Pricing and hedging of credit derivatives via?the?innovations approach to nonlinear filtering

In this paper, we propose a new, information-based approach for modelling the dynamic evolution of a portfolio of credit risky securities. In our setup, market prices of traded credit derivatives are given by the solution of a nonlinear filtering problem. The innovations approach to nonlinear filtering is used to solve this problem and to derive the dynamics of market prices. Moreover, the practical application of the model is discussed: we analyse calibration, the pricing of exotic credit derivatives and the computation of risk-minimizing hedging strategies. The paper closes with a few numerical case studies.     

Pricing volatility of stock returns with volatile and persistent components

This paper introduces a two-component volatility model based on first moments of both components to describe the dynamics of speculative return volatility. The two components capture the volatile and the persistent part of volatility, respectively. The model is applied to 10 Asia-Pacific stock markets. Their in-mean effects on returns are tested. The empirical results show that the persistent component is much more important for the volatility dynamic process than is the volatile component. However, the volatile component is found to be a significant pricing factor of asset returns for most markets. A positive or risk-premium effect exists between the return and the volatile component, yet the persistent component is not significantly priced for the return dynamic process.

Pricing and hedging guaranteed minimum withdrawal benefits under a general Lévy framework using the COS method

This paper extends the Fourier-cosine (COS) method to the pricing and hedging of variable annuities embedded with guaranteed minimum withdrawal benefit (GMWB) riders. The COS method facilitates efficient computation of prices and hedge ratios of the GMWB riders when the underlying fund dynamics evolve under the influence of the general class of Lévy processes. Formulae are derived to value the contract at each withdrawal date using a backward recursive dynamic programming algorithm. Numerical comparisons are performed with results presented in Bacinello et al. [Scand. Actuar. J., 2014, 1–20], and Luo and Shevchenko [Int. J. Financ. Eng., 2014, 2, 1–24], to confirm the accuracy of the method. The efficiency of the proposed method is assessed by making comparisons with the approach presented in Bacinello et al. [op. cit.]. We find that the COS method presents highly accurate results with notably fast computational times. The valuation framework forms the basis for GMWB hedging. A local risk minimisation approach to hedging intra-withdrawal date risks is developed. A variety of risk measures are considered for minimisation in the general Lévy framework. While the second moment and variance have been considered in existing literature, we show that the Value-at-Risk (VaR) may also be of interest as a risk measure to minimise risk in variable annuities portfolios.     

Pricing options under stochastic volatility: a power series approach

In this paper we present a new approach for solving the pricing equations (PDEs) of European call options for very general stochastic volatility models, including the Stein and Stein, the Hull and White, and the Heston models as particular cases. The main idea is to express the price in terms of a power series of the correlation parameter between the processes driving the dynamics of the price and of the volatility. The expansion is done around correlation zero and each term is identified via a probabilistic expression. It is shown that the power series converges with positive radius under some regularity conditions. Besides, we propose (as in Alós in Finance Stoch. 10:353–365, 2006) a further approximation to make the terms of the series easily computable and we estimate the error we commit. Finally we apply our methodology to some well-known financial models.      

Even beyond humanity – a comment on ‘Change and commitment: beyond risk and responsibility’ by Silvio Funtowicz and Roger Strand

Due to past major food scares, food-safety perceptions have become a widely investigated topic. The aim of the present study was to examine food-safety perceptions separately for every step of the total meat supply chain, as such a detailed approach yields more promising strategies to ensure food safety in the future. Using a large-scale survey, we examined people’s risk perceptions of 18 steps describing the total meat supply chain. The results revealed a clear distinction between risk perception at the production stage and risk perception at home in the total meat supply chain, in that people perceived significantly less risk at home. However, people’s risk perceptions of the single stages in the total meat supply chain were overall slightly above average. Additionally, there were individual differences, as risk perception at the production stage was highly correlated with risk perception at home, meaning that some people perceived more risk than others overall. Using a multiple regression analysis, we found food-safety perceptions to be barely significant next to other important variables affecting people’s meat-consumption decisions. For those analyses, we asked participants to assess several constructs previously found to be associated with meat consumption. The goal was to determine how food-safety perceptions influence people’s meat consumption next to other important constructs in situations in which no major food scandal is present. The present paper concludes by discussing possible marketing and policy strategies to overcome people’s inaccurate safety perceptions of the stages of the total food chain.     

