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Closed form formulas for swaption prices in HJM model are derived. These formulas are used for nonparametric fit of deterministic forward volatility. It is demonstrated that this formula and non-parametric fit works very well and can be…

Pricing of Securities · Quantitative Finance 2017-04-11 V. M. Belyaev

We obtain a constructive criterion for robust no-arbitrage in discrete-time market models with transaction costs. This criterion is expressed in terms of the supports of the regular conditional upper distributions of the solvency cones. We…

Probability · Mathematics 2008-12-10 Dmitry B. Rokhlin

The crisis that affected financial markets in the last years leaded market practitioners to revise well known basic concepts like the ones of discount factors and forward rates. A single yield curve is not sufficient any longer to describe…

Pricing of Securities · Quantitative Finance 2010-06-25 Andrea Pallavicini , Marco Tarenghi

We present an approach, based on deep neural networks, that allows identifying robust statistical arbitrage strategies in financial markets. Robust statistical arbitrage strategies refer to trading strategies that enable profitable trading…

Computational Finance · Quantitative Finance 2024-02-27 Ariel Neufeld , Julian Sester , Daiying Yin

We study the Hull-White model for the term structure of interest rates in the presence of volatility uncertainty. The uncertainty about the volatility is represented by a set of beliefs, which naturally leads to a sublinear expectation and…

Pricing of Securities · Quantitative Finance 2021-01-28 Julian Hölzermann

With model uncertainty characterized by a convex, possibly non-dominated set of probability measures, the agent minimizes the cost of hedging a path dependent contingent claim with given expected success ratio, in a discrete-time,…

Mathematical Finance · Quantitative Finance 2017-09-29 Erhan Bayraktar , Gu Wang

We discuss a simple extension of the Ho and Lee model with generic time-dependent drift in which: 1) we compute bond prices analytically; 2) the yield curve is sensible and the asymptotic yield is positive; and 3) our analytical solution…

Mathematical Finance · Quantitative Finance 2016-01-26 Zura Kakushadze

Over the last decade, nonparametric methods have gained increasing attention for modeling complex data structures due to their flexibility and minimal structural assumptions. In this paper, we study a general multivariate nonparametric…

Methodology · Statistics 2026-03-18 Kunal Rai , Archi Roy , Itai Dattner , Soudeep Deb

This paper develops a flexible and computationally efficient multivariate volatility model, which allows for dynamic conditional correlations and volatility spillover effects among financial assets. The new model has desirable properties…

Methodology · Statistics 2025-07-25 Wenyu Li , Yuchang Lin , Qianqian Zhu , Guodong Li

Based on a criterium of mathematical simplicity and consistency with empirical market data, a stochastic volatility model has been obtained with the volatility process driven by fractional noise. Depending on whether the stochasticity…

Pricing of Securities · Quantitative Finance 2010-07-28 R. Vilela Mendes , Maria João Oliveira

We introduce a discrete binary tree for pricing contingent claims with the underlying security prices exhibiting history dependence characteristic of that induced by market microstructure phenomena. Example dependencies considered include…

Mathematical Finance · Quantitative Finance 2024-02-29 Davide Lauria , W. Brent Lindquist , Svetlozar T. Rachev , Yuan Hu

We consider a general class of continuous asset price models where the drift and the volatility functions, as well as the driving Brownian motions, change at a random time $\tau$. Under minimal assumptions on the random time and on the…

Pricing of Securities · Quantitative Finance 2014-05-15 Claudio Fontana , Zorana Grbac , Monique Jeanblanc , Qinghua Li

We study hedging and pricing of unattainable contingent claims in a non-Markovian regime-switching financial model. Our financial market consists of a bank account and a risky asset whose dynamics are driven by a Brownian motion and a…

Pricing of Securities · Quantitative Finance 2013-03-19 Łukasz Delong , Antoon Pelsser

We propose a method for recovering the structure of a sparse undirected graphical model when very few samples are available. The method decides about the presence or absence of bonds between pairs of variable by considering one pair at a…

Machine Learning · Statistics 2017-01-03 Nicola Bulso , Matteo Marsili , Yasser Roudi

We consider a short rate model, driven by a stochastic process on the cone of positive semidefinite matrices. We derive sufficient conditions ensuring that the model replicates normal, inverse or humped yield curves.

Pricing of Securities · Quantitative Finance 2014-05-08 Alessandro Gnoatto

We consider the estimation problem in a regression setting where the outcome variable is subject to nonignorable missingness and identifiability is ensured by the shadow variable approach. We propose a versatile estimation procedure where…

Methodology · Statistics 2019-07-09 Jiwei Zhao , Yanyuan Ma

The objective of this paper is to provide a comprehensive study no-arbitrage pricing of financial derivatives in the presence of funding costs, the counterparty credit risk and market frictions affecting the trading mechanism, such as…

Mathematical Finance · Quantitative Finance 2018-04-11 Tomasz R. Bielecki , Igor Cialenco , Marek Rutkowski

Confidence intervals and joint confidence sets are constructed for the nonparametric calibration of exponential L\'evy models based on prices of European options. To this end, we show joint asymptotic normality in the spectral calibration…

Statistical Finance · Quantitative Finance 2020-05-26 Jakob Söhl

Many countries have adopted negative interest rate policies with tiering remuneration, which allows for exemption from negative rates. This practice has led to higher interbank trading volumes, with market rates ranging between zero and the…

General Economics · Economics 2026-01-21 Toshifumi Nakamura

A fundamental task in statistical learning is quantifying the joint dependence or association between two continuous random variables. We introduce a novel, fully non-parametric measure that assesses the degree of association between…