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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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1122 · Mar 201319922001200920172026
34 results for semi-martingales

The paper develops a method for stochastic differential equations on manifolds using Schwartz morphisms and diffusion generators.

problem Representing stochastic differential equations on smooth manifolds.
method Using Schwartz morphisms and diffusion generators to construct SDEs on manifolds.
result An extended Ito formula for SDEs on manifolds.

This paper studies the problem of maximizing expected utility from terminal wealth combining a static position in derivative securities, which we assume can be traded only at time zero, with a traditional dynamic trading strategy in stocks. We work in the framework of a general semi-martingale model and consider a util…

2012-10-19abs ↗pdf ↗

This paper studies the problem of maximizing expected utility from terminal wealth in a semi-static market composed of derivative securities, which we assume can be traded only at time zero, and of stocks, which can be traded continuously in time and are modeled as locally-bounded semi-martingales. Using a general util…

2013-03-01abs ↗pdf ↗

This paper is concerned with the estimation of the volatility process in a stochastic volatility model of the following form: dXt=atdt+σtdWtdX_t=a_tdt+σ_tdW_t, where XX denotes the log-price and σσ is a càdlàg semi-martingale. In the spirit of a series of recent works on the estimation of the cumulated volatility, we here focus …

2008-12-18abs ↗pdf ↗

In this paper, we study a semi-martingale optimal transport problem and its application to the calibration of Local-Stochastic Volatility (LSV) models. Rather than considering the classical constraints on marginal distributions at initial and final time, we optimise our cost function given the prices of a finite number…

2019-06-15abs ↗pdf ↗

We study the properties of nonlinear Backward Stochastic Differential Equations (BSDEs) driven by a Brownian motion and a martingale measure associated with a default jump with intensity process (λt)(λ_t). We give a priori estimates for these equations and prove comparison and strict comparison theorems. These results ar…

2016-12-16abs ↗pdf ↗

Approximations to utility indifference prices are provided for a contingent claim in the large position size limit. Results are valid for general utility functions on the real line and semi-martingale models. It is shown that as the position size approaches infinity, the utility function's decay rate for large negative…

2012-02-17abs ↗pdf ↗

Study on stochastic covariant derivatives in curved space-time.

problem Analyzing covariant derivatives in curved space-time under stochastic processes.
method Using Itô-Wiener processes and stochastic calculus, including Besov spaces, Schrödinger operators, and white noise.
result Developed a framework for stochastic geodesics and white noise in fractoid spaces.

We discuss the finite sample theoretical properties of online predictions in non-stationary time series under model misspecification. To analyze the theoretical predictive properties of statistical methods under this setting, we first define the Kullback-Leibler risk, in order to place the problem within a decision the…

2019-11-20abs ↗pdf ↗

In this paper we study the exponential functionals of the processes XX with independent increments , namely It=0texp(Xs)ds,,t0,I_t= \int _0^t\exp(-X_s)ds, _,\,\, t\geq 0, and also I=0exp(Xs)ds.I_{\infty}= \int _0^{\infty}\exp(-X_s)ds. When XX is a semi-martingale with absolutely continuous characteristics, we derive recurrent integral equat…

2016-10-27abs ↗pdf ↗

We study optimal investment in an asset subject to risk of default for investors that rely on different levels of information. The price dynamics can include noises both from a Wiener process and a Poisson random measure with infinite activity. The default events are modelled via a counting process in line with large p…

2013-12-20abs ↗pdf ↗

The paper derives the QGS equations using stochastic central extensions.

problem Deriving the viscous quasi-geostrophic equations on the torus.
method Central extensions of Lie groups and Lie algebras, stochastic Lagrangian formulation, and Euler-Poincaré reduction.
result Stochastic perturbations to the central extension lead to solutions of the QGS equations.

We study utility indifference prices and optimal purchasing quantities for a non-traded contingent claim in an incomplete semi-martingale market with vanishing hedging errors. We make connections with the theory of large deviations. We concentrate on sequences of semi-complete markets where in the nthn^{th} market, the …

2014-10-01abs ↗pdf ↗

Optimal linear contracts are possible even with memory in Gaussian settings.

problem Can optimal dynamic contracts be linear when agents control memory processes?
method Developed a methodology for non-Markovian and non-semimartingale settings, showed linear contracts are optimal for one-dimensional models.
result Linear contracts are optimal for one-dimensional models with memory, and for radial effort cost functions in higher dimensions.

We consider a stochastic control problem for a class of nonlinear kernels. More precisely, our problem of interest consists in the optimisation, over a set of possibly non-dominated probability measures, of solutions of backward stochastic differential equations (BSDEs). Since BSDEs are nonlinear generalisations of the…

2015-10-28abs ↗pdf ↗

In this paper we apply Markovian approximation of the fractional Brownian motion (BM), known as the Dobric-Ojeda (DO) process, to the fractional stochastic volatility model where the instantaneous variance is modelled by a lognormal process with drift and fractional diffusion. Since the DO process is a semi-martingale,…

2019-04-19abs ↗pdf ↗

It has been understood that the "local" existence of the Markowitz' optimal portfolio or the solution to the local-risk minimization problem is guaranteed by some specific mathematical structures on the underlying assets price processes known in the literature as "{\it Structure Conditions}". In this paper, we consider…

2014-03-13abs ↗pdf ↗

This paper proposes a new framework for financial risk that considers predictability rather than volatility.

problem Volatility's limitations as a risk measure, especially in complex strategies and non-stationary markets.
method Developed a new paradigm based on stochastic processes and the Multifractional Process with Random Exponent (MPRE) framework.
result A formal definition of 'fair volatility' that aligns with market efficiency and provides a measure of market inefficiency.

Method detects jumps in high-frequency order prices using local minima.

problem Detecting jumps in high-frequency order prices with noisy data.
method Developed methods to estimate, locate and test for jumps using local minima of best ask quotes.
result Consistently estimated jump sizes and times, established asymptotic properties of tests, and demonstrated faster convergence rates.

Method learns radial basis function distributions from samples.

problem Learning radial basis function distributions from training samples.
method Projected particle Langevin optimization method with distributionally robust optimization.
result Empirical measure of Langevin particles converges to a reflected Itô diffusion-drift process.