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Predicting institutional ownership using order flow

Published on September 26, 2023 by Navneet Singh Teotia

Introduction

In the realm of stock market analysis, understanding the dynamics of institutional ownership is crucial for investors and analysts alike. Institutional ownership refers to the ownership stake held by institutional investors, such as mutual funds, pension funds and hedge funds, in publicly traded companies. These investors, with their significant financial resources and expertise, play a pivotal role in shaping market trends and influencing stock prices. Unravelling the factors that drive institutional ownership has long been a focus of research in the financial sector.

Against this backdrop, a research paper titled “Caught on Tape: Predicting Institutional Ownership with Order Flow”[1] by John Y Campbell et al offers a fresh perspective on the predictive power of order flow in anticipating changes in institutional ownership. By examining buying and selling activity of retail investors, the research uncovers a new source of data for predicting institutional ownership, adding to the usual factors of market capitalisation and stock returns of businesses.

Order flow

Understanding

In financial markets, order flow refers to the actual trades executed in the market, representing the buying and selling activity of market participants. It captures the collective actions of investors, both individual and institutional, as they make decisions based on their assessment of a company’s prospects and market conditions. Order flow data provides a detailed record of trade size, trade time and trader identity, offering a rich source of information for researchers and market participants.

This order flow data has been matched with records of SEC-mandated 13-F filings of large institutional investors, providing quarterly snapshots of institutional holdings. By regressing changes in institutional ownership on cumulative trades of different sizes, the paper attempts to find the best function mapping trade size to institutional behaviour.

Sources

The authors made use of the Transactions and Quotes (TAQ) database of the New York Stock Exchange. It contains trade-by-trade data pertaining to all listed stocks, beginning in 1993, and records transaction prices and quantities of all trades. However, the database does not classify transactions as buys or sells. An algorithm suggested by Lee and Ready[2] was used to classify the direction of the trade. The trades that could not be classified were assigned to a separate bin, which was used as additional input for the prediction.

The predictive power of order flow

The research paper unravels a compelling relationship between the trading behaviour of retail investors, reflected in order flow data, and the subsequent actions of institutional investors in terms of their ownership decisions.

Institutional ownership has traditionally been analysed through the lens of fundamental factors such as market capitalisation, stock returns and trading volume. While these factors undoubtedly provide valuable insights on institutional investment patterns, the research paper demonstrates that order flow can offer an additional and distinctive signal that goes beyond these conventional metrics.

The analysis reveals that the order flow of retail investors serves as a robust predictor of future changes in institutional ownership. When retail investors engage in net buying for a specific stock, institutions tend to increase their ownership of that stock in the subsequent quarter. Conversely, when investors exhibit net selling activity, institutions tend to reduce their ownership.

Signal beyond traditional factors

What makes the finding of this paper interesting is that the predictive power of order flow surpasses the influence of traditional factors such as market capitalisation, stock returns and trading volume. While these factors have long been considered important determinants of institutional ownership, the research paper highlights the unique information embedded within the order flow of investors. It suggests that order flow data captures market dynamics and investor sentiment in a distinct and powerful way, providing a supplementary signal that traditional factors might overlook.

Implications for investors and analysts

The implications of the research are significant for researchers, financial analysts and fund managers. By paying attention to the order flow of retail investors, market participants can potentially gain an edge in predicting institutional ownership. This information can guide investment strategies and risk management decisions. For institutional investors, understanding the order flow can aid in identifying potential market opportunities and adjusting their own positions accordingly.

Limitations and future directions

As with any research study, it is essential to acknowledge the limitations. The research paper focused on a specific dataset and time period, and the findings may not apply universally across market conditions. Further research could explore if these results can be generalised and investigate the nuances of order flow in different market conditions.

Additional data sources

While the paper primarily underscores the potential of order flow in guiding institutional ownership, informed by stock returns, trade volume and market capitalisation, there exist other elements that could shape institutional ownership decisions:

Corporate governance

Institutional interest can be swayed by a company's governance quality. Entities that promote transparency, cultivate shareholder-aligned incentives and establish competent leadership teams are often held in high regard by institutional stakeholders.

Macroeconomic factors

Broader economic landscapes, encompassing aspects such as inflation, interest rates and overall economic vitality, can dictate the preferences of institutional owners. These entities frequently modify their portfolios to resonate with the prevailing economic scenarios, emphasising sectors or assets that thrive in certain conditions.

Environmental, social and governance (ESG) factors

The modern institutional investor places significant weight on ESG considerations. Firms that champion environmental responsibility, prioritise social welfare and adopt strong governance mechanisms are increasingly being spotlighted by those keen on principled investing.

Analyst ratings

The viewpoints and assessments of market analysts, research entities and credit institutions can steer institutional ownership patterns.

Footnotes:


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About the Author

Data Scientist with 5+ years of industry experience in building Machine Learning and Statistical models across various industries using Python, R, and SQL.

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