Errata for the article “Pricing and static hedging of American-style options under the jump to default extended CEV model”

This errata corrects an error in Ruas et al. (2013, Equation 27) and updates the numerical results contained in Ruas et al. (2013, Tables 4 and 5). The material provided here is meant to be read strictly in conjunction with Ruas et al. (2013).     

Fuel hedging,operational hedging and risk exposure — Evidence from the global airline industry

The aviation industry is characterized by low profit margins and a constant struggle with skyrocketing fuel costs. Financial and operational hedging strategies serve aviation managers as a tool to counteract high and volatile fuel prices. While most research on fuel hedging has concentrated on the U.S. airline market, this paper is the first study to include airlines from Asia and Europe. We analyze 64 airlines over 11 years and find that Asian carriers are more negatively exposed than European airlines but less exposed than North American airlines. In contrast to Treanor, Simkins, Rogers and Carter (2012), this study finds less significant negative exposure coefficients among U.S. carriers. Using a fixed effects model we reject the hypothesis that financial hedging decreases risk exposure. One possibility is that the decreased volatility in jet fuel prices over the past few years has perhaps made airlines less exposed to fuel prices and hence, financial hedging is less effective. Operational hedging, defined by two proxies for fleet diversity, does not reduce exposure significantly, either. In contrast, a one percentage point increase in fleet diversity, calculated with a dispersion index using different aircraft types, increases the risk exposure coefficient by 1.83%. On the other hand, fleet diversity, calculated with different aircraft families, increases exposure by only 0.63%. These results are supported by the global trend of airline managers to reduce fleet diversity. Airlines have reduced their fleet diversity by 7.70% or 10.77% (depending on the proxy) between 2002 and 2012. The greatest reduction can be found among European airlines with 23.12% (28.04%).     

On irregular functionals of SDEs and the Euler scheme

We prove a sharp upper bound for the error $\mathbb {E}|g(X)-g(\hat{X})|^{p}We prove a sharp upper bound for the error in terms of moments of , where X and are random variables and the function g is a function of bounded variation. We apply the results to the approximation of a solution to a stochastic differential equation at time T by the Euler scheme, and show that the approximation of the payoff of the binary option has asymptotically sharp strong convergence rate 1/2. This has consequences for multilevel Monte Carlo methods. The author was supported by the Finnish Graduate School in Stochastics and Statistics, the Ellen and Artturi Nyyss?nen Foundation, and the Academy of Finland, project #110599.     

Challenges faced by accountancy education during and beyond the years of transition—some Hong Kong evidence

The sovereignty of Hong Kong (HK) was returned to China on 1 July l997 and HK has become a Special Administrative Region of China under the principle of “one country, two systems”. In order to evaluate the impact of the “l997” issue on accountancy education in HK, the Department of Accountancy of The Hong Kong Polytechnic University was chosen as a case study. This paper discusses the accounting reforms taking place in China, the political factor of “1997”, and their corresponding impacts on accountancy education in HK. This discussion is followed by assessing the challenges faced and the responses made by the Department of Accountancy of The Hong Kong Polytechnic University in order adapt to the challenges.     

Optimal tax policy and expected longevity: a mean and variance utility approach

This paper studies the normative problem of redistribution between agents who can influence their survival probability through private health spending, but who differ in their attitude towards the risks involved in the lotteries of life to be chosen. For that purpose, a two-period model is developed, where agents’ preferences on lotteries of life can be represented by a mean and variance utility function allowing, unlike the expected utility form, some sensitivity to what Allais (Econometrica 21(4), 503–546, 1953) calls the ‘dispersion of psychological values’. It is shown that if agents ignore the impact of health spending on the return of their savings, the decentralization of the first-best utilitarian optimum requires intergroup lump sum transfers and group-specific positive taxes on health spending. Under asymmetric information, a differentiated taxation across agents is still required, but subsidizing health spending may be optimal as a way to solve the incentive problem.     

Model uncertainty,recalibration, and the emergence of delta–vega hedging

We study option pricing and hedging with uncertainty about a Black–Scholes reference model which is dynamically recalibrated to the market price of a liquidly traded vanilla option. For dynamic trading in the underlying asset and this vanilla option, delta–vega hedging is asymptotically optimal in the limit for small uncertainty aversion. The corresponding indifference price corrections are determined by the disparity between the vegas, gammas, vannas and volgas of the non-traded and the liquidly traded options.     

Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?

We assess whether the long-run volatilities of Bitcoin, global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results provide evidence supporting this hypothesis, except in the case of bonds. For Bitcoin investors, the results imply the ability to use information about the state of global economic uncertainty to enhance the predictions of Bitcoin volatility. We further examine whether the correlation between Bitcoin and global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results reveal that global economic policy uncertainty has a negative significant impact on the Bitcoin-bonds correlation and a positive impact on both Bitcoin-equities and Bitcoin-commodities correlations, suggesting the possibility of Bitcoin acting as a hedge under specific economic uncertainty conditions. Interestingly, the hedging effectiveness of Bitcoin for both global equities and global bonds enhances slightly after considering the level of global economic policy uncertainty. Such a weak effect of the state of global economic uncertainty on the hedging ability of Bitcoin implies that investors cannot substantially enhance the hedging performance of Bitcoin under different economic uncertainty conditions.     

Option pricing and hedging under a stochastic volatility Lévy process model

In this paper, we discuss a stochastic volatility model with a Lévy driving process and then apply the model to option pricing and hedging. The stochastic volatility in our model is defined by the continuous Markov chain. The risk-neutral measure is obtained by applying the Esscher transform. The option price using this model is computed by the Fourier transform method. We obtain the closed-form solution for the hedge ratio by applying locally risk-minimizing hedging.     

Association between environmental factors and equity market performance: evidence from a nonparametric frontier method

In this cross-sectional study, equity market performance is assessed in a multidimensional risk-adjusted return framework using a nonparametric procedure known as data envelopment analysis. Employing a censored regression procedure, the association between equity market performance and a set of variables that proxy market characteristics and the political and business environment in which the market operates is investigated. The paper contributes to the literature on the association between environmental factors and equity market performance by using a methodology not previously employed in such investigations. The results reveal that equity market performance may be positively related to the size of the market and friendliness of the business environment. Friendliness of the business environment is an objective measure of regulations conducive to business and their enforcement.     

Pricing Perpetual Put Options by the Black–Scholes Equation with a Nonlinear Volatility Function

We investigate qualitative and quantitative behavior of a solution of the mathematical model for pricing American style of perpetual put options. We assume the option price is a solution to the stationary generalized Black–Scholes equation in which the volatility function may depend on the second derivative of the option price itself. We prove existence and uniqueness of a solution to the free boundary problem. We derive a single implicit equation for the free boundary position and the closed form formula for the option price. It is a generalization of the well-known explicit closed form solution derived by Merton for the case of a constant volatility. We also present results of numerical computations of the free boundary position, option price and their dependence on model parameters.     

Comparing alternative Lévy base correlation models for pricing and hedging CDO tranches

In this paper we investigate alternative Lévy base correlation models that arise from the Gamma, Inverse Gaussian and CMY distribution classes. We compare these models with the basic (exponential) Lévy base correlation model and the classical Gaussian base correlation model. For all investigated models, the Lévy base correlation curve is significantly flatter than the corresponding Gaussian curve, which indicates better correspondence of the Lévy models with reality. Furthermore, we present the results of pricing bespoke tranchlets and comparing deltas of both standard and custom-made tranches under all the considered models. We focus on deltas with respect to the CDS index and individual CDSs, and the hedge ratio for hedging the equity tranche with the junior mezzanine.