Informed Trading Probability in Exchange-traded Funds on the Tehran Stock Exchange: A Market Microstructure Approach

Document Type : Research Paper

Authors

1 Associate Prof., Department of Financial Engineering, Faculty of Accounting and Financial Sciences, College of Management, University of Tehran, Tehran, Iran.

2 Assistant Prof., Faculty of Accounting and Financial Sciences, College of Management, University of Tehran, Tehran, Iran

3 Ph.D. Candidate, Department of Financial Engineering, Kish International Campus, University of Tehran, Tehran, Iran.

Abstract

Objective
Informed trading, as a key factor undermining market transparency and efficiency, plays a pivotal role in investor decision-making and risk management. Accordingly, identifying and quantifying such trading activities at the microstructure level of the market is of critical importance. Given the growing presence of exchange-traded equity funds (ETFs) in Iran’s capital market and the need for enhanced transparency and regulatory oversight, this study aims to propose a robust and reliable index for measuring information asymmetry within these financial institutions.
 
Methods
The foundational model for estimating the extent of informed trading is the Probability of Informed Trading (PIN) model. This well-established measure in financial economics captures the likelihood of informed traders’ participation in the market and reflects the degree of information asymmetry in trading activity. Over time, the PIN model has undergone refinements to address computational inefficiencies and the complexity of multi-parameter estimation. A prominent advancement is the Volume-Synchronized Probability of Informed Trading (VPIN) model, which offers superior speed and accuracy, requires fewer parameter estimations, and incorporates a volume-based framework that enables continuous updating. By addressing the primary limitation of the original model—its disregard for trading volume—VPIN facilitates a more precise assessment of informed trading probabilities. The dataset used in this study consists of intraday price, time, and volume data for 92 equity exchange-traded funds listed on the Tehran Stock Exchange, covering the period from April 2019 to March 2025. To compute the VPIN index, real-time data on trade time, volume, and price were collected and processed, yielding VPIN values for each fund across the specified timeframe. Additionally, the funds were categorized based on variables such as assets under management and the industry sector of investment (sectoral ETFs), allowing for an examination of structural factors influencing informed trading levels.
 
Results
The results reveal significant variation in the probability of informed trading across the studied funds. Specifically, funds with larger assets under management (AUM) exhibited lower average VPIN values compared to smaller funds. Furthermore, sector-specific funds investing in different industries display varying VPIN levels. Moreover, funds investing in less transparent and specialized industries demonstrated higher average VPIN scores. These differences suggest that structural factors—including fund size, the nature of the target industry, and investor trading behavior— significantly influence the extent of informed trading.
 
Conclusion
This study contributes to the literature by introducing an analytical framework grounded in the VPIN methodology to identify and quantify information asymmetry among ETFs operating in Iran’s capital market. The findings—encompassing VPIN monitoring across sectoral, small, medium, and large equity funds—underscore the necessity for regulatory authorities and policymakers to consider variables such as fund structure, industry focus, and trading volume in efforts to enhance market transparency and mitigate informational inequality. Furthermore, the VPIN index proves to be an effective analytical tool for modeling informational risk in ETFs and offers a foundation for developing intelligent regulatory monitoring systems. Ultimately, the insights derived from this research hold practical relevance for investor decision-making, strategic trading design, and the advancement of capital market oversight policies.

Keywords

Main Subjects

References

 
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Financial Research Journal
Volume 28, Issue 1
2026
Pages 300-326

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