JimmyJam mentioned: 1. http://www.tradingpro.com/ they actually forecast S&P500, intraday predictions, as they claim at the beginning of the day they forecast when to enter and exit the market for that day
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Stock Index Forecasting using Recurrent Neural Networks S.-I. Wu and H. Zheng (USA) Keywords: Recurrent Neural Network, Financial Forecasting and Prediction, ARIMA, Time Series, Stock Market Abstract: We have developed two different architectures of recurrent neural networks (RNN) to forecast the daily closing prices of stock indexes (S&P500, Dow Jones, and NASDAQ) five days ahead. Experiments showed that the price is predictable and much better than the random guess. According to a simple short-term investment strategy, a good annual profit rate can be obtained. Different activation functions were tested in order to dynamically choose the best neural network topology. We explored more than 600 network structures for each neural network. The same data sets were analyzed by the ARIMA model using commercial statistics package MINITAB. The RNNs outperform a better result than the ARIMA model in terms of profit rates. The autoregressive parameter helped us determine the recurrent neural network structure -- http://www.actapress.com/PaperInfo.aspx?PaperID=15048
SmartQuant Ltd info@smartquant.com Download QuantDeveloper Demo (20Mb). Neural networks Portfolio selection General optimization Portfolio optimization Heuristic optimization CAPM (Capital Asset Pricing Model) Neural optimization VaR (Value at Risk) Genetic algorithms Prospect Theory Simulated annealing Technical analysis Taboo search Data patterns Game theory Bond pricing Multi-agent simulations Option pricing Monte Carlo simulations Volatility estimations Time series analysis SWAP pricing Fuzzy logic Arbitrage trading Fractals and chaos Term structure Neural networks [1] Feedforward and Recurrent Neural Networks and Genetic Programs for Stock Market and Time Series Forecasting, P.C.McCluskey, 1993 [2] Clustering of the Self-Organizing Map , Juha Vesanto , 2000 [3] The Learning Vector Quantization Program Package, T.Kohonen, 1996 [4] A Neural Network Model for Gold Market, P.J.McCann, B.L.Kalman,1993 [5] Prediction Risk and Architecture Selection for Neural Networks ..... -- http://www.smartquant.com/references.php
It is much the same old story as the Great Californian goldrush. The people that made the money were the sellers of booze, picks and shovels etc. not the 49'ers generally. Their success rate was probably about the same as trading, with a few notable exceptions , which publicised the goldfields nicely. Over 90% failure rate in both areas of activity and populated by very similiar people. Sorry to poor cold water on what is a fascinating subject but........ Do you reaaly believe the scamsters and snake-oil vendors can predict the future ? No way. They just see a load of suckers ( like me too ) they can con with ease.
Dont worry folks I will be back in the markets come Monday. Call it human optimism if you wish see ya suckers !!!!!!!!!!!!!!!!!!!!!!!!!!!