believe that the validity of the model has not been
affected.
The academics believe that there are several main
reasons for the reduced validity of the model, firstly
because the factors used in the model are based on
normal market conditions and economic situations, so
these factors are unable to capture the state of the
market in a situation as volatile as an epidemic.
According to Kostin et al., who studied the
performance of selected companies in the energy
sector as well as in emerging sectors during the
COVID-19 pandemic through the FF3 and the FF5,
the traditionally efficient as well as self-regulating
market was severely disrupted so that the
performance of the market was less dependent on
conventional financial indicators and more
influenced by short-term factors influence, and the
traditional five factors do not capture such unusual
market movements (Kostin et al., 2022). Secondly,
scholars have also argued that the effectiveness of the
model is reduced in emerging markets that are prone
to anomalies and in markets that have been severely
hit by the crisis. According to the study, the FF5 has
a significantly lower R² value during the crisis, which
measures the model's capacity to clarify the
anomalies in the data, which represents the near-zero
ability of the five-factors to explain stock returns in
emerging and energy sectors (sectors severely
affected by the pandemic), which are different from
the normal market (Kostin et al., 2022). Third,
regional differentiation in an epidemic can also lead
to a reduction in the validity of the FF5. According to
the research, countries like China and Russia, which
have adopted both free markets orientated and
economically planned policies, deviate from the
efficient market assumption on which the multifactor
model is based, and the inadequacy of the model is
evident during the pandemic as it is unable to adapt to
the external macroeconomic disruptions and
governmental policies affecting these markets
(Kostin et al., 2022). Finally, scholars argue that the
complexity of the model also reduces its validity. In
previous studies (Kostin et al., 2022; Zhou, 2024),
they all argue that the FF5 is less effective than FF3
in the context of pandemics and that a multi-factor
model would be more firm-focused and therefore of
limited applicability. The RMW and CMA factors in
the FF5 do not enhance the model’s explanatory
power. For example, the FF5 is unable to explain the
market returns of the Chinese pharmaceutical
industry during an epidemic (Zhou, 2024) because its
rigid assumptions rely on traditional risk, which
would limit the model's ability to capture market
changes under high uncertainty.
Conversely, several academics contend that the
reliability of the five-factor model remains robust in
an epidemic scenario. Alqadhib et al., who
incorporated the five-factor model in their research to
measure the risk-managed performance of active
mutual funds in Tehran, put forth compelling
evidence that attests to the model's durability during
the pandemic (Alqadhib et al., 2022). It was found to
elucidate approximately 75% of the fluctuations in
the returns of equity mutual funds. Regardless of the
prevailing pandemic, enterprises with sizable profits
and those pursuing conservative investment strategies
were present. For such enterprises, the five-factor
model capably accounted for the deviation, yielding
an accurate depiction of returns investors garnered
after risk adjustments. Substantially positive returns
were accomplished in the study by adjusting for the
recognized risks.
The study of other scholars also studies exhibit
mixed results. According to Zhang et al. on the excess
returns of real estate investment trusts (REITs), there
conclusion indicates two of the factors in FF5, RM-
Rf and SMB, show a relatively stable impact in
explaining the returns and the model also
demonstrates a certain level of validity after adding
the momentum factor which explains the returns
during the pandemic (Zhang et al., 2023). However,
the applicability and validity of the model is limited
by the fact that the skewness and kurtosis factors are
not consistent across regions.
The research aims to investigate the effectiveness
of the FF5 in the gaming industry before and during
the pandemic. The pandemic provided this study with
a market context of economic disruption and high
volatility, which helped to test the robustness of the
model. Although the FF5 has been widely validated
in stable markets, it lacks performance in the gaming
industry during a crisis. By exploring the gaming
industry, this study aims to gain insights into how the
five-factor model works when an unprecedented
market crisis erupts and to assess the model's
robustness. In the following, this will be done through
an explanation of the methodology used in this study,
presentation of the empirical results, analysis of the
empirical results, conclusions, limitations of the
model and outlook.
2 DATA AND METHOD
The data selected in this article are from daily data of
the game industry in the United States. In this case,
we have intercepted two time periods, the first
starting from 2 January 2019 to 31 December, and the