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Related papers: Rational Kernel on Pricing Models of Inflation Der…

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We present a detailed analysis of interest rate derivatives valuation under credit risk and collateral modeling. We show how the credit and collateral extended valuation framework in Pallavicini et al (2011), and the related collateralized…

Pricing of Securities · Quantitative Finance 2015-09-15 Giacomo Bormetti , Damiano Brigo , Marco Francischello , Andrea Pallavicini

This work is focused on the study of early time cosmology and in particular on the study of inflation. After an introduction on the standard Big Bang theory, we discuss the physics of CMB and we explain how its observations can be used to…

General Relativity and Quantum Cosmology · Physics 2016-11-14 Mauro Pieroni

Causality is a seminal concept in science: Any research discipline, from sociology and medicine to physics and chemistry, aims at understanding the causes that could explain the correlations observed among some measured variables. While…

We develop a general term structure framework taking stochastic discontinuities explicitly into account. Stochastic discontinuities are a key feature in interest rate markets, as for example the jumps of the term structures in…

Mathematical Finance · Quantitative Finance 2020-04-28 Claudio Fontana , Zorana Grbac , Sandrine Gümbel , Thorsten Schmidt

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

Generalizations and variations of the fundamental lemma by Willems et al. are an active topic of recent research. In this note, we explore and formalize the links between kernel regression and some known nonlinear extensions of the…

Systems and Control · Electrical Eng. & Systems 2024-09-16 Oleksii Molodchyk , Timm Faulwasser

The problem of causal inference is to determine if a given probability distribution on observed variables is compatible with some causal structure. The difficult case is when the causal structure includes latent variables. We here introduce…

Quantum Physics · Physics 2019-07-24 Elie Wolfe , Robert W. Spekkens , Tobias Fritz

The goal of this thesis is threefold: first, to provide a general semantic setting for reasoning about incremental computation. Second, to establish and clarify the connection between derivatives in the incremental sense and derivatives in…

Logic in Computer Science · Computer Science 2020-06-30 Mario Alvarez-Picallo

Kernel methods are powerful machine learning techniques which implement generic non-linear functions to solve complex tasks in a simple way. They Have a solid mathematical background and exhibit excellent performance in practice. However,…

Machine Learning · Computer Science 2021-01-27 J. Emmanuel Johnson , Valero Laparra , Adrián Pérez-Suay , Miguel D. Mahecha , Gustau Camps-Valls

A relation between interest rates and inflation is presented using a two component economic model and a simple general principle. Preliminary results indicate a remarkable similarity to classical economic theories, in particular that of…

General Finance · Quantitative Finance 2011-04-14 Michael Coopersmith

Interest rate market models, like the LIBOR market model, have the advantage that the basic model quantities are directly observable in financial markets. Inflation market models extend this approach to inflation markets, where zero-coupon…

Pricing of Securities · Quantitative Finance 2015-03-18 Stefan Waldenberger

The market practice of extrapolating different term structures from different instruments lacks a rigorous justification in terms of cash flows structure and market observables. In this paper, we integrate our previous consistent theory for…

Pricing of Securities · Quantitative Finance 2013-04-05 Andrea Pallavicini , Damiano Brigo

Collateralization with daily margining has become a new standard in the post-crisis market. Although there appeared vast literature on a so-called multi-curve framework, a complete picture of a multi-currency setup with cross-currency basis…

Pricing of Securities · Quantitative Finance 2015-09-08 Masaaki Fujii , Akihiko Takahashi

We propose a new model for the joint evolution of the European inflation rate, the European Central Bank official interest rate and the short-term interest rate, in a stochastic, continuous time setting. We derive the valuation equation for…

Mathematical Finance · Quantitative Finance 2022-12-22 F. Antonacci , C. Costantini , F. D'Ippoliti , M. Papi

This textbook is an introduction to economic networks, intended for students and researchers in the fields of economics and applied mathematics. The textbook emphasizes quantitative modeling, with the main underlying tools being graph…

General Economics · Economics 2022-07-04 Thomas J. Sargent , John Stachurski

This is an informal and sketchy review of six topical, somewhat unrelated subjects in quantitative finance: rough volatility models; random covariance matrix theory; copulas; crowded trades; high-frequency trading & market stability; and…

General Finance · Quantitative Finance 2022-01-05 Jean-Philippe Bouchaud

We study inflation for a quantum scalar electrodynamics model in curved space-time and for higher-derivative quantum gravity (QG) coupled with scalar electrodynamics. The corresponding renormalization-group (RG) improved potential is…

High Energy Physics - Theory · Physics 2017-03-15 Ratbay Myrzakulov , Sergei Odintsov , Lorenzo Sebastiani

This article is an extension of the work of one of us (Coopersmith, 2011) in deriving the relationship between certain interest rates and the inflation rate of a two component economic system. We use the well-known Fisher relation between…

Economics · Quantitative Finance 2016-03-29 Michael Coopersmith , Pascal J. Gambardella

Recent progress in the development of efficient computational algorithms to price financial derivatives is summarized. A first algorithm is based on a path integral approach to option pricing, while a second algorithm makes use of a neural…

Statistical Mechanics · Physics 2009-11-07 G. Montagna , M. Morelli , O. Nicrosini , P. Amato , M. Farina

This paper addresses the problem of pricing involved financial derivatives by means of advanced of deep learning techniques. More precisely, we smartly combine several sophisticated neural network-based concepts like differential machine…

Computational Finance · Quantitative Finance 2024-04-18 Francisco Gómez Casanova , Álvaro Leitao , Fernando de Lope Contreras , Carlos Vázquez