Galen88 wrote:Hi Gamma and friends,

Many thanks to Gamma for introducing this system and sharing the information he has on this as I too am very interested.

I found out about Louis Mendelsohn's system recently and his commercial system claimed 86% accuracy. Another independent report gave a mean accuracy of 78%. They have 2 documents giving some details.

The first gives a glimpse into how their system works:
VantagePoint software uses five neural networks, in a two-level hierarchy, to forecast five different indicators for that market.
1. The first forecasts the next-day high to help set stops for entry and exit points.
2. The second forecasts the next-day low to help set stops for entry and exit points.
3. The third forecasts a five-day moving average of closes two days into the future to indicate the expