Estimating Information Asymmetry using Market Microstructure Measures; A Case Study of Energy Sector Companies Listed in the Iranian Stock Exchange

Mohajeri, Parisa; Taleblou, Reza

doi:10.22054/jiee.2023.75617.2036

Document Type : Research Paper

Authors

Associate Professor of Economics, Department of Economics, Allemeh Tabataba’i University, Tehran, Iran.

https://doi.org/10.22054/jiee.2023.75617.2036

Abstract

The Probability of Informed Trading (PIN) is one of the important measures of market microstructure that is generally used to estimate the level of information asymmetry. Estimating PIN can be challenging due to boundary solutions, local maxima, and Floating Point Exceptions (FPE). Additionally, the prevailing assumption of the existence of only one information layer per trading day in PIN is inconsistent with the real-world empirical evidence and exposes it to a considerable underestimation bias. In this paper, we estimate information asymmetry for 55 listed companies in the energy sector during the period from 2017:Q1 to 2023:Q2, utilizing the Multi-Layer Probability of Informed Trading (MPIN) model introduced by Ghachem and Ersan (2023). The findings indicate: First, the assumption of a single information layer is satisfied for only 2.67% of the 1,200 stock/season observations, which implies the necessity of using MPIN to estimate information asymmetry. Second, the use of PIN not only leads to significant underestimation bias, but also provides an inaccurate picture of the ranking of companies from the perspective of information asymmetry. Third, the energy sector faces an average information asymmetry of 34.4%, and estimations reveal that private information reached its peak in the summer of 2020, exceeding 49%. Fourth, the symbols "Bepeyvand" from the electricity, gas, and steam sub-sector and "Shapna" from the refining sub-sector hold the highest (64.75%) and lowest (18.9%) information asymmetry, respectively.
Abstract should be written in one paragraph and the subject matter (one or two sentences), purpose (one sentence), method (in two to three sentences including research design, statistical population, sample number, sampling method, intervention, instruments (Full name of the instrument, designer's name, and year of the design}, data analysis method (the name of the software used should not be stated), results (two to three sentences including key findings without mentioning the numbers) and conclusions (two sentences) (Verbs should be in past tense).

Keywords

Main Subjects

سیاستگذاری‌های اقتصادی و مالی در حوزه‌های فوق‌الذکر در سطوح ملی، منطقه‌ای و جهانی

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Estimating Information Asymmetry using Market Microstructure Measures; A Case Study of Energy Sector Companies Listed in the Iranian Stock Exchange

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Volume 13, Issue 50 - Serial Number 2SPRING2024November 2024Pages 141-173

Volume 13, Issue 50 - Serial Number 2
SPRING2024
November 2024
Pages 141-173