Credit risk in covered bonds

Covered bonds are a promising alternative for prime mortgage securitization. In this paper, we explore risk premia in the covered bond market and particularly investigate whether and how credit risk is priced. In extant literature, yield spreads between high-quality covered bonds and government bonds are often interpreted as pure liquidity premia. In contrast, we show that although liquidity is important, it is not the exclusive risk factor. Using a hand-collected data set of cover pool information, we find that the credit quality of the cover assets is an important determinant of covered bond yield spreads. This effect is particularly strong in times of financial turmoil and has a significant influence on the issuer's refinancing cost.

Commodity futures prices: more evidence on forecast power, risk premia and the theory of storage

In this paper, we examine the temporal stability of the evidence for two commodity futures pricing theories. We investigate whether the forecast power of commodity futures can be attributed to the extent to which they exhibit seasonality and we also consider whether there are time varying parameters or structural breaks in these pricing relationships. Compared to previous studies, we find stronger evidence of seasonality in the basis, which supports the theory of storage. The power of the basis to forecast subsequent price changes is also strengthened, while results on the presence of a risk premium are inconclusive. In addition, we show that the forecasting power of commodity futures cannot be attributed to the extent to which they exhibit seasonality. We find that in most cases where structural breaks occur, only changes in the intercepts and not the slopes are detected, illustrating that the forecast power of the basis is stable over different economic environments.

The dynamics of commodity prices

In this paper we study the stochastic behavior of the prices and volatilities of a sample of six of the most important commodity markets and we compare these properties with those of the equity market. we observe a substantial degree of heterogeneity in the behavior of the series. Our findings show that it is inappropriate to treat different kinds of commodities as a single asset class as is frequently the case in the academic literature and in the industry. We demonstrate that commodities can be a useful diversifier of equity volatility as well as equity returns. Options pricing and hedging applications exemplify the economic impacts of the differences across commodities and between model specifications.

Handbook of research methods and applications in empirical finance

The objective of this book is to present the quantitative techniques that are commonly employed in empirical finance research together with real world, state of the art research examples. Each chapter is written by international experts in their fields. The unique approach is to describe a question or issue in finance and then to demonstrate the methodologies that may be used to solve it. All of the techniques described are used to address real problems rather than being presented for their own sake and the areas of application have been carefully selected so that a broad range of methodological approaches can be covered. This book is aimed primarily at doctoral researchers and academics who are engaged in conducting original empirical research in finance. In addition, the book will be useful to researchers in the financial markets and also advanced Masters-level students who are writing dissertations.

The importance of the volatility risk premium for volatility forecasting

In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.

Commodity price dynamics and derivatives valuation: a review

This paper reviews extant research on commodity price dynamics and commodity derivatives pricing models. In the first half, we provide an overview of stylized facts of commodity price behavior that have been explored and documented in the theoretical and empirical literature. In the second half, we review existing derivatives pricing models and discuss how the peculiarities of commodity markets have been integrated in these models. We conclude the paper with a brief outlook on important research questions that need to be addressed in the future.

Booms and busts in commodity markets: bubbles or fundamentals?

This paper considers whether there were periodically collapsing rational speculative bubbles in commodity prices over a 40-year period from the late 1960s. We apply a switching regression approach to a broad range of commodities using two different measures of fundamental values—estimated from convenience yields and from a set of macroeconomic factors believed to affect commodity demand. We find reliable evidence for bubbles only among crude oil and feeder cattle, showing the popular belief that the extreme price movements observed in commodity markets were caused by pure speculation to be unsustainable

Mycolactone-dependent depletion of endothelial cell thrombomodulin is strongly associated with fibrin deposition in buruli ulcer lesions

A well-known histopathological feature of diseased skin in Buruli ulcer (BU) is coagulative necrosis caused by the Mycobacterium ulcerans macrolide exotoxin mycolactone. Since the underlying mechanism is not known, we have investigated the effect of mycolactone on endothelial cells, focussing on the expression of surface anticoagulant molecules involved in the protein C anticoagulant pathway. Congenital deficiencies in this natural anticoagulant pathway are known to induce thrombotic complications such as purpura fulimans and spontaneous necrosis. Mycolactone profoundly decreased thrombomodulin (TM) expression on the surface of human dermal microvascular endothelial cells (HDMVEC) at doses as low as 2ng/ml and as early as 8hrs after exposure. TM activates protein C by altering thrombin’s substrate specificity, and exposure of HDMVEC to mycolactone for 24 hours resulted in an almost complete loss of the cells’ ability to produce activated protein C. Loss of TM was shown to be due to a previously described mechanism involving mycolactone-dependent blockade of Sec61 translocation that results in proteasome-dependent degradation of newly synthesised ER-transiting proteins. Indeed, depletion from cells determined by live-cell imaging of cells stably expressing a recombinant TM-GFP fusion protein occurred at the known turnover rate. In order to determine the relevance of these findings to BU disease, immunohistochemistry of punch biopsies from 40 BU lesions (31 ulcers, nine plaques) was performed. TM abundance was profoundly reduced in the subcutis of 78% of biopsies. Furthermore, it was confirmed that fibrin deposition is a common feature of BU lesions, particularly in the necrotic areas. These findings indicate that there is decreased ability to control thrombin generation in BU skin. Mycolactone’s effects on normal endothelial cell function, including its ability to activate the protein C anticoagulant pathway are strongly associated with this. Fibrin-driven tissue ischemia could contribute to the development of the tissue necrosis seen in BU lesions.

Time-variations in commodity price jumps

In this paper, we study jumps in commodity prices. Unlike assumed in existing models of commodity price dynamics, a simple analysis of the data reveals that the probability of tail events is not constant but depends on the time of the year, i.e. exhibits seasonality. We propose a stochastic volatility jump–diffusion model to capture this seasonal variation. Applying the Markov Chain Monte Carlo (MCMC) methodology, we estimate our model using 20 years of futures data from four different commodity markets. We find strong statistical evidence to suggest that our model with seasonal jump intensity outperforms models featuring a constant jump intensity. To demonstrate the practical relevance of our findings, we show that our model typically improves Value-at-Risk (VaR) forecasts.

Do jumps matter for volatility forecasting? Evidence from energy markets

This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high-frequency data on four prominent energy markets, we perform a model-free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in-sample and out-of-sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions

An empirical model comparison for valuing crack spread options

In this paper, we investigate the pricing of crack spread options. Particular emphasis is placed on the question of whether univariate modeling of the crack spread or explicit modeling of the two underlyings is preferable. Therefore, we contrast a bivariate GARCH volatility model for cointegrated underlyings with the alternative of modeling the crack spread directly. Conducting an empirical analysis of crude oil/heating oil and crude oil/gasoline crack spread options traded on the New York Mercantile Exchange, the more simplistic univariate approach is found to be superior with respect to option pricing performance.

Electricity derivatives pricing with forward-looking information

In order to increase overall transparency on key operational information, power transmission system operators publish an increasing amount of fundamental data, including forecasts of electricity demand and available capacity. We employ a fundamental model for electricity prices which lends itself well to integrating such forecasts, while retaining ease of implementation and tractability to allow for analytic derivatives pricing formulae. In an extensive futures pricing study, the pricing performance of our model is shown to further improve based on the inclusion of electricity demand and capacity forecasts, thus confirming the general importance of forward-looking information for electricity derivatives pricing. However, we also find that the usefulness of integrating forecast data into the pricing approach is primarily limited to those periods during which electricity prices are highly sensitive to demand or available capacity, whereas the impact is less visible when fuel prices are the primary underlying driver to prices instead.