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Complaints of heightened risks in the sub-Saharan African equities markets are rife in the practitioner literature. Investors need an understanding of the volatility dynamics in these frontier markets. This paper uses the Hidden Markov Models to detect the points of regime changes in the volatility in the markets of Ghana, Kenya, Nigeria and Botswana. The daily closing indices of the exchanges and modeled 2- and 3-regimes in the market were used. Information criteria selected the best fitting model of 2-regime changes corresponding to periods of low and high volatilities. This has been shown through smoothed volatility plots depicting times of regime changes over the sample periods. Investors will be guided in the strategies they choose by setting price filters according to the particular regimes. For regulators, the work will help in setting risk sensitive capital based on market regimes so that firms do not carry too much capital than is required. Keywords: Stylized properties, regime changes, sub-Saharan equities, expectation maximization algorithm, price filters.