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Related papers: How to hedge extrapolated yield curves

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Yield curve forecasting is an important problem in finance. In this work we explore the use of Gaussian Processes in conjunction with a dynamic modeling strategy, much like the Kalman Filter, to model the yield curve. Gaussian Processes…

Machine Learning · Statistics 2017-03-07 Rajiv Sambasivan , Sourish Das

We investigate LIBOR-based derivatives using a parsimonious field theory interest rate model capable of instilling imperfect correlation between different maturities. Delta and Gamma hedge parameters are derived for LIBOR Caps against…

Physics and Society · Physics 2008-12-02 Belal E. Baaquie , Cui Liang , Mitch C. Warachka

In computational materials science, predicting the yield strain of crosslinked polymers remains a challenging task. A common approach is to identify yield via the first critical point of stress-strain curves produced by molecular dynamics…

Soft Condensed Matter · Physics 2016-06-17 Paul N. Patrone

We develop a modelling framework for multiple yield curves driven by continuous-state branching processes with immigration (CBI processes). Exploiting the self-exciting behavior of CBI jump processes, this approach can reproduce the…

Pricing of Securities · Quantitative Finance 2020-10-15 Claudio Fontana , Alessandro Gnoatto , Guillaume Szulda

We study U.S. Treasury yield curve forecasting under distributional uncertainty and recast forecasting as an operations research and managerial decision problem. Rather than minimizing average forecast error, the forecaster selects a…

Mathematical Finance · Quantitative Finance 2026-01-09 Jinjun Liu , Ming-Yen Cheng

We present a PDE-based approach for the multidimensional extrapolation of smooth scalar quantities across interfaces with kinks and regions of high curvature. Unlike the commonly used method of [2] in which normal derivatives are…

Numerical Analysis · Mathematics 2023-09-26 Daniil Bochkov , Frederic Gibou

This study deals with the pricing and hedging of single-tranche collateralized debt obligations (STCDOs). We specify an affine two-factor model in which a catastrophic risk component is incorporated. Apart from being analytically tractable,…

Mathematical Finance · Quantitative Finance 2020-11-23 Zehra Eksi , Damir Filipović

We present a robust Deep Hedging framework for the pricing and hedging of option portfolios that significantly improves training efficiency and model robustness. In particular, we propose a neural model for training model embeddings which…

Computational Finance · Quantitative Finance 2025-04-24 Fabienne Schmid , Daniel Oeltz

The traditional way of building a yield curve is to choose an interpolation on discount factors, implied by the market tradable instruments. Since then, constructions based on specific interpolations of the forward rates have become the…

Pricing of Securities · Quantitative Finance 2020-05-29 Jherek Healy

This paper deals with the solving of variational inequality problem where the constrained set is given as the intersection of a number of fixed-point sets. To this end, we present an extrapolated sequential constraint method. At each…

Optimization and Control · Mathematics 2020-06-30 Mootta Prangprakhon , Nimit Nimana

We consider the theory of bond discounts, defined as the difference between the terminal payoff of the contract and its current price. Working in the setting of finite-dimensional realizations in the HJM framework, under suitable notions of…

Mathematical Finance · Quantitative Finance 2025-06-05 Andreas Celary , Paul Krühner , Zehra Eksi

This paper investigates the deep hedging framework, based on reinforcement learning (RL), for the dynamic hedging of swaptions, contrasting its performance with traditional sensitivity-based rho-hedging. We design agents under three…

Risk Management · Quantitative Finance 2025-12-09 Zaniar Ahmadi , Frédéric Godin

We derive an equation of motion for interest-rate yield curves by applying a minimum Fisher information variational approach to the implied probability density. By construction, solutions to the equation of motion recover observed bond…

Data Analysis, Statistics and Probability · Physics 2008-12-02 Raymond J. Hawkins , B. Roy Frieden , Joseph L. D'Anna

We use granular regulatory data on euro interest rate swap trades between January 2021 and June 2023 to assess whether derivative positions of Italian banks can offset losses on their debt securities holdings should interest rates rise…

Portfolio Management · Quantitative Finance 2024-12-23 Michele Leonardo Bianchi , Dario Ruzzi , Anatoli Segura

We study in this paper the function approximation error of multivariate linear extrapolation. The sharp error bound of linear interpolation already exists in the literature. However, linear extrapolation is used far more often in…

Optimization and Control · Mathematics 2026-05-20 Liyuan Cao , Zaiwen Wen , Ya-xiang Yuan

This work studies the dynamic risk management of the risk-neutral value of the potential credit losses on a portfolio of derivatives. Sensitivities-based hedging of such liability is sub-optimal because of bid-ask costs, pricing models…

Computational Finance · Quantitative Finance 2023-12-22 Roberto Daluiso , Marco Pinciroli , Michele Trapletti , Edoardo Vittori

We investigate model risk and distributionally robust optimization (DRO) under marginal and martingale constraints. Building on our previous work, we address the previously open case of static hedging with second-period maturity vanilla…

Probability · Mathematics 2026-01-29 Nathan Sauldubois

The main purpose of the paper is to derive Thiele's differential equation for unit-linked policies in the Heston-Hawkes stochastic volatility model introduced in arXiv:2210.15343. This model is an extension of the well-known Heston model…

Pricing of Securities · Quantitative Finance 2024-02-16 David R. Baños , Salvador Ortiz-Latorre , Oriol Zamora Font

We introduce a new method to calculate the credit exposure of European and path-dependent options. The proposed method is able to calculate accurate expected exposure and potential future exposure profiles under the risk-neutral and the…

Computational Finance · Quantitative Finance 2019-12-04 Kathrin Glau , Ricardo Pachon , Christian Pötz

We consider the problem of option hedging in a market with proportional transaction costs. Since super-replication is very costly in such markets, we replace perfect hedging with an expected loss constraint. Asymptotic analysis for small…

Portfolio Management · Quantitative Finance 2014-09-12 Bruno Bouchard , Ludovic Moreau , Mete H. Soner