Results 11 to 20 of about 207,950 (53)
Sticky processes, local and true martingales [PDF]
We prove that for a so-called sticky process $S$ there exists an equivalent probability $Q$ and a $Q$-martingale $\tilde{S}$ that is arbitrarily close to $S$ in $L^p(Q)$ norm.
M. Rásonyi, Hasanjan Sayit
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The celebrated theorem of Halmos and Savage implies that if M is a set of P-absolutely continuous probability measures Q on (Ω, F, P) such that each A ∈ F,P(A) > 0 is charged by some Q ∈ M, that is, Q(A) > 0 (where the choice of Q depends on the set A ...
I. Klein, W. Schachermayer
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On a probability space (Ω,A,Q) we consider two filtrations F ⊆ G and a G stopping time θ such that the G predictable processes coincide with F predictable processes on (0, θ].
St'ephane Cr'epey, Shiqi Song
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Quantum Computing for Financial Mathematics [PDF]
Quantum computing has recently appeared in the headlines of many scientific and popular publications. In the context of quantitative finance, we provide here an overview of its potential.
arxiv
Practical Finance Strategies in Immunization
My first goal is to present the basic immunization problem (BIP) as it is understood in finance. BIP relies on a construction of such a bond portfolio (BP), meaning a selection of individual bonds, that the single liability to pay L dollars q years from ...
L. Zaremba
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The exact Taylor formula of the implied volatility [PDF]
In a model driven by a multidimensional local diffusion, we study the behavior of the implied volatility σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage ...
Stefano Pagliarani, A. Pascucci
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Backward SDE representation for stochastic control problems with nondominated controlled intensity. [PDF]
We are interested in stochastic control problems coming from mathematical finance and, in particular, related to model uncertainty, where the uncertainty affects both volatility and intensity.
S'ebastien Choukroun, Andrea Cosso
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Diamonds and forward variance models [PDF]
In this non-technical introduction to diamond trees and forests, we focus on their application to computation in stochastic volatility models written in forward variance form, rough volatility models in particular.
arxiv
CARMA Approximations and Estimation
CARMA(p, q) processes are compactly defined through a stochastic differential equation (SDE) involving q + 1 derivatives of the Lévy process driving the noise, despite this latter having in general no differentiable paths.
Silvia Lavagnini
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Explicit Computations for Delayed Semistatic Hedging [PDF]
In this work we consider the exponential utility maximization problem in the framework of semistatic hedging.
arxiv