovers from foreign public debt auctions into domestic secondary‐market auction cycles. We also confirm existing evidence of such spillovers from domestic issues into the domestic secondary market. Consistent with a theory of primary dealers’ limited risk‐bearing capacity, we find that auction cycles from domestic issues are stronger during the recent crisis period, whereas cross‐border effects are stronger in the precrisis period, but this evidence is not strong. This finding likely reflects the opposing effects of reduced sovereign bond market integration during the crisis and higher yield covariances caused by more market volatility.     

Volatility dependences of stock markets with structural breaks

We develop a Vector Heterogeneous Autoregression model with Continuous Volatility and Jumps (VHARCJ) where residuals follow a flexible dynamic heterogeneous covariance structure. We employ the Bayesian data augmentation approach to match the realised volatility series based on high-frequency data from six stock markets. The structural breaks in the covariance are captured by an exogenous stochastic component that follows a three-state Markov regime-switching process. We find that the stock markets have higher volatility dependence during turmoil periods and that breakdowns in volatility dependence can be attributed to the increase in market volatilities. We also find positive correlations between the Asian stock markets, the European stock market, and the UK stock market. The US stock market has positive correlations with all other markets for most of the sample periods, indicating the leading position of US stock market in the global stock markets. In addition, the proposed three-state VHARCJ model with Dynamic Conditional Correlation (DCC) and break structure under student-t distribution has a superior density forecast performance as compared to the competing models. The forecast models with structural breaks outperform those without structural breaks based on the log predicted likelihood, the log Bayesian factor, and the root mean square loss function.     

Physical delivery versus cash settlement: an empirical study on the feeder cattle contract

This paper investigates the effects of the switch from physical delivery to cash settlement on the behavior of the cash and futures prices of the feeder cattle contract traded on the Chicago Mercantile Exchange. A bivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model is applied to estimate the conditional volatility structure, with a possible structural break due to the switch to cash settlement. The results show that the volatility of the futures prices (but not the cash prices) declined after physical delivery was replaced by cash settlement. In terms of futures hedging, cash settlement led to smaller and more stable hedge ratios. The variance of the hedged portfolio also decreased substantially. The evidence suggests that cash settlement is beneficial to the feeder cattle futures market.     

Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models

This paper examines the dynamic relationship between the oil market and stock markets from two perspectives: dependence between the crude oil market (WTI) and stock markets of the US and China, and volatility spillovers between them during 1991–2016. We further analyze structural breaks of market dependences and consider the extent of their influence on such relationships. Our vine-copula results show that the dependences between the three paired markets, WTI-US, WTI-China and US-China, vary dynamically across the six identified structural break periods. In particular, the dependence between WTI-US is stronger and more volatile than that between WTI-China during most of the periods. The dependence between US-China remains at a lower level in the earlier periods, but increases in the final period. Our VAR-BEKK-GARCH results demonstrate distinctive volatility spillovers across these periods, with varying directionality, in response to the structural changes. Overall, our results indicate that the oil market stimulates rapid and continual fluctuations in market dependences, which become manifest most acutely in the aftermath of the Financial Crisis of 2007–08, demonstrating the increasing interdependence between the oil and stock markets. Further, the growing influence of China on the dynamics of these relationships, in the period following the Great Recession, presents evidence that it begins to assume an increasingly important role in global economic recovery.     

Volatility‐Spillover Effects in European Bond Markets

Volatility spillover from the US and aggregate European bond markets into individual European bond markets using a GARCH volatility‐spillover model is analysed. Strong statistical evidence of volatility spillover from the US and aggregate European bond markets is found. For EMU countries, the US volatility‐spillover effects are rather weak (in economic terms) whereas the European volatility‐spillover effects are strong. The bond markets of EMU countries have become much more integrated after the introduction of the euro, and in recent years they have become close to being perfectly integrated. The main driver of the integration appears to be convergence in interest rates.     

Forecasting value‐at‐risk in oil prices in the presence of volatility shifts

Recent evidence suggests shifts (structural breaks) in the volatility of returns causes non‐normality by significantly increasing kurtosis. In this paper, we endogenously detect significant shifts in the volatility of oil prices and incorporate this information to estimate Value‐at‐Risk (VaR) to accurately forecast large declines in oil prices. Our out‐of‐sample performance results indicate that the model, which incorporates both time varying volatility (without making any distributional assumptions) and shifts in volatility, produces more accurate VaR forecasts than several benchmark methods. We make a timely contribution as the recent more frequent occurrences of unexpected large oil price declines has gained significant attention because of its substantial impact on the financial markets and the global economy.     

The network structure of the CDS market and its determinants

This paper analyses the network structure of the credit default swap (CDS) market and its determinants, using a unique dataset of bilateral notional exposures on 642 financial and sovereign reference entities. We find that the CDS network is centred around 14 major dealers, exhibits a “small world” structure and a scale-free degree distribution. A large share of investors are net CDS buyers, implying that total credit risk exposure is fairly concentrated. Consistent with the theoretical literature on the use of CDS, the debt volume outstanding and its structure (maturity and collateralization), the CDS spread volatility and market beta, as well as the type (sovereign/financial) of the underlying bond are statistically significantly related—with expected signs—to structural characteristics of the CDS market.     

The Risk Microstructure of Corporate Bonds: A Case Study from the German Corporate Bond Market

This article presents joint econometric analysis of interest rate risk, issuer‐specific risk (credit risk) and bond‐specific risk (liquidity risk) in a reduced‐form framework. We estimate issuer‐specific and bond‐specific risk from corporate bond data in the German market. We find that bond‐specific risk plays a crucial role in the pricing of corporate bonds. We observe substantial differences between different bonds with respect to the relative influence of issuer‐specific vs. bond‐specific spread on the level and the volatility of the total spread. Issuer‐specific risk exhibits strong autocorrelation and a strong impact of weekday effects, the level of the risk‐free term structure and the debt to value ratio. Moreover, we can observe some impact of the stock market volatility, the respective stock's return and the distance to default. For the bond‐specific risk we find strong autocorrelation, some impact of the stock market index, the stock market volatility, weekday effects and monthly effects as well as a very weak impact of the risk‐free term structure and the specific stock's return. Altogether, the determinants of the spread components vary strongly between different bonds/issuers.     

Dynamic volatility spillover effects between oil and agricultural products

The strong volatility spillover between crude oil and agricultural commodity markets reduces the diversification benefits and implies costly risk management process faced by portfolio managers and agricultural producers. This paper proposes a comprehensive study of their dynamic implied volatility spillover effects after the global financial crisis 2008–2009, while considering the transition between oil volatility's regimes. By using implied volatility, our analysis emphasizes on the forward-looking information that market traders usually convey in making decisions. We employ the generalized spillover indices within a fractionally integrated VAR model to capture the dynamic patterns of the volatility spillover effects alongside the Markov Switching Autoregressive model to extract the regimes of oil. Our results show new evidence that the net volatility spillover effect from crude oil to all agricultural commodities tends to decrease when crude oil remains in its low volatility regime. Conversely, this effect experiences an increasing trend when crude oil remains in its relatively high volatility regime. A dynamic strategy that combines oil and the most balanced agricultural commodity in terms of volatility transmission with oil (i.e., close-to-zero net volatility spillovers) depending on oil's regimes consistently outperforms the buy and hold strategy in terms of information ratio.