A jump diffusion model for VIX volatility options and futures

Volatility indices are becoming increasingly popular as a measure of market uncertainty and as a new asset class for developing derivative instruments. Although jumps are widely considered as a salient feature of volatility, their implications for pricing volatility options and futures are not yet fully understood. This paper provides evidence indicating that the time series behaviour of the VIX index is well approximated by a mean reverting logarithmic diffusion with jumps. This process is capable of capturing stylized facts of VIX dynamics such as fast mean-reversion at higher levels, level effects of volatility and large upward movements during times of market stress. Based on the empirical results, we provide closed-form valuation models for European options written on the spot and forward VIX, respectively.     

On measuring nonlinear risk with scarce observations

We propose a methodology for estimating the risk of portfolios that exhibit nonlinear dependence on the risk driving factors and have scarce observations, which is typical for portfolios of investments in hedge funds. The methodology consists of two steps: first, regressing the portfolio return on nonlinear functions of each single risk driving factor and second, merging together the obtained estimates taking into account the dependence between different factors. Performing the second step leads us to a certain probabilistic problem, for which we propose an analytic and computationally feasible solution for the case where the joint law of the factors is a Gaussian copula. A typical practical application can be to estimate the risk of a hedge fund or a portfolio of hedge funds. As a theoretical consequence of our results, we propose a new definition of the factor risk, i.e., the risk of a portfolio brought by a given factor.     

Assessment of banking service quality perception using the SERVPERF model

The purpose of this article is to evaluate the quality of the services provided by the two most important banks that operate in Mexico, using as case study those branches that are located in the four main cities of the Isthmus of Tehuantepec: Ixtepec, Juchitán, Tehuantepec and Salina Cruz. The methodological strategy of this investigation resided in the application of a modified version of the SERVPERF model, one of the most important in this type of studies, which assesses the perception of the clients based on five criteria: reliability, responsiveness, safety, empathy and tangible elements. Strictly speaking, these criteria or dimensions jointly define the quality of the service received. The results found indicate that, in general terms, the assessment of the clients of both banks regarding their services is high, which could be explained by the establishment of very low expectations by the users according to the specific socioeconomic variables. Additionally, significant differences were found regarding the assessment between groups of people according to the different analyzed variables, such as occupation, level of education and age range.     

Evaluación de la percepción de la calidad de los servicios bancarios mediante el modelo SERVPERF

The purpose of this paper is to assess the quality of the services provided by two major banks in Mexico. The case study is with reference to the branches located in the four major cities of the Isthmus of Tehuantepec: Ixtepec, Juchitán, Tehuantepec and Salina Cruz. The strategic method adopted for this research was the application of a modified version of the SERVPERF model, one of the most important models in this type of study. The SERVPERF model assesses customers’ perceptions according to five criteria: reliability, responsiveness, security, empathy, and tangible factors. Strictly speaking, these criteria or dimensions combined define the quality of the services. The results indicate that the overall customers’ valuation of both banks with regard to their services is high; these results might respond to very low expectations according to specific socioeconomic variables. Additionally, significant differences in users’ perception among groups of people according to various analyzed variables such as occupation, education, and age ranges were found.     

The macroeconomics outcome of oil shocks in the small Eurozone economies

In this work, we provide an analysis over the period 1999–2015 of the effects of oil shocks on prices and GDP in a group of small Euro-area economies. The group includes Austria, Belgium, Finland, Greece, Ireland, Italy, Netherlands, Portugal and Spain. In order to characterise the macroeconomic outcomes of movements in oil prices, we adopt the structural vector autoregression (VAR) methodology. We find that under the European Monetary Union (EMU), oil price shocks have been important drivers of business cycle fluctuations in almost all these countries. Moreover, an increase in oil prices produces significant recessionary effects in all the countries included in the investigation. Thus, although there are different sizes in the responses of output in the investigated countries, our main conclusion is that despite the structural changes experienced by the European economies in the last decades, oil prices still matter for these countries. In the light of these results, we also stress some important challenges for the conduct of monetary policy in the Euro area.     

Environmental policy implications of extreme variations in pollutant stock levels and socioeconomic costs

This paper uses a real options approach to examine the impact of abrupt increases in carbon dioxide emissions and pollutant-related socio-economic costs. It derives optimal investment rules in the form of critical values for both pollutant stock levels and social costs, above which environmental policies should be adopted. Moreover, it determines the optimal emissions abatement level. Our analysis extends the methodology of Pindyck (2000) using jump diffusion processes. We show that if the stock of pollutant is subject to extreme variations and the emissions abatement level is chosen exogenously by the policymaker, then lower levels of the pollutant stock are required to trigger policy adoption. A similar, yet more prominent, effect is observed under the assumption that pollutant-related socio-economic costs and benefits are expected to exhibit abrupt changes. However, different results are obtained when we examine simultaneously the two interrelated decisions, namely, the optimal threshold of emissions abatement and the optimal abatement level. In this case, an increase in the size and/or probability of a jump increases the critical values of both pollutant stock levels and socio-economic costs but leads to higher optimal abatement.     

Clusters for life or life cycles of clusters: in search of the critical factors of clusters' resilience

This article investigates the driving forces behind the life cycles and resilience of technological clusters. It concentrates, in particular, on the combination of critical parameters which allows clusters to succeed in disconnecting their cycle from the cycle of the technologies they produce, in order to maintain stability and growth in unstable economic environments. Three propositions on location decision externalities, the life cycle of composite technologies and the structural properties of knowledge networks are developed and introduced in an inclusive study of cluster trajectories. Discussions show that resilient clusters are those that combine network and external audience effects in location decision-making and evolve towards a specific core/periphery and disassortative structure of knowledge interactions along the knowledge and market phases. Understanding these pathways could be at the heart of the renewal of cluster and regional policy in a macro-economic context characterized by high instability and new growing consumer paradigms.     

Relative Robust Portfolio Optimization with benchmark regret

We extend Relative Robust Portfolio Optimization models to allow portfolios to optimize their performance when considered relative to a set of benchmarks. We do this in a minimum volatility setting, where we model regret directly as the maximum difference between our volatility and that of a given benchmark. Portfolio managers are also given the option of computing regret as a proportion of the benchmark’s performance, which is more in line with market practice than other approaches suggested in the literature. Furthermore, we propose using regret as an extra constraint rather than as a brand new objective function, so practitioners can maintain their current framework. We also look into how such a triple optimization problem can be solved or at least approximated for a general class of objective functions and uncertainty and benchmark sets. Finally, we illustrate the benefits of this approach by examining its performance against other common methods in the literature in several equity markets.     

A disaggregated analysis of EU imports: the implications for the study of patterns of trade and technology

This paper examines trends in the unit prices of manufacturedimports into the European Union (EU) in the period 1988–2002.This is undertaken at a high level of disaggregation, and itis this decomposition which we believe has important implicationsboth for a range of bodies of economic analysis and for policy.The analyses undertaken in this paper confirm that disaggregationmatters in helping to identify unit-price trends. We have alsoshown that unit-price trends vary with the type of economy exportinginto Europe and the type of product being exported, and thatthese results are robust at high levels of disaggregation.