Abstract:
Equity anomalies in frontier markets appear and disappear over
time. This article aims to demonstrate the predictability of which
of these transient anomalies will be profitable using a Markov
switching model. To do so, we examine 140 equity anomalies
identified in the literature using a unique sample of over 3,600
stocks from 23 frontier equity markets between 1997 and 2016.
The application of a Markov switching model reveals that the
time-series pattern of expected returns is dependent upon the
type of anomaly; some anomalies become unprofitable over time
whereas profitability increases in tandem with the development
of a specific stock market for other types of anomalies. Results
further indicate that forecasts of the next month’s return obtained
from this model can translate into profitable investment strategies.
We find that an anomaly selection strategy that relies on
the model produces abnormal returns and outperforms a naïve
benchmark that considers all the anomalies. We go onto demonstrate
that our results are robust.
