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Strathprints makes available Open Access scholarly outputs by the Department of Accounting & Finance at Strathclyde. Particular research specialisms include financial risk management and investment strategies.

The Department also hosts the Centre for Financial Regulation and Innovation (CeFRI), demonstrating research expertise in fintech and capital markets. It also aims to provide a strategic link between academia, policy-makers, regulators and other financial industry participants.

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Performance evaluation of dynamic trading strategies in UK stock returns incorporating lagged conditioning information

Anderson, G. and Fletcher, Jonathan and Marshall, A.P. (2011) Performance evaluation of dynamic trading strategies in UK stock returns incorporating lagged conditioning information. European Journal of Finance, 17 (1). pp. 67-82.

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Abstract

This paper evaluates the performance of the optimal mean-variance portfolio decision when lagged conditioning information is included in the investment universe. Motivated by the dynamic trading literature we evaluate the performance of eight conditioned information portfolios against an unconditional portfolio and various benchmark strategies. We find with that including lagged conditioning information into the optimal mean-variance portfolio decision can add economic wealth. A number of the conditioning information variables used are significantly effective at improving the portfolio performance in terms of the Sharpe (1966) ratio, Certainty Equivalent Return, and Jensen (1968) performance. We find that the lagged market excess returns instrument has the greatest impact on the portfolio decision.