Pairs trading investment strategies are based on relative mispricing between pairs of historically correlated stocks and have been widely implemented in Hedge funds by taking long-short position in selected stocks when price divergences appear and taking profit after convergence. A mean reversion model is described to analyze the dinamics of the price spread between preffered and ordinary shares of a single company in the same market. Initial long run convergence mean and results are obtained from filtering data with a moving average, subsequently, parameters of the mean reverting model are estimated through a Kalman filter on a state space formulation using historical data. An algoritmic pairs trading strategy upon the suggested model is then backtesting indicating potential wealth in financial markets observed to be out of equilibrium. Applications of empirical results may reveal opportunities to excel portfolio results, correct mispricing and overcome low return periods.
