Applying self-organizing mapping neural network for discovery market behavior of equity fund

Maximizing the profit and minimizing the loss notwithstanding the trend of the market is always desirable in any investment strategy. The present research develops an investment strategy, which has been verified effective in the real world, by employing self-organizing map neural network for mutual funds tracking the trends of stock market indices according to macroeconomics indicators and weighted indices and rankings of mutual funds. Our experiment shows if utilizing strategy 3 according to our model during a period from January 2002 to December 2008 the total returns could be at 122 percents even though the weighted index fell 22 percents during the same period and averaged investment returns for random transaction strategies stand at minus 25 percents. As such, we conclude that our model does efficiently increase the investment return.