We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Sparse estimation within Pearson's system, with an application to financial market risk.
- Authors
Carey, Michelle; Genest, Christian; Ramsay, James O.
- Abstract
Pearson's system is a rich class of models that includes many classical univariate distributions. It comprises all continuous densities whose logarithmic derivative can be expressed as a ratio of quadratic polynomials governed by a vector β$$ \beta $$ of coefficients. The estimation of a Pearson density is challenging, as small variations in β$$ \beta $$ can induce wild changes in the shape of the corresponding density fβ$$ {f}_{\beta } $$. The authors show how to estimate β$$ \beta $$ and fβ$$ {f}_{\beta } $$ effectively through a penalized likelihood procedure involving differential regularization. The approach combines a penalized regression method and a profiled estimation technique. Simulations and an illustration with S&P 500 data suggest that the proposed method can improve market risk assessment substantially through value‐at‐risk and expected shortfall estimates that outperform those currently used by financial institutions and regulators.
- Subjects
FINANCIAL risk; FINANCIAL markets; STANDARD &; Poor's 500 Index; SPARSE approximations; VALUE at risk; RISK assessment
- Publication
Canadian Journal of Statistics, 2023, Vol 51, Issue 3, p800
- ISSN
0319-5724
- Publication type
Article
- DOI
10.1002/cjs.11754