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The research presented in this article provides an alternative option pricing approach for a class of rough fractional stochastic volatility models. These models are increasingly popular between academics and practitioners due to their…

Pricing of Securities · Quantitative Finance 2019-08-02 Raul Merino , Jan Pospíšil , Tomáš Sobotka , Tommi Sottinen , Josep Vives

In this paper we derive an effective equation for derivative pricing which accounts for the presence of virtual arbitrage opportunities and their elimination by the market. We model the arbitrage return by a stochastic process and find an…

Statistical Mechanics · Physics 2008-12-02 Kirill Ilinski , Alexander Stepanenko

Financial models are studied where each asset may potentially lose value relative to any other. Conditioning on non-devaluation, each asset can serve as proper num\'eraire and classical valuation rules can be formulated. It is shown when…

Pricing of Securities · Quantitative Finance 2017-10-19 Travis Fisher , Sergio Pulido , Johannes Ruf

Under suitable assumptions of regularity and non-degeneracy on the covariance of the driving additive noise, any Markov solution to the stochastic Navier-Stokes equations has an associated generator of the diffusion and is the unique…

Probability · Mathematics 2009-02-10 Marco Romito

In a Markovian model for a financial market, we characterize the best arbitrage with respect to the market portfolio that can be achieved using nonanticipative investment strategies, in terms of the smallest positive solution to a parabolic…

Computational Finance · Quantitative Finance 2010-10-26 Daniel Fernholz , Ioannis Karatzas

A central problem of Quantitative Finance is that of formulating a probabilistic model of the time evolution of asset prices allowing reliable predictions on their future volatility. As in several natural phenomena, the predictions of such…

Statistical Finance · Quantitative Finance 2012-09-25 Fulvio Baldovin , Dario Bovina , Francesco Camana , Attilio L. Stella

We establish four structural results for signature volatility models. First, we prove global existence and uniqueness of strong solutions to the signature SDE $dS_t = S_t \langle \ell, \widehat{W}_t \rangle \, dB_t$ on the weighted tensor…

Mathematical Finance · Quantitative Finance 2026-05-19 Akmal Xodarev

This thesis develops a mathematical framework for the analysis of continuous-time trading strategies which, in contrast to the classical setting of continuous-time finance, does not rely on stochastic integrals or other probabilistic…

Probability · Mathematics 2016-02-16 Candia Riga

We develop a general approach to estimating the derivative of a function-valued parameter $\theta_o(u)$ that is identified for every value of $u$ as the solution to a moment condition. This setup in particular covers many interesting models…

Methodology · Statistics 2016-10-31 Christoph Rothe , Dominik Wied

We consider asset price models whose dynamics are described by linear functions of the (time extended) signature of a primary underlying process, which can range from a (market-inferred) Brownian motion to a general multidimensional…

Mathematical Finance · Quantitative Finance 2022-07-28 Christa Cuchiero , Guido Gazzani , Sara Svaluto-Ferro

In this paper, we propose the uncertain volatility models with stochastic bounds. Like the regular uncertain volatility models, we know only that the true model lies in a family of progressively measurable and bounded processes, but instead…

Mathematical Finance · Quantitative Finance 2017-02-17 Jean-Pierre Fouque , Ning Ning

We introduce polynomial processes in the sense of [8] in the context of stochastic portfolio theory to model simultaneously companies' market capitalizations and the corresponding market weights. These models substantially extend volatility…

Mathematical Finance · Quantitative Finance 2017-05-12 Christa Cuchiero

A version of indifference valuation of a European call option is proposed that includes statistical regularities of nonstochastic randomness. Classical relations (forward contract value and Black-Scholes formula) are obtained as particular…

Pricing of Securities · Quantitative Finance 2011-03-22 Yaroslav Ivanenko

We discuss martingales, detrending data, and the efficient market hypothesis for stochastic processes x(t) with arbitrary diffusion coefficients D(x,t). Beginning with x-independent drift coefficients R(t) we show that Martingale stochastic…

Physics and Society · Physics 2009-11-13 Joseph L. McCauley , Kevin E. Bassler , Gemunu H. Gunaratne

In this paper we introduce the concept of conic martingales}. This class refers to stochastic processes having the martingale property, but that evolve within given (possibly time-dependent) boundaries. We first review some results about…

Probability · Mathematics 2016-03-25 Frédéric Vrins , Monique Jeanblanc

In this paper, we investigate specific least action principles for laws of stochastic processes within a framework which stands on filtrations preserving variations. The associated Euler-Lagrange conditions, which we obtain, exhibit a…

Probability · Mathematics 2022-08-08 Rémi Lassalle

The Heston stochastic volatility process, which is widely used as an asset price model in mathematical finance, is a paradigm for a degenerate diffusion process where the degeneracy in the diffusion coefficient is proportional to the square…

Analysis of PDEs · Mathematics 2011-09-07 Panagiota Daskalopoulos , Paul M. N. Feehan

In setting up a stochastic description of the time evolution of a financial index, the challenge consists in devising a model compatible with all stylized facts emerging from the analysis of financial time series and providing a reliable…

Statistical Finance · Quantitative Finance 2009-11-13 Fulvio Baldovin , Attilio L. Stella

This paper presents the solution to a European option pricing problem by considering a regime-switching jump diffusion model of the underlying financial asset price dynamics. The regimes are assumed to be the results of an observed pure…

Pricing of Securities · Quantitative Finance 2019-10-21 Anindya Goswami , Omkar Manjarekar , Anjana R

We introduce a multivariate stochastic volatility model for asset returns that imposes no restrictions to the structure of the volatility matrix and treats all its elements as functions of latent stochastic processes. When the number of…

Machine Learning · Statistics 2017-01-09 P. Dellaportas , A. Plataniotis , M. K. Titsias