A second-order stock market model

TL;DR

This paper introduces a second-order stock market model that considers both stock rank and identity for return and variance parameters, providing a more detailed framework for analyzing stock behavior.

Contribution

It develops methods for estimating parameters of the second-order model, enhancing the modeling of individual stock dynamics beyond rank-based approaches.

Findings

Second-order models incorporate stock identity for better accuracy.

Estimation methods for second-order model parameters are proposed.

Models demonstrate stability properties suitable for stock analysis.

Abstract

A first-order model for a stock market assigns to each stock a return parameter and a variance parameter that depend only on the rank of the stock. A second-order model assigns these parameters based on both the rank and the name of the stock. First- and second-order models exhibit stability properties that make them appropriate as a backdrop for the analysis of the idiosyncratic behavior of individual stocks. Methods for the estimation of the parameters of second-order models are developed in this paper.