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Stripping the Swiss discount curve using kernel ridge regression

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003  MAP
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008  240830e20240815che|||p |0|||b|eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎921
1001 ‎$0‎MAPA20240020989‎$a‎Camenzind, Nicolas
24510‎$a‎Stripping the Swiss discount curve using kernel ridge regression‎$c‎Nicolas Camenzind & Damir Filipovic
520  ‎$a‎We analyze and implement the kernel ridge regression (KR) method developed in Filipovic et al. (Stripping the discount curvea robust machine learning approach. Swiss Finance Institute Research Paper No. 2224. to estimate the risk-free discount curve for the Swiss government bond market. We show that the insurance industry standard SmithWilson method is a special case of the KR framework. We recapitulate the curve estimation methods of the Swiss Solvency Test (SST) and the Swiss National Bank (SNB). In an extensive empirical study covering the years 20102022 we compare the KR curves with the SST and SNB curves. The KR method proves to be robust, flexible, transparent, reproducible and easy to implement, and outperforms the benchmarks in- and out-of-sample. We show the limitations of all methods for extrapolating the yield curve and propose possible solutions for the extrapolation problem. We conclude that the KR method is the preferred method for estimating the discount curve
650 4‎$0‎MAPA20080565381‎$a‎Deuda pública
650 4‎$0‎MAPA20080586294‎$a‎Mercado de seguros
650 4‎$0‎MAPA20090003736‎$a‎Estimación Kernel
650 4‎$0‎MAPA20080538279‎$a‎Bonos
651 1‎$0‎MAPA20080637668‎$a‎Suiza
700  ‎$0‎MAPA20080649678‎$a‎Filipovic, Damir
7730 ‎$w‎MAP20220007085‎$g‎15/08/2024 Volumen 14 - Número 2 - agosto 2024 , p.371-410‎$t‎European Actuarial Journal‎$d‎Cham, Switzerland : Springer Nature Switzerland AG, 2021-2022
856  ‎$u‎https://link.springer.com/article/10.1007/s13385-024-00386-4