Bibliographic citations
Villano, A., (2022). Estimación de no arbitraje para una curva de financiamiento en dólares usando el modelo paramétrico de Nelson y Siegel con regresiones lineales sucesivas [Trabajo de suficiencia profesional, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/24518
Villano, A., Estimación de no arbitraje para una curva de financiamiento en dólares usando el modelo paramétrico de Nelson y Siegel con regresiones lineales sucesivas [Trabajo de suficiencia profesional]. PE: Universidad Nacional de Ingeniería; 2022. http://hdl.handle.net/20.500.14076/24518
@misc{renati/712479,
title = "Estimación de no arbitraje para una curva de financiamiento en dólares usando el modelo paramétrico de Nelson y Siegel con regresiones lineales sucesivas",
author = "Villano Ccopa, Armando",
publisher = "Universidad Nacional de Ingeniería",
year = "2022"
}
Construction of financing or funding curve in US dollar can be done directly from the capital market, but it can also be obtained indirectly through the local derivatives market. This paper presents the construction of a short-term financing curve in dollars through non-arbitrage conditions in the local FX derivatives market, using the covered parity of interest rates between the Chilean Peso and the US Dollar currencies. Subsequently, having obtained the implicit rates in dollars, with forward prices observed in the FX market, a structure of spot interest rates in US dollars is estimated using the Nelson and Siegel parametric model. Under this four-parameter model, successive linear regressions are performed, varying the non-linear parameter λ - lambda, time decay rate – in such a way as to find the model with the highest R2 fitting. Finally, the model will be determined with the four estimated parameters, the first three by linear regression and λ by optimization of R2. Since this procedure is empirical, the modelling and parameters estimation of the financing curve in dollars can be done several times a day, depending on how the financial conditions of the market changes.
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