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Andrey Sarantsev

Publications and source records attributed to Andrey Sarantsev.

At least 37 records · Page 2Linked to original sources
arXiv2021

Beam-spin asymmetry $\boldsymbolΣ$ for $Σ^-$ hyperon photoproduction off the neutron

We report a new measurement of the beam-spin asymmetry $\boldsymbolΣ$ for the $\vecγ n \rightarrow K^+Σ^-$ reaction using quasi-free neutrons in a liquid-deuterium target. The new dataset includes data at previously unmeasured photon energy and angular ranges, thereby providing new constraints on partial wave analyses used to extract properties of the excited nucleon states. The experimental data were obtained using the CEBAF Large Acceptance Spectrometer (CLAS), housed in Hall B of the Thomas Jefferson National Accelerator Facility (JLab). The CLAS detector measured reaction products from a liquid-deuterium target produced by an energy-tagged, linearly polarised photon beam with energies in the range 1.1 to 2.3 GeV. Predictions from an isobar model indicate strong sensitivity to $N(1720)3/2^+$, $Δ(1900)1/2^-$, and $N(1895)1/2^-$, with the latter being a state not considered in previous photoproduction analyses. When our data are incorporated in the fits of partial-wave analyses, one observes significant changes in $γ$-$n$ couplings of the resonances which have small branching ratios to the $πN$ channel.

nucl-ex↗
arXiv2021

A Stock Market Model Based on CAPM and Market Size

We introduce a new system of stochastic differential equations which models dependence of market beta and unsystematic risk upon size, measured by market capitalization. We fit our model using size deciles data from Kenneth French's data library. This model is somewhat similar to generalized volatility-stabilized models in (Pal, 2011; Pickova, 2013). The novelty of our work is twofold. First, we take into account the difference between price and total returns (in other words, between market size and wealth processes). Second, we work with actual market data. We study the long-term properties of this system of equations, and reproduce observed linearity of the capital distribution curve. Our model has two modifications: for price returns and for equity premium. Somewhat surprisingly, they exhibit the same fit, with very similar coefficients. In the Appendix, we analyze size-based real-world index funds.

q-fin.ST↗
arXiv2021

A Note on Subexponential Rate of Convergence to Equilibrium for Processes on the Half-Line

A powerful tool for studying long-term convergence of a Markov process to its stationary distribution is a Lyapunov function. In some sense, this is a substitute for eigenfunctions. For a stochastically ordered Markov process on the half-line, Lyapunov functions can be used to easily find explicit rates of convergence. Our earlier research focused on exponential rate of convergence. This note extends these results to slower rates, including power rates, thus improving results of (Douc, Fort, Guillin, 2009).

math.PR↗
arXiv2020

Convergence rate to equilibrium in Wasserstein distance for reflected jump-diffusions

Convergence rate to the stationary distribution for continuous-time Markov processes can be studied using Lyapunov functions. Recent work by the author provided explicit rates of convergence in special case of a reflected jump-diffusion on a half-line. These results are proved for total variation distance and its generalizations: measure distances defined by test functions regardless of their continuity. Here we prove similar results for Wasserstein distance, convergence in which is related to convergence for continuou test functions. In some cases, including the reflected Ornstein-Uhlenbeck process, we get faster exponential convergence rates for Wasserstein distance than for total variation distance.

math.PR↗
arXiv2020

Stationary Distributions and Convergence for M/M/1 Queues in Interactive Random Environment

A Markovian single-server queue is studied in an interactive random environment. The arrival and service rates of the queue depend on the environment, while the transition dynamics of the random environment depends on the queue length. We consider in detail two types of Markov random environments: a pure jump process and a reflected jump-diffusion. In both cases, the joint dynamics is constructed so that the stationary distribution can be explicitly found in a simple form (weighted geometric). We also derive an explicit estimate for exponential rate of convergence to the stationary distribution via coupling.

math.PR↗
arXiv2019

Autoregressive Modeling of Forest Dynamics

In this work, we employ autoregressive models developed in financial engineering for modeling of forest dynamics. Autoregressive models have some theoretical advantage over currently employed forest modeling approaches such as Markov chains and individual-based models, as autoregressive models are both analytically tractable and operate with continuous state space. We perform time series statistical analysis of forest biomass and basal area recorded in Quebec provincial forest inventories in 1970-2007. The geometric random walk model adequately describes the yearly average dynamics. For individual patches, we fit an AR(1) process capable to model negative feedback (mean-reversion). Overall, the best fit also turns out to be geometric random walk, however, the normality tests for residuals fail. In contrast, yearly means are adequately described by normal fluctuations, with annual growth, on average, 2.3%, but with standard deviation of order 40%. We use Bayesian analysis to account for uneven number of observations per year. This work demonstrates that autoregressive models represent a valuable tool for modeling of forest dynamics. In particular, they quantify stochastic effects of environmental disturbances and develop predictive empirical models on short and intermediate temporal scales.

q-bio.QM↗
arXiv2019

Partisan Lean of States: Electoral College and Popular Vote

We compare federal election results for each state versus the USA in every second year from 1992 to 2018, to model partisan lean of each state and its dependence on the nationwide popular vote. For each state, we model both its current partisan lean and its rate of change, as well as sensitivity of state results with respect to the nationwide popular vote, using Bayesian linear regression. We apply this to simulate the Electoral College outcome in 2020, given even (equal) nationwide popular vote, as well as 2016, 2008, and 2004 nationwide popular vote. We backtest 2012 and 2016 elections given actual popular vote. Taking equal popular vote for two major parties, we prove that the Electoral College is biased towards Republicans.

stat.AP↗
arXiv2019

A Note on Jump Atlas Models

The market weight of a stock is its capitalization (cap) divided by the total market cap. Rank these weights from top to bottom. The capital distribution curve is a plot of weights versus ranks. For the US stock market, it is linear on a double logarithmic scale, and stable with respect to time (Fernholz, 2002). This property has been captured by models with rank-dependent dynamics: Each stock's cap logarithm is a Brownian motion with drift and diffusion coefficients depending on its current rank (Chatterjee, Pal, 2010). However, short-term stock movements have heavy tails. One can add jumps to Brownian motions to capture this. Observed time stability follows from a long-term stability result, stated and proved here. Via simulations, we find which properties of continuous models are preserved after adding jumps.

math.PR↗
arXiv2019

Dynamic Contagion in a Banking System with Births and Defaults

We consider a dynamic model of interconnected banks. New banks can emerge, and existing banks can default, creating a birth-and-death setup. Microscopically, banks evolve as independent geometric Brownian motions. Systemic effects are captured through default contagion: as one bank defaults, reserves of other banks are reduced by a random proportion. After examining the long-term stability of this system, we investigate mean-field limits as the number of banks tends to infinity. Our main results concern the measure-valued scaling limit which is governed by a McKean-Vlasov jump-diffusion. The default impact creates a mean-field drift, while the births and defaults introduce jump terms tied to the current distribution of the process. Individual dynamics in the limit is described by the propagation of chaos phenomenon. In certain cases, we explicitly characterize the limiting average reserves.

math.PR↗
arXiv2019

Large Rank-Based Models with Common Noise

For large systems of Brownian particles interacting through their ranks introduced in (Banner, Fernholz, Karatzas, 2005), the empirical cumulative distribution function satisfies a porous medium PDE. However, when we introduce a common noise, the limit is no longer deterministic. Instead, we show that this limit is a solution of a stochastic PDE related to this porous medium PDE. This stochastic PDE is somewhat similar to the equations developed for conservation laws with rough stochastic fluxes (Lions, Perthame, Souganidis, 2013).

math.PR↗
arXiv2019

A Note on Transportation Cost Inequalities for Diffusions with Reflections

We prove that reflected Brownian motion with normal reflections in a convex domain satisfies a dimension free Talagrand type transportation cost-information inequality. The result is generalized to other reflected diffusions with suitable drifts and diffusions. We apply this to get such an inequality for interacting Brownian particles with rank-based drift and diffusion coefficients such as the infinite Atlas model. This is an improvement over earlier dimension-dependent results.

math.PR↗
arXiv2018

Talagrand Concentration Inequalities for Stochastic Partial Differential Equations

One way to define the concentration of measure phenomenon is via Talagrand inequalities, also called transportation-information inequalities. That is, a comparison of the Wasserstein distance from the given measure to any other absolutely continuous measure with finite relative entropy. Such transportation-information inequalities were recently established for some stochastic differential equations. Here, we develop a similar theory for some stochastic partial differential equations.

math.PR↗
arXiv2018

Modeling Financial System with Interbank Flows, Borrowing, and Investing

In our model, private actors with interbank cash flows similar to, but nore general than (Carmona, Fouque, Sun, 2013) borrow from the outside economy at a certain interest rate, controlled by the central bank, and invest in risky assets. Each private actor aims to maximize its expected terminal logarithmic utility. The central bank, in turn, aims to control the overall economy by means of an exponential utility function. We solve all stochastic optimal control problems explicitly. We are able to recreate occasions such as liquidity trap. We study distribution of the number of defaults (net worth of a private actor going below a certain threshold).

q-fin.RM↗
arXiv2018

Convergence and Stationary Distributions for Walsh Diffusions

A Walsh diffusion on Euclidean space moves along each ray from the origin, as a solution to a stochastic differential equation with certain drift and diffusion coefficients, as long as it stays away from the origin. As it hits the origin, it instantaneously chooses a new direction according to a given probability law, called the spinning measure. A special example is a real-valued diffusion with skew reflections at the origin. This process continuously (in the weak sense) depends on the spinning measure. We determine a stationary measure for such process, explore long-term convergence to this distribution and establish an explicit rate of exponential convergence.

math.PR↗
arXiv2017

Brownian Particles with Rank-Dependent Drifts: Out-of-Equilibrium Behavior

We study the long-range asymptotic behavior for an out-of-equilibrium countable one-dimensional system of Brownian particles interacting through their rank-dependent drifts. Focusing on the semi-infinite case, where only the leftmost particle gets a constant drift to the right, we derive and solve the corresponding one- sided Stefan (free-boundary) equations. Via this solution we explicitly determine the limiting particle-density profile as well as the asymptotic trajectory of the leftmost particle. While doing so we further establish stochastic domination and convergence to equilibrium results for the vector of relative spacings among the leading particles.

math.PR↗
arXiv2017

Weak Convergence of Obliquely Reflected Diffusions

Burdzy and Chen (1998) proved results on weak convergence of multidimensional normally reflected Brownian motions. We generalize their work by considering obliquely reflected diffusion processes. We require weak convergence of domains, which is stronger than convergence in Wijsman topology, but weaker than convergence in Hausdorff topology.

math.PR↗
arXiv2017

Two-Sided Infinite Systems of Competing Brownian Particles

Two-sided infinite systems of Brownian particles with rank-dependent dynamics, indexed by all integers, exhibit different properties from their one-sided infinite counterparts, indexed by positive integers, and from finite systems. Consider the gap process, which is formed by spacings between adjacent particles. In stark contrast with finite and one-sided infinite systems, two-sided infinite systems can have one- or two-parameter family of stationary gap distributions, or the gap process weakly converging to zero as time goes to infinity.

math.PR↗