English
Related papers

Related papers: On the range of admissible term-structures

200 papers

Discount is the difference between the face value of a bond and its present value. I propose an arbitrage-free dynamic framework for discount models, which provides an alternative to the Heath--Jarrow--Morton framework for forward rates. I…

Mathematical Finance · Quantitative Finance 2023-07-28 Damir Filipovic

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

This paper offers a new class of models of the term structure of interest rates. We allow each instantaneous forward rate to be driven by a different stochastic shock, constrained in such a way as to keep the forward rate curve continuous.…

Statistical Mechanics · Physics 2008-12-02 P. Santa-Clara , D. Sornette

The two main approaches in credit risk are the structural approach pioneered in Merton (1974) and the reduced-form framework proposed in Jarrow & Turnbull (1995) and in Artzner & Delbaen (1995). The goal of this article is to provide a…

Mathematical Finance · Quantitative Finance 2015-07-14 Frank Gehmlich , Thorsten Schmidt

In the paper we study dynamics of the arbitrage prices of credit default swaps within a hazard process model of credit risk. We derive these dynamics without postulating that the immersion property is satisfied between some relevant…

Probability · Mathematics 2009-01-19 Tomasz R. Bielecki , Monique Jeanblanc , Marek Rutkowski

We propose a new static parameterization of the implied volatility surface which is constructed by using polynomials of sigmoid functions combined with some other terms. This parameterization is flexible enough to fit market implied…

Mathematical Finance · Quantitative Finance 2014-12-09 Andrey Itkin

In the second part of our series we suggest new definitions of credit bond duration and convexity that remain consistent across all levels of credit quality including deeply distressed bonds and introduce additional risk measures that are…

Pricing of Securities · Quantitative Finance 2009-12-24 Arthur M. Berd , Roy Mashal , Peili Wang

We show how risk measures originally defined in a model free framework in terms of acceptance sets and reference assets imply a meaningful underlying probability structure. Hereafter we construct a maximal domain of definition of the risk…

Risk Management · Quantitative Finance 2017-11-27 Felix-Benedikt Liebrich , Gregor Svindland

We provide a general and tractable framework under which all multiple yield curve modeling approaches based on affine processes, be it short rate, Libor market, or HJM modeling, can be consolidated. We model a numeraire process and…

Mathematical Finance · Quantitative Finance 2017-02-08 Christa Cuchiero , Claudio Fontana , Alessandro Gnoatto

We propose a general framework for modeling multiple yield curves which have emerged after the last financial crisis. In a general semimartingale setting, we provide an HJM approach to model the term structure of multiplicative spreads…

Mathematical Finance · Quantitative Finance 2016-05-05 Christa Cuchiero , Claudio Fontana , Alessandro Gnoatto

The constitutive modelling of granular, porous and quasi-brittle materials is based on yield (or damage) functions, which may exhibit features (for instance, lack of convexity, or branches where the values go to infinity, or false elastic…

Materials Science · Physics 2014-09-24 S. Stupkiewicz , R. Denzer , A. Piccolroaz , D. Bigoni

This paper proposes a method to automatically construct or estimate Neyman-orthogonal moments in general models defined by a finite number of conditional moment restrictions (CMRs), with possibly different conditioning variables and…

Econometrics · Economics 2025-12-10 Facundo Argañaraz

Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to an ad-hoc operating point,…

Machine Learning · Computer Science 2023-10-06 Jiri Navratil , Benjamin Elder , Matthew Arnold , Soumya Ghosh , Prasanna Sattigeri

The paper analyzes the mathematics of the relationship between the default risk and yield-to-maturity of a coupon bond. It is shown that the yield-to-maturity is driven not only by the default probability and recovery rate of the bond but…

Pricing of Securities · Quantitative Finance 2012-04-02 Sara Cecchetti , Antonio Di Cesare

This paper studies the application of machine learning in extracting the market implied features from historical risk neutral corporate bond yields. We consider the example of a hypothetical illiquid fixed income market. After choosing a…

Mathematical Finance · Quantitative Finance 2018-06-06 Greg Kirczenow , Ali Fathi , Matt Davison

US Yield curve has recently collapsed to its most flattened level since subprime crisis and is close to the inversion. This fact has gathered attention of investors around the world and revived the discussion of proper modeling and…

Statistical Finance · Quantitative Finance 2018-08-01 Jarek Duda , Małgorzata Snarska

We consider a structural default model in an interconnected banking network as in Lipton [International Journal of Theoretical and Applied Finance, 19(6), 2016], with mutual obligations between each pair of banks. We analyse the model…

Computational Finance · Quantitative Finance 2017-01-03 Vadim Kaushansky , Alexander Lipton , Christoph Reisinger

Interest-rate risk is a key factor for property-casualty insurer capital. P&C companies tend to be highly leveraged, with bond holdings much greater than capital. For GAAP capital, bonds are marked to market but liabilities are not, so…

Risk Management · Quantitative Finance 2019-12-24 Gary Venter , Kailan Shang

Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to a specific operating point,…

Machine Learning · Computer Science 2021-06-03 Jiri Navratil , Benjamin Elder , Matthew Arnold , Soumya Ghosh , Prasanna Sattigeri

In this note, we develop stock option price approximations for a model which takes both the risk o default and the stochastic volatility into account. We also let the intensity of defaults be influenced by the volatility. We show that it…

Computational Engineering, Finance, and Science · Computer Science 2007-12-21 Erhan Bayraktar