Javier Mencía

Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation

We derive the statistical properties of the SNP densities of Gallant and Nychka (1987). We show that these densities, which are always positive, are more general than the truncated Gram-Charlier expansions of Jondeau and Rochinger (2001), who impose parameter restrictions to ensure positivity. We also use the SNP densities for option valuation. We relate real and risk-neutral measures, obtain closed-form prices for European options, and study the ?Greeks?. We show that SNP densities generate wider option price ranges than the truncated expansions. In an empirical application to S&P 500 index options, we find that the SNP model beats the standard and Practitioner?s Black-Scholes formulas, and truncated expansions.

Distributional Tests in Multivariate Dynamic Models with Normal and Student T Innovations

We derive Lagrange Multiplier and Likelihood Ratio specifi cation tests for the null hypotheses of multivariate normal and Student t innovations using the Generalised Hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange Multiplier-type tests into skewness and kurtosis components, from which we obtain more powerful one-sided Kuhn-Tucker versions that are equivalent to the Likelihood Ratio test, whose asymptotic distribution we provide. We conduct detailed Monte Carlo exercises to study our proposed tests in finite samples. Finally, we present an empirical application to ten US sectoral stock returns, which indicates that their conditional distribution is mildly asymmetric and strongly leptokurtic.

Volatility-Related Exchange Traded Assets: An Econometric Investigation

We develop a theoretical framework for covariance stationary but persistent positively valued processes which combines a semi-nonparametric expansion of the Gamma distribution with a component version of the multiplicative error model. Our conditional mean assumption allows for slow, possibly nonmonotonic mean-reversion, while our distribution assumption provides more flexibility than a traditional Laguerre expansion while preserving positivity of the density. We apply our framework to a dynamic portfolio allocation for Exchange Traded Notes tracking short- and mid-term VIX futures indices, which are increasingly popular but risky financial instruments. We show the superior performance of the strategies based on our econometric model.

Distributional Linkages between European Sovereign Bond and Bank Asset Returns

We analyse the dependence between sovereign bonds’ and banks’ asset return distributions with a large panel of European data from 2001 to 2013. Using quantile regressions, we identify nonlinear contemporaneous and lagged dependence. As a result, shocks to crisis-hit sovereign bonds have contemporaneous effects on the whole distribution of banks’ returns, as well as a persistent impact in the tails. Our results offer relevant insights about the relationship between banking and sovereign crises. In particular, during the recent financial crisis, banks’ asset return distributions have lower means and fatter tails than in the absence of a simultaneous sovereign crisis.

Distributional Tests in Multivariate Dynamic Models with Normal and Student-t Innovations

We derive Lagrange multiplier and likelihood ratio specification tests for the null hypotheses of multivariate normal and Student-t innovations using the generalized hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange multiplier-type tests into skewness and kurtosis components. We also obtain more powerful one-sided Kuhn-Tucker versions that are equivalent to the likelihood ratio test, whose asymptotic distribution we provide. Finally, we conduct detailed Monte Carlo exercises to study the size and power properties of our proposed tests in finite samples.

Macroprudential Policy: Objectives, Instruments and Indicators (Política macroprudencial: objetivos, instrumentos e indicadores)

English Abstract: This document presents the analytical framework recently developed by the Banco de Espana for the implementation of its macroprudential policy. The methodology described uses a broad set of indicators that enables macroprudential risks to be monitored through risk mapping. This framework will provide support for the Banco de Espana’s broad macroprudential policy stance.Spanish Abstract: Este documento presenta el marco analitico desarrollado recientemente por el Banco de Espana para la puesta en marcha de su politica macroprudencial. La metodologia descrita incorpora un amplio conjunto de indicadores que permiten realizar un seguimiento de los riesgos macroprudenciales a traves de un mapa de riesgos. El marco servira de soporte para definir la orientacion general de la politica macroprudencial del Banco de Espana.

Testing Non-Linear Dependence in the Hedge Fund Industry

This paper proposes a parsimonious approach to test non-linear dependence on the conditional mean and variance of hedge funds with respect to several market factors. My approach introduces non-linear dependence by means of empirically relevant polynomial functions of the factors. For comparison purposes, I also consider multifactor extensions of tests based on piecewise linear alternatives. I apply these tests to a database of monthly returns on 1,071 hedge funds. I fi nd that non-linear dependence on the mean is highly sensitive to the factors that I consider. However, I obtain a much stronger evidence of non-linear dependence on the conditional variance