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Data · dataset · 2026

Abnormal Return Synchronicity R2 (ARS-R2)

Listed in Teesside University Research Data Repository

This dataset provides the Abnormal Return Synchronicity R2 (ARS-R2) measure for 41 global equity markets over the period from January 1994 to June 2021.

Description

ARS-R2 measures the proportion of systematic variation in risk-adjusted returns that is captured by latent factors after controlling for established risk factors, so it reflects the residual return comovement that lies beyond standard asset pricing models. A higher ARS-R2 indicates that a larger share of abnormal return variation is organized by common latent factors, a pattern associated with potential market inefficiency arising from market frictions and correlated behavioral biases.

The measure is constructed by applying instrumented principal component analysis (IPCA) to Fama and French (2015) five-factor risk-adjusted returns, using 11 standard mispricing anomalies as instruments: net stock issues, composite equity issues, accruals, net operating assets, asset growth, investment to assets, distress, O-score, momentum, gross profitability, and return on assets. The file contains a single sheet. The first column, Date, gives the month in YYYYMM format, and each remaining column gives the monthly ARS-R2 for one market, identified by its country code.

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Values are expressed as fractions, so 0.0157 corresponds to 1.57 percent. Cells are left blank for months before a market enters the sample. This dataset accompanies the paper "Systematic Abnormal Return Variation and Global Market Inefficiencies" by Vitor Azevedo, Minghui Chen, Christoph Kaserer, and Sebastian Müller.

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