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Motivated by empirical evidence from the joint behavior of realized volatility time series, we propose to model the joint dynamics of log-volatilities using a multivariate fractional Ornstein-Uhlenbeck process. This model is a multivariate…

Statistical Finance · Quantitative Finance 2026-05-19 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among many complex systems in science and engineering. The existence of a strange attractor in the turbulent…

Fluid Dynamics · Physics 2018-02-23 Andrew J. Majda , Di Qi

The Fokker--Planck equation is a key ingredient of many models in physics, and related subjects, and arises in a diverse array of settings. Analytical solutions are limited to special cases, and resorting to numerical simulation is often…

Mathematical Physics · Physics 2019-02-20 R. J. Martin , R. V. Craster , A. Pannier , M. J. Kearney

We study the large deviations of the power injected by the active force for an Active Ornstein-Uhlenbeck Particle (AOUP), free or in a confining potential. For the free-particle case, we compute the rate function analytically in…

Statistical Mechanics · Physics 2022-01-03 Massimiliano Semeraro , Antonio Suma , Isabella Petrelli , Francesco Cagnetta , Giuseppe Gonnella

Global oil price is an important factor in determining many economic variables in the world's economy. It is generally modeled as a stochastic process and have been studied through different techniques by comparing the historic time series…

General Finance · Quantitative Finance 2018-05-31 Sina Aghaei

A one-factor asset pricing model with an Ornstein--Uhlenbeck process as its state variable is studied under partial information: the mean-reverting level and the mean-reverting speed parameters are modeled as hidden/unobservable stochastic…

Pricing of Securities · Quantitative Finance 2014-06-18 Takashi Kato , Jun Sekine , Hiromitsu Yamamoto

We show that disentangling sentiment-induced biases from fundamental expectations significantly improves the accuracy and consistency of probabilistic forecasts. Using data from 1994 to 2017, we analyze 15 stochastic models and…

Risk Management · Quantitative Finance 2021-01-26 Ricardo Crisóstomo

The 2030 Agenda for Sustainable Development of the United Nations outlines 17 goals as global challenges for countries of the world to address in their development. However, the progress of countries towards these goals has been much slower…

A deterministic multiscale toy model is studied in which a chaotic fast subsystem triggers rare transitions between slow regimes, akin to weather or climate regimes. Using homogenization techniques, a reduced stochastic parametrization…

Data Analysis, Statistics and Probability · Physics 2012-04-11 Lewis Mitchell , Georg A. Gottwald

This work is concerned with model reduction of stochastic differential equations and builds on the idea of replacing drift and noise coefficients of preselected relevant, e.g. slow variables by their conditional expectations. We extend…

Analysis of PDEs · Mathematics 2020-03-05 Carsten Hartmann , Lara Neureither , Upanshu Sharma

Over the last few decades, climate scientists have devoted much effort to the development of large numerical models of the atmosphere and the ocean. While there is no question that such models provide important and useful information on…

Atmospheric and Oceanic Physics · Physics 2009-08-25 Michel Crucifix , Jonathan Rougier

Modern methods of generative modelling and unpaired data translation based on Schr\"odinger bridges and stochastic optimal control theory aim to transform an initial density to a target one in an optimal way. In the present paper, we assume…

Machine Learning · Computer Science 2026-03-24 Nikita Puchkin , Denis Suchkov , Alexey Naumov , Denis Belomestny

We reinterpret Starobinsky's stochastic inflation as an open quantum system, where short-wavelength modes act as the environment for long-wavelength modes. Using the Schwinger-Keldysh formalism, we systematically trace out the environment…

High Energy Physics - Theory · Physics 2025-09-16 Yue-Zhou Li

We propose a new model for the joint evolution of the European inflation rate, the European Central Bank official interest rate and the short-term interest rate, in a stochastic, continuous time setting. We derive the valuation equation for…

Mathematical Finance · Quantitative Finance 2022-12-22 F. Antonacci , C. Costantini , F. D'Ippoliti , M. Papi

In electricity markets, it is sensible to use a two-factor model with mean reversion for spot prices. One of the factors is an Ornstein-Uhlenbeck (OU) process driven by a Brownian motion and accounts for the small variations. The other…

Pricing of Securities · Quantitative Finance 2013-08-16 Fred Espen Benth , Salvador Ortiz-Latorre

Using observational data and an elementary rigorous statistical fact it is easily shown that the distribution of Earth's climate is non-stationary. Examination of records of hundreds of local Industrial Era temperature histories in the…

Atmospheric and Oceanic Physics · Physics 2022-01-21 Juan M. Restrepo , Michael E. Mann

The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. We show for the first time…

Statistical Mechanics · Physics 2011-10-11 Valerio Lucarini , Stefania Sarno

We develop a mechanistic model to analyze the impact of sulfur dioxide emissions from coal-fired power plants on average sulfate concentrations in the central United States. A multivariate Ornstein-Uhlenbeck (OU) process is used to…

Methodology · Statistics 2020-10-12 Nathan B. Wikle , Ephraim M. Hanks , Lucas R. F. Henneman , Corwin M. Zigler

We study the stochastic growth process in discrete time $x_{i+1} = (1 + \mu_i) x_i$ with growth rate $\mu_i = \rho e^{Z_i - \frac12 var(Z_i)}$ proportional to the exponential of an Ornstein-Uhlenbeck (O-U) process $dZ_t = - \gamma Z_t dt +…

Probability · Mathematics 2022-09-07 Dan Pirjol

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental…

Computational Physics · Physics 2023-06-14 John Strahan , Justin Finkel , Aaron R. Dinner , Jonathan Weare
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