Predictors for high frequency processes based on rational polynomials approximation of periodic exponentials

07/01/2022
by   Nikolai Dokuchaev, et al.
0

The paper presents linear integral predictors for continuous time high-frequency processes with a a finite spectrum gap. The predictors are based on approximation of complex valued periodic exponentials (complex sinusoid) by rational polynomials.

READ FULL TEXT
research
02/11/2020

Limited memory predictors with compact explicit representations

The paper presents limited memory time-invariant linear integral predict...
research
02/28/2023

Near-ideal predictors and causal filters for discrete time signals

The paper presents linear predictors and causal filters for discrete tim...
research
01/03/2023

Measuring tail risk at high-frequency: An L_1-regularized extreme value regression approach with unit-root predictors

We study tail risk dynamics in high-frequency financial markets and thei...
research
01/04/2019

Decomposing tropical rational functions

An algorithm is designed which decomposes a tropical univariate rational...
research
06/11/2020

Resiliency by Retrograded Communication- The Revival of Shortwave as a Military Communication Channel

In the last three decades, the great powers have become increasingly dep...
research
08/12/2020

The AAAtrig algorithm for rational approximation of periodic functions

We present an extension of the AAA (adaptive Antoulas–Anderson) algorith...
research
03/06/2018

Predictability of sequences and subsequences with spectrum degeneracy at periodically located points

The paper established sufficient conditions of predictability with degen...

Please sign up or login with your details

Forgot password? Click here to reset