Resummation Methods for Analyzing Time Series

TL;DR

This paper introduces a novel approach for analyzing time series data using resummation techniques from theoretical physics, specifically algebraic self-similar renormalization, demonstrated through stock market examples.

Contribution

It develops and illustrates a new resummation-based method for time series analysis using algebraic self-similar renormalization.

Findings

Effective analysis of stock market time series

Demonstrates applicability of physics-based resummation techniques

Provides a new tool for time series analysis

Abstract

An approach is suggested for analyzing time series by means of resummation techniques of theoretical physics. A particular form of such an analysis, based on the algebraic self-similar renormalization, is developed and illustrated by several examples from the stock market time series.