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Application of adaptive RPCL-CLP with trading system to foreign exchange investment

In this paper, an adaptive rival penalized competitive learning and combined linear prediction (RPCL-CLP) model is applied to the forecast of stock price and exchange rate. As shown by the experimental results, this approach not only is better than Elman net and MA (q) models in the criterion of root mean square error, but also can bring in more returns in the trade between US dollar (USD) and German Deutschmark (DEM) with the association of a trading system. Moreover, whatever trading strategies with different risks are used in the trading system, adaptive RPCL-CLP can always keep the profits increasing as time goes through.