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Starting from an iterative and hence numerically easily implementable representation of the thin set of jumps of a c\`{a}dl\`{a}g adapted stochastic process $X$ (including a few applications to the integration with respect to the jump…

Probability · Mathematics 2015-08-11 Frank Oertel

Indices of acceptability are well suited to frame the axiomatic features of many performance measures, associated to terminal random cash flows.We extend this notion to classes of c\`adl\`ag processes modelling cash flows over a fixed…

Mathematical Finance · Quantitative Finance 2019-11-07 Christos E. Kountzakis , Damiano Rossello

For any real-valued stochastic process $X$ with c\'rdl\'rg paths we define non-empty family of processes which have locally finite total variation, have jumps of the same order as the process $X$ and uniformly approximate its paths on…

Probability · Mathematics 2017-06-26 Rafał M. Łochowski

Using Vovk's outer measure, which corresponds to a minimal superhedging price, the existence of quadratic variation is shown for "typical price paths" in the space of c\`adl\`ag functions possessing a mild restriction on the jumps directed…

Mathematical Finance · Quantitative Finance 2018-11-14 Rafał M. Łochowski , Nicolas Perkowski , David J. Prömel

We prove that typical (in the model-free finance setting) price paths with jumps may be uniformly approximated with accuracy $c>0$ by paths whose total variation is of order $1/c.$ A more precise result is obtained for semimartingales with…

Probability · Mathematics 2017-06-26 Rafał M. Łochowski

Based on a dyadic approximation of It\^o integrals, we show the existence of It\^o c\`adl\`ag rough paths above general semimartingales, suitable Gaussian processes and non-negative typical price paths. Furthermore, Lyons-Victoir extension…

Probability · Mathematics 2018-11-14 Chong Liu , David J. Prömel

We introduce Generalized Integrated Gradients (GIG), a formal extension of the Integrated Gradients (IG) (Sundararajan et al., 2017) method for attributing credit to the input variables of a predictive model. GIG improves IG by explaining a…

Machine Learning · Computer Science 2019-09-10 John Merrill , Geoff Ward , Sean Kamkar , Jay Budzik , Douglas Merrill

We present two different approaches to stochastic integration in frictionless model free financial mathematics. The first one is in the spirit of It\^o's integral and based on a certain topology which is induced by the outer measure…

Probability · Mathematics 2016-06-28 Nicolas Perkowski , David J. Prömel

The goal of this paper is to define stochastic integrals and to solve stochastic differential equations for typical paths taking values in a possibly infinite dimensional separable Hilbert space without imposing any probabilistic structure.…

Probability · Mathematics 2019-09-30 Daniel Bartl , Michael Kupper , Ariel Neufeld

In this article we show that the payment flow of a linear tax on trading gains from a security with a semimartingale price process can be constructed for all c\`agl\`ad and adapted trading strategies. It is characterized as the unique…

Portfolio Management · Quantitative Finance 2015-07-01 Christoph Kühn , Björn Ulbricht

We consider idealized financial markets in which price paths of the traded securities are cadlag functions, imposing mild restrictions on the allowed size of jumps. We prove the existence of quadratic variation for typical price paths,…

Trading and Market Microstructure · Quantitative Finance 2014-09-01 Vladimir Vovk

We consider pure-jump transaction-level models for asset prices in continuous time, driven by point processes. In a bivariate model that admits cointegration, we allow for time deformations to account for such effects as intraday seasonal…

Statistics Theory · Mathematics 2014-04-15 Alexander Aue , Lajos Horváth , Clifford M. Hurvich , Philippe Soulier

For a finite simplicial graph $\Gamma$, let $G(\Gamma)$ denote the right-angled Artin group on the complement graph of $\Gamma$. In this article, we introduce the notions of "induced path lifting property" and "semi-induced path lifting…

Geometric Topology · Mathematics 2015-12-14 Eon-Kyung Lee , Sang-Jin Lee

We prove that the model-free typical (in the sense of Vovk) c\`adl\`ag price paths with mildly restricted downward jumps possess quadratic variation which does not depend on the specific sequence of partitions as long as these partitions…

Mathematical Finance · Quantitative Finance 2018-05-15 Lesiba Ch. Galane , Rafał M. Łochowski , Farai J. Mhlanga

We use a path integral approach for solving the stochastic equations underlying the financial markets, and we show the equivalence between the path integral and the usual SDE and PDE methods. We analyze both the one-dimensional and the…

Statistical Mechanics · Physics 2008-12-10 Marco Rosa-Clot , Stefano Taddei

Using rough path theory, we provide a pathwise foundation for stochastic It\^o integration, which covers most commonly applied trading strategies and mathematical models of financial markets, including those under Knightian uncertainty. To…

Probability · Mathematics 2024-01-04 Andrew L. Allan , Chong Liu , David J. Prömel

We introduce a model for the dynamics of stock prices based on a non quadratic path integral. The model is a generalization of Ilinski's path integral model, more precisely we choose a different action, which can be tuned to different time…

Computational Finance · Quantitative Finance 2018-12-26 Giovanni Paolinelli , Gianni Arioli

For a real c\`adl\`ag path $x$ we define sequence of semi-explicit quantities, which do not depend on any partitions and such that whenever $x$ is a path of a c\`adl\`ag semimartingale then these quantities tend a.s. to the continuous part…

Probability · Mathematics 2019-01-10 Rafał M. Łochowski

A new approach to stochastic integration is described, which is based on an a.s. pathwise approximation of the integrator by simple, symmetric random walks. Hopefully, this method is didactically more advantageous, more transparent, and…

Probability · Mathematics 2009-07-06 Tamás Szabados , Balázs Székely

A recent article introduced thecontinuous stochastic gradient method (CSG) for the efficient solution of a class of stochastic optimization problems. While the applicability of known stochastic gradient type methods is typically limited to…

Optimization and Control · Mathematics 2021-11-16 Lukas Pflug , Max Grieshammer , Andrian Uihlein , Michael Stingl
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