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Most measures are self-explanatory and are commonly used in the fund management industry. Some of the more important measures include the Sharpe ratio, maximum drawdown and average gain/loss ratio. The Sharpe ratio is a 18 The MAE and RMSE statistics are scale-dependent measures but allow a comparison between the actual and forecast values, the lower the values the better the forecasting accuracy. 19 When it is more important to evaluate the forecast errors independently of the scale of the variables, the MAPE and Theil-U are used.
Pesaran (1997), “Lessons in Logit and Probit Estimation”, in Interactive Econometric Analysis Working with Microﬁt 4, Oxford University Press, Oxford, pp. 263–275. Pindyck, R. S. and D. L. Rubinfeld (1998), Econometric Models and Economic Forecasts, 4th edition, McGraw-Hill, New York. fr/previa). Refenes, A. N. and A. Zaidi (1993), “Managing Exchange Rate Prediction Strategies with Neural Networks”, in P. J. G. Lisboa and M. J. Taylor (eds), Techniques and Applications of Neural Networks, Ellis Horwood, Hemel Hempstead, pp.
019754 Mean dependent var. D. dependent var. Akaike info. 6760εt−10 The restricted ARMA(10,10) model was retained for out-of-sample estimation. The performance of the strategy is evaluated in terms of traditional forecasting accuracy and in terms of trading performance. Several other models were produced and their performance evaluated, for example an alternative restricted ARMA(10,10) model was produced (equation arma16710). The decision to retain the original restricted ARMA(10,10) model is because it has signiﬁcantly better in-sample trading results than the alternative ARMA(10,10) model.