Basket Options on Heterogeneous Underlying Assets

Basket options are among the most popular products of the new generation of exotic options. This attraction is explained by the fact that they can efficiently and simultaneously hedge a wide variety of intrinsically different financial risks. They are flexible enough to include all the risks faced by non-financial firms. Unfortunately, the existing literature on basket options considers only homogeneous baskets where all the underlying assets are identical and hedge the same kind of risk. Moreover, the empirical implementation of basket-option models is not yet well developed, particularly when they are composed of heterogeneous underlying assets. This paper focus on the modelization and the parameters estimation of basket options on commodity price with stochastic convenience yield, exchange rate, and domestic and foreign zero-coupon bonds in a stochastic interest rates setting. We empirically compare the performance of the heterogeneous basket option to that of a portfolio of individual options. The results show that the basket strategy is less expensive and more efficient. We apply the maximum-likelihood method to estimate the different parameters of the theoretical basket model as well as the correlations between the variables. Monte Carlo studies are conducted to examine the performance of the maximum-likelihood estimator in finite samples of simulated data. A real data study is presented.Basket options, maximum likelihood, hedging performance, options pricing, Monte Carlo simulation

Heterogeneous Basket Options Pricing Using Analytical Approximations

This paper proposes the use of analytical approximations to price an heterogeneous basket option combining commodity prices, foreign currencies and zero-coupon bonds. We examine the performance of three moment matching approximations: inverse gamma, Edgeworth expansion around the lognormal and Johnson family distributions. Since there is no closed-form formula for basket options, we carry out Monte Carlo simulations to generate the benchmark values. We perfom a simulation experiment on a whole set of options based on a random choice of parameters. Our results show that the lognormal and Johnson distributions give the most accurate results.Basket Options, Options Pricing, Analytical Approximations, Monte Carlo Simulation

Giemsa versus acridine orange staining in the fish micronucleus assay and validation for use in water quality monitoring

This study concerns a comparative analysis of the acridineorange and Giemsastaining procedures for the fish erythrocyte micronucleusassay. The goal was to optimize the assay in the context of field watermonitoring. Fish (Carassius carassius) were exposed to a reference genotoxic agent, cyclophosphamide monohydrate 5 mg l−1 for 2, 4, and 6 days before testing. Slides from each individual were scored using the two procedures. The results show that the assay was more sensitive when acridineorange was used. When slides were Giemsa stained, the presence of ambiguous artefacts, leading to false positives and increasing random variance, reduced the contrast between exposed and control samples. AcridineOrangestaining was then applied in the context of waterqualitymonitoring. Fish were exposed for 4 days to water sampled in two hydrological contexts: basal flow and spring flood. The results show that exposure to spring flood water in an agricultural stream can induce mutagenicity

Default Risk in Corporate Yield Spreads

An important research question examined in the recent credit risk literature focuses on the proportion of corporate yield spreads which can be attributed to default risk. Past studies have verified that only a small fraction of the spreads can be explained by default risk. In this paper, we reexamine this topic in the light of the different issues associated with the computation of transition and default probabilities obained with historical rating transition data. One significant finding of our research is that the estimated default-risk proportion of corporate yield spreads in highly sensitive to the term structure of the default probabilities estimated for each rating class. Moreover, this proportion can become a large fraction of the yield spread when sensitivity analyses are made with respect to recovery rates, default cycles in the economy, and information considered in the historical rating transition data.Credit risk, default risk, corporate yield spread, transition matrix, default probability, Moody's, Standard and Poor's, recovery rate, data filtration, default cycle

A Reduced Form Model of Default Spreads with Markov-Switching Macroeconomic Factors

An important research area of the corporate yield spread literature seeks to measure the proportion of the spread that can be explained by factors such as the possibility of default, liquidity, tax differentials and market risk. We contribute to this literature by assessing the ability of observed macroeconomic factors and the possibility of changes in regime to explain the proportion of yield spreads caused by the risk of default in the context of a reduced form model. For this purpose, we extend the Markov Switching risk-free term structure model of Bansal and Zhou (2002) to the corporate bond setting and develop recursive formulas for default probabilities, risk-free and risky zero-coupon bond yields as well as credit default swap premia. The model is calibrated with consumption, inflation, risk-free yields and default data for Aa, A and Baa bonds from the 1987-2008 period. We find that our macroeconomic factors are linked with two out of three sharp increases in the spreads during this sample period, indicating that the variations can be related to macroeconomic undiversifiable risk. The estimated default spreads can explain almost half of the 10 years to maturity industrial Baa zero-coupon yields in some regime. Much smaller proportions are found for Aa and A bonds with numbers around 10%. The proportions of default estimated with credit default swaps are higher, in many cases doubling those found with corporate yield spreads.Credit spread, default spread, Markov switching, macroeconomic factors, reduced form model of default, random subjective discount factor, credit default swap, CDS

A Reduced Form Model of Default Spreads with Markov Switching Macroeconomic Factors

An important research area of the corporate yield spread literature seeks to measure the proportion of the spread explained by factors such as the possibility of default, liquidity or tax differentials. We contribute to this literature by assessing the ability of observed macroeconomic factors and the possibility of changes in regime to explain the proportion in yield spreads caused by the risk of default in the context of a reduced form model. For this purpose, we extend the Markov Switching risk-free term structure model of Bansal ad Zhou (2002) to the corporate bond setting and develop recursive formulas for default probabilities, risk-free and risky zero-coupon bond yields. The model is calibrated out of sample with consumption, inflation, risk-free yield and default data over the 1987-1996 period. Our results indicate that inflation is a key factor to consider for explaining default spreads during our sample period. We also find that the estimated default spreads can explain up to half of the 10 year to maturity Baa zero-coupon yield in certain regime with different sensitivities to consumption and inflation through time.Credit spread, default spread, Markov Switching, macroeconomic factors, reduced form model of default

Mutagenic impact on fish of runoff events in agricultural areas in south-west France

When heavy rainfall follows herbicide application, the intense surface runoff causes stream water contamination. Aquatic organisms are then briefly exposed to a complex mixture of contaminants. The aim of the present study is to investigate the genotoxic impact of such events on fish. A model fish, the Crucian carp (Carassius carassius) was exposed in controlled conditions, for 4 days, to water sampled daily in the Save River (France). The watershed of this stream is representative of agricultural areas in southwest France. Three hydrological conditions were compared: basal flow, winter flood, and spring flood. Chemical analysis of the water samples confirmed the higher contamination of the spring flood water,mainly explained by a peak of metolachlor. Genotoxicity was evaluated by micronucleus (MN) test and comet assay in peripheral erythrocytes. A significant increase in DNA breakdowns compared to controls was detected by the comet assay for all conditions. Exposure to spring flood water resulted in the highest damage induction. Moreover, induced chromosomal damage was only detected in this condition. In addition, fish were exposed, for 4 days, to an experimental mixture of 5 herbicides representative of the spring flood water contamination. Fish exhibited moderate DNA damage induction and no significant chromosomal damage. The mutagenicity induced by field-collected water is then suspected to be the result of numerous interactions between contaminants themselves and environmental factors, stressing the use of realistic exposure conditions. The results revealed a mutagenic impact of water contamination during the spring flood, emphasizing the need to consider these transient events in water quality monitoring programs