Mapping Intraday Stock Correlations and Daily Market Structure

Summary

This article examines correlations and co-movements among stocks to study intraday seasonality and market evolution. Using intraday CAC 40 data, it revisits earlier findings that average stock correlations rise over the course of the trading day. It applies multidimensional scaling (MDS) to create maps that show how the market’s correlation structure changes over time, but reports no pronounced structural differences within a day.

The study also applies MDS to daily data to visualize market sectors and periods of crisis. The authors suggest that these maps could help identify candidate stocks for pairs trading. This is a visualization and exploratory analysis approach rather than a tested trading strategy: the document gives no trade rules, out-of-sample results, or evidence that MDS-selected pairs are profitable. Its intraday findings are based on CAC 40 data, and the summary does not specify the data period or robustness checks.

Key ideas

• Average stock correlations in the intraday CAC 40 data rise through the trading day, consistent with earlier findings.
• MDS maps are used to visualize changes in correlation structure during the day.
• The study finds no marked intraday change in the market’s overall structure.
• Daily-data maps may reveal sectors and periods of crisis.
• The authors propose the maps as a way to find candidate pairs, but do not report strategy performance.

Tags

# Study of statistical correlations in intraday and daily financial return time series


# Study of statistical correlations in intraday and daily financial return time series









The aim of this article is to briefly review and make new studies of correlations and co-movements of stocks, so as to understand the "seasonalities" and market evolution. Using the intraday data of the CAC40, we begin by reasserting the findings of Allez and Bouchaud [New J. Phys. 13, 025010 (2011)]: the average correlation between stocks increases throughout the day. We then use multidimensional scaling (MDS) in generating maps and visualizing the dynamic evolution of the stock market during the day. We do not find any marked difference in the structure of the market during a day. Another aim is to use daily data for MDS studies, and visualize or detect specific sectors in a market and periods of crisis. We suggest that this type of visualization may be used in identifying potential pairs of stocks for "pairs trade".

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.