سیاستگذاریهای اقتصادی و مالی در حوزههای فوقالذکر در سطوح ملی، منطقهای و جهانی
parisa Mohajeri; Reza Taleblou
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 ...
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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.
