▪  ABOUT US

▪  NIF is a team of experienced experts for Neural Networks and Capital Markets.

Our main business is providing 24h-forecasts for Currencies and for Gold by developing, training and testing hundreds of different databases and neural networks per month.

Technical and fundamental data sets are combined to generate highly profitable forecasts for our clients.

▪ NIF sends out Neural Network Forecasts to its clients via E-MAIL or SMS on a daily basis.

Emails include clear UP/DOWN signals and results of the previous day. Clients enter their contracts upon receipt of our forecasts, stay in the market for 24h and place new trades upon receipt of new forecasts.

There is no need to monitor FX-quotes or place new trades during the 24h-period. All results published on this website were achieved under real market conditions.

▪  NIF TRADING STRATEGY

▪  NIF recommends to trade according to the following strategy:  Stop Loss limit of USD 1000.- per contract / no exit level (AUXUSD: USD 1500.-) We started with these values in nov. 08. All results prior were achieved with stop loss of USD 800.- for EURUSD and USD 1000.- for XAUUSD. That's the strategy our results published herein are based upon.

▪ Trailing Stop: Trailing stop is an advanced order type that automatically adjust itself as the market rate moves in the direction of the open position. The trailing stop feature allows Forex/Gold traders to specify a limit on the maximum possible loss and secure profits without setting stops on the order again. So you can secure profit without monitoring the market. In case you decide to use a trailing stop our advice is to set it at 50 pips (XAUUSD: 7 points) with the initial stop loss at 100 pips. (XAUUSD: 15 points)

▪ For QUESTIONS please contact: trading@neuralinvestmentforecast.com

▪ NIF NEURAL FORECASTS AND SIGNALS

▪ excellent Performance Record

▪ 1 month Free Trial

▪ no need to monitor the market

▪ daily email and/or sms delivery

▪  NEURAL NETWORKS have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics. Indeed, anywhere that there are problems of prediction, classification or control, neural networks are being introduced. This sweeping success can be attributed to the following few key factors:

▪ Power: Neural networks are very sophisticated modeling techniques capable of modeling extremely complex functions. In particular, neural networks are nonlinear. For many years linear modeling has been the commonly used technique in most modeling domains since linear models have well-known optimization strategies. Where the linear approximation was not valid (which was frequently the case) the models suffered accordingly. Neural networks also keep in check the curse of dimensionality problem that bedevils attempts to model nonlinear functions with large numbers of variables.

▪ Method of Use: Neural networks learn by example. The neural network user gathers representative data, and then invokes training algorithms to automatically learn the structure of the data. Users need to have knowledge of how to select and prepare data, how to select an appropriate neural network, and how to interpret the results.