Deviation probability bounds for fractional martingales and related remarks

User-friendly Tail Bounds for Matrix Martingales

This report presents probability inequalities for sums of adapted sequences of random, self-adjoint matrices. The results frame simple, easily verifiable hypotheses on the summands, and they yield strong conclusions about the large-deviation behavior of the maximum eigenvalue of the sum. The methods also specialize to sums of independent random matrices. 1. Main Results This technical report is...

Bounds for Singular Fractional Integrals and Related Fourier Integral Operators

Fractional Probability Measure and Its Properties

Based on recent studies by Guy Jumarie [1] which defines probability density of fractional order and fractional moments by using fractional calculus (fractional derivatives and fractional integration), this study expands the concept of probability density of fractional order by defining the fractional probability measure, which leads to a fractional probability theory parallel to the classical ...

A Large Deviation Principle for Martingales over Brownian Filtration

In this article we establish a large deviation principle for the family {ν ε : ε ∈ (0, 1)} of distributions of the scaled stochastic processes {P − log √ ε Z t } t≤1 , where (Z t) t∈[0,1] is a square-integrable martingale over Brownian filtration and (P t) t≥0 is the Ornstein-Uhlenbeck semigroup. The rate function is identified as well in terms of the Wiener-Itô chaos decomposition of the termi...

A large-deviation inequality for vector-valued martingales

Let X = (X0, . . . , Xn) be a discrete-time martingale taking values in any real Euclidean space such that X0 = 0 and for all n, ‖Xn − Xn−1‖ ≤ 1. We prove the large deviation bound Pr [‖Xn‖ ≥ a] < 2e1−(a−1) 2/2n. This upper bound is within a constant factor, e2, of the AzumaHoeffding Inequality for real-valued martingales. This improves an earlier result of O. Kallenberg and R. Sztencel (1992)....