STOCK MARKET INDEX DYNAMICS AND MARKET ACTIVITY

This paper proposes a parsimonious model for stock market index dynamics grounded in information theory. It models market activity, the derivative of the market time, as a linear function of the squared derivative of an exponential moving average from a proxy of the single driving Brownian motion. The normalized index is following in market time a Cox–Ingersoll–Ross process with dimension 4. In calendar time, major shifts in the driving Brownian motion cause spikes in market activity. Applied to S&P500 data, the model accurately extracts the potential driving Brownian motion, which withstands rejection as a Brownian motion by a joint variance ratio test, providing a realistic representation of the stock index dynamics.

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Publication Details

Journal
International Journal of Theoretical and Applied Finance
Published
2026-06-17
DOI
https://doi.org/10.1142/s0219024926500147
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

STOCK MARKET INDEX DYNAMICS AND MARKET ACTIVITY

Renata Rendek, Eckhard Platen
International Journal of Theoretical and Applied Finance
Complex Systems and Time Series Analysis
article

STOCK MARKET INDEX DYNAMICS AND MARKET ACTIVITY

Renata Rendek, Eckhard Platen
article en

Abstract

This paper proposes a parsimonious model for stock market index dynamics grounded in information theory. It models market activity, the derivative of the market time, as a linear function of the squared derivative of an exponential moving average from a proxy of the single driving Brownian motion. The normalized index is following in market time a Cox–Ingersoll–Ross process with dimension 4. In calendar time, major shifts in the driving Brownian motion cause spikes in market activity. Applied to S&P500 data, the model accurately extracts the potential driving Brownian motion, which withstands rejection as a Brownian motion by a joint variance ratio test, providing a realistic representation of the stock index dynamics.

International Journal of Theoretical and Applied Finance
University of Technology Sydney (AU), UNSW Sydney (AU)
Australian Research Council
Openalex Percentile: Top 3%
Complex Systems and Time Series Analysis
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