Multi-curve HJM modelling for risk management. Issue 4 (3rd April 2018)

• Record Type: Journal Article
• Authors: Sabelli, Chiara; Pioppi, Michele; Sitzia, Luca; Bormetti, Giacomo
• Is Part Of: Quantitative finance. Volume 18:Issue 4(2018)
• Page Start: 563
• Page End: 590
• Publication Date: 2018-04-03
• Subjects: HJM -- Multiple-curve -- Scenario generation -- PCA; C32 -- C5 -- C51 -- G01 -- G10; Finance -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Investments -- Mathematics -- Periodicals; Economics -- Periodicals; Finances -- Modèles mathématiques -- Périodiques; 332.015118
• DOI: 10.1080/14697688.2017.1355104
• Languages: English
• ISSNs: 1469-7688

Abstract

Abstract : We present a HJM approach to the projection of multiple yield curves developed to capture the volatility content of historical term structures for risk management purposes. Since we observe the empirical data at daily frequency and only for a finite number of time-to-maturity buckets, we propose a modelling framework which is inherently discrete. In particular, we show how to approximate the HJM continuous time description of the multi-curve dynamics by a Vector Autoregressive process of order one. The resulting dynamics lends itself to a feasible estimation of the model volatility-correlation structure and market risk-premia. Then, resorting to the Principal Component Analysis we further simplify the dynamics reducing the number of covariance components. Applying the constant volatility version of our model on a sample of curves from the Euro area, we demonstrate its forecasting ability through an out-of-sample test.