Value and Size Premiums in the Philippine Equity Market: Evidence from an Extended Dataset with Volatility Analysis
DOI:
https://doi.org/10.65166/nbsg0j88Keywords:
Philippine Stock Exchange, size premium, volatility clustering, GARCH, emerging equity markets , asset pricing anomalies, temporal aggregationAbstract
This study provides an updated and extended empirical assessment of the size premium and return volatility clustering in the Philippine Stock Exchange (PSE), covering the period from July 2018 to June 2025. The analysis extends and updates the foundational work of Perez (2018) — the only prior published study examining size and value anomalies in the PSE using firm-level return data — across a sample period that encompasses the COVID-19 market disruption, the post-pandemic recovery, and the Bangko Sentral ng Pilipinas monetary tightening cycle of 2022 to 2023. Annual tercile portfolios are constructed using price per share as a proxy for firm size, and equal-weighted portfolio returns are computed at weekly and monthly frequencies. The value premium is excluded from the empirical scope due to the unavailability of structured historical fundamental data through publicly accessible sources for PSE-listed firms, a constraint that is acknowledged as a study limitation. Full-sample tests find no statistically significant size premium at either weekly (SML = 0.030%, p = 0.793) or monthly (SML = 0.145%, p = 0.758) frequency. This null result is consistent across all seven individual portfolio years examined and across three structurally distinct sub-periods — pre-COVID, COVID-recovery, and post-COVID tightening — confirming that the absence of a size premium in the Philippine market is a durable structural feature rather than a sample-specific artifact. Volatility clustering tests using the GARCH(1,1) framework reveal strong and uniform evidence of conditional heteroskedasticity at weekly frequency across all three size portfolios, with ARCH Lagrange Multiplier p-values < 0.001 and volatility persistence measures ranging from 0.863 to 0.936, while no clustering is detected at monthly frequency for any portfolio. This frequency-dependent pattern is consistent with the temporal aggregation theory of volatility and directly replicates the Perez (2018) volatility findings over an extended and more turbulent sample horizon. The findings have implications for asset pricing model application, portfolio risk management, and the development of Philippine equity market data infrastructure.
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Copyright (c) 2026 Ramon George O. Atento, PhD, Andrea Gwyneth Atento, Cherry Ann Marie H. Espelita, MBA, Faye Del Mundo, Ryza Gaile Nona, Margareth M. Mangubat, Veronica Grace Dela Costa, Paul Manzana, Amor Espina (Author)
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