Matching a distribution by matching quantiles estimation

• Autores: Nikolaos Sgouropoulos, Qiwei Yao, Claudia Yastremiz
• Localización: Journal of the American Statistical Association, ISSN 0162-1459, Vol. 110, Nº 510, 2015, págs. 742-759
• Idioma: inglés
• DOI: 10.1080/01621459.2014.929522
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• Resumen

  • Motivated by the problem of selecting representative portfolios for backtesting counterparty credit risks, we propose a matching quantiles estimation (MQE) method for matching a target distribution by that of a linear combination of a set of random variables. An iterative procedure based on the ordinary least-squares estimation (OLS) is proposed to compute MQE. MQE can be easily modified by adding a LASSO penalty term if a sparse representation is desired, or by restricting the matching within certain range of quantiles to match a part of the target distribution. The convergence of the algorithm and the asymptotic properties of the estimation, both with or without LASSO, are established. A measure and an associated statistical test are proposed to assess the goodness-of-match. The finite sample properties are illustrated by simulation. An application in selecting a counterparty representative portfolio with a real dataset is reported. The proposed MQE also finds applications in portfolio tracking, which demonstrates the usefulness of combining MQE with LASSO