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We use machine learning for designing a medium frequency trading strategy fora portfolio of 5 year and 10 year US Treasury note futures. We formulate thisas a classification problem where we predict the weekly direction of movementof the portfolio using features extracted from a deep belief network trained ontechnical indicators of the portfolio constituents. The experimentation showsthat the resulting pipeline is effective in making a profitable trade.

Using machine learning for medium frequency derivative portfolio trading