Person: Vilar Zanón, José Luis
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First Name
José Luis
Last Name
Vilar Zanón
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Ciencias Económicas y Empresariales
Department
Economía Financiera, Actuarial y Estadística
Area
Economía Financiera y Contabilidad
Identifiers
20 results
Search Results
Now showing 1 - 10 of 20
Item Ciencia y seguros: el sugimiento de la ciencia actuarial(2016) Vilar Zanón, José LuisLa Ciencia Actuarial, como todas las ciencias, atraviesa una serie de periodos hasta su afirmación final como disciplina científica conocida bajo ese nombre.Item Modelización estocástica de los requisitos de capital de solvencia II por el riesgo de caídas de cartera para un seguro de vida de larga duración(Anales Del Instituto De Actuarios Españoles, 2017) Vilar Zanón, José Luis; Gil Fana, José Antonio; Dylewska, Ewa; Heras Martínez, Antonio JoséLa observación de la estructura de los requisitos de capital de Solvencia II para un ejemplo de un seguro de vida y supervivencia indica que el elemento principal del sub-módulo de riesgo de suscripción de vida se corresponde con el riesgo de caídas de cartera. Por lo tanto, la primera tarea en la optimización de los requisitos de capital consiste en la búsqueda de posibles reducciones de requisitos de capital correspondientes a este riesgo. Los resultados del análisis implican que para productos similares al estudiado la fórmula estándar puede ser demasiado onerosa respecto a los requisitos de capital por riesgo de cartera.Item An average model approach to experience based premium rates discounts: an application to Spanish agricultural insurance(European Actuarial Journal, 2020) De Frutos, Estela; Vilar Zanón, José Luis; Heras Martínez, Antonio JoséWe address some issues in agricultural insurance, describing drawbacks of the bonus-malus system (BMS) methodology used in Spain and many other EU countries. We develop an alternative experience based premium rate discount system taking into account the adverse years when high losses caused by extreme weather events happen. Our contribution consists of a two-step methodology. Firstly, we use tobit or Tweedie regressions to calculate yearly correction rates. Secondly, we calculate the mean of the correction rates. This average model acts as a bufer against adverse year losses. We compare three alternatives: our two resulting average models and the BMS operating in the Spanish line of business exemplifed—table grapes.Item Online product returns risk assessment and management(TOP, 2017) Vilar Zanón, José Luis; Vilar, Eduardo; Heras Martínez, Antonio JoséCommonly viewed as a cost center from an operations perspective, product returns have the potential to strongly influence operating margins and business profitability, thus constituting a risk for online retailers. This work addresses the problem of how to assess and manage product returns costs using a risk analysis methodology. Online product returns are seen as a random phenomenon that fluctuates in severity over time, threatening the profitability of the online store. Therefore, the starting point is that this risk can be modeled as a future random stream of payments. Given one or many future time periods, we aim to assess and manage this risk by answering two important questions: (1) Pricing—or what dollar amount factored on top of the current price of goods sold online would cover the cost of product returns, and (2) Reserving—or how much capital does an online retailer need to reserve at the beginning of each period to cover the cost of online product returns. We develop our analysis for one period (a month) by a closed formula model, and for multi-period (a year) by a dynamic simulation model. Risk measurements are executed in both cases to answer the two main questions above. We exemplify this methodology using an anonymized archival database of actual purchase and return history provided by a large size US women’s apparel online retailer.Item On the evaluation of the asymptotic fairness of bonus-malus systems(2001) Heras Martínez, Antonio José; Vilar Zanón, José Luis; Gil Fana, José AntonioIn this paper we try to evaluate the asymptotic fairness of bonus-malus systems, assuming the simplest case when there is no hunger for bonus.The asymptotic fairness has to be understood as the bonus-malus systemability in assessing the individual risks in the long run (see Lemaire[1995] p.xvi). Firstly we de…ne the asymptotic fairness of a bonus-malussystem following an expression that can be found in Lemaire [1985] p.168. Secondly, we de…ne a measure of the global asymptotic fairness considering the structure function of the risk group. Finally we try to calculate, for each set of transition rules and a given structure function,the scale of premiums that brings the global asymptotic fairness closest to the ideal situation where each insured pays in the long run a premium corresponding to its own claim frequency. This is possible thanks to the application of a multiobjective optimization technique named Goal Programing. We give an example illustrating the fact that the ideal case could be fairly well approached.Item Linear Goal Programming and experience rating(2001) Heras Martínez, Antonio José; Vilar Zanón, José Luis; Gil Fana, José Antonio; García Pineda, María PilarThis paper is devoted to the explanation of a new methodology in bonus malus system design, capable of taking into account very well known theoretical conditions like fairness and …nancial equilibrium of the portfolio, in addition to market conditions that could …t the resulting scale of premiums into competitive commercial settings. This is done through the resolution of a classical Bayesian decision problem, by means of minimization of the absolute error instead of the classical quadratic error. It is at this stage that we apply Goal Programming methods, which are linear thanks to the equivalence between the minimization of the absolute error and the minimization of the sum of some deviation variables which have a natural interpretation as rating errors. We show in an example how does the new methodology work. All the linear programs have been solved using the simplex method.Item A linear goal programming method to recover risk neutral probabilities from options prices by maximum entropy(Decisions in Economics and Finance, 2019) Peraita Ezcurra, Olivia; Vilar Zanón, José LuisWe develop a new methodology to retrieve risk neutral probabilities (equivalent martingale measure) with maximum entropy from quoted option prices. We assume the no arbitrage hypothesis and model the efficient market hypothesis by means of a maximum entropic risk neutral distribution. The method is free of parametric assumption except for the simulation of the distribution support, for which purpose we can choose any stochastic model. Firstly, we innovate in the minimization of a different f-divergence than Kullback–Leibler’s relative entropy, resulting in the total variation distance. We minimize it by means of linear goal programming, thus guaranteeing a fast numerical resolution. The method values non-traded assets finding a RNP minimizing its f-divergence to the maximum entropy distribution over a simulated support—the uniform distribution—calibrated to the benchmarks prices constraints. Our second innovation is that in an incomplete market, we can increase the f-divergence from its minimum to obtain any asset price belonging to the interval satisfying the non-existence of an arbitrage portfolio, without presupposing any utility function for the decision maker. We exemplify our methodology by means of synthetic and real-world cases, showing that our methodology can either price non-traded assets or interpolate and extrapolate a volatility surface.Item Using rough sets to predict insolvency of Spanish non-life insurance companies(2003) Segovia Vargas, María Jesús; Gil Fana, José Antonio; Heras Martínez, Antonio José; Vilar Zanón, José Luis; Sanchís Arellano, AliciaInsolvency of insurance companies has been a concern of several parties stemmed from the perceived need to protect the general public and to try to minimize the costs associated to this problem such as the effects on state insurance guaranty funds or the responsibilities for management and auditors. Most methods applied in the past to predict business failure in insurance companies are techniques of statistical nature and use financial ratios as explicative variables. These variables do not normally satisfy statistical assumptions so we propose an approach to predict insolvency of insurance companies based on Rough Set Theory. Some of the advantages of this approach are: first, it is a useful tool to analyse information systems representing knowledge gained by experience; second, elimination of the redundant variables is got, so we can focus on minimal subsets of variables to evaluate insolvency and the cost of the decision making process and time employed by the decision maker are reduced; third, a model consisted of a set of easily understandable decision rules is produced and it is not necessary the interpretation of an expert and, fourth, these rules based on the experience are well supported by a set of real examples so this allows the argumentation of the decisions we make. This study completes previous researches for bankruptcy prediction based on Rough Set Theory developing a prediction model for Spanish non-life insurance companies and using general financial ratios as well as those that are specifically proposed for evaluating insolvency of insurance sector. The results are very encouraging in comparison with discriminant analysis and show that Rough Set Theory can be a useful tool for parties interested in evaluating insolvency of an insurance firm.Item Claims counts and stable distributions(2008) Vilar Zanón, José Luis; Heras Martínez, Antonio José; Gil Fana, José AntonioCómo se usan las distribuciones estables para garantiza el ajuste de la función de estructura de una cartera de pólizas de seguros.Item Pricing Illiquid Assets by Entropy Maximization Through Linear Goal Programming(Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2018) Peraita Ezcurra, Olivia; Vilar Zanón, José LuisIn this contribution we study the problem of retrieving a risk neutral probability (RNP) in an incomplete market, with the aim of pricing non-traded assets and hedging their risk. The pricing issue has been often addressed in the literature finding an RNP with maximum entropy by means of the minimization of the Kullback-Leibler divergence. Under this approach, the efficient market hypothesis is modelled by means of the maximum entropy RNP. This methodology consists of three steps: firstly simulating a finite number of market states of some underlying stochastic model, secondly choosing a set of assets—called benchmarks—with characteristics close to the given one, and thirdly calculating an RNP by means of the minimization of its divergence from the maximum entropy distribution over the simulated finite sample market states, i.e. from the uniform distribution. This maximum entropy RNP must exactly price the benchmarks by their quoted prices. Here we proceed in a different way consisting of the minimization of a different divergence resulting in the total variation distance. This is done by means of a two steps linear goal programming method. The calculation of the super-replicating portfolios (not supplied by the Kullback-Leibler approach) would then be derived as solutions of the dual linear programs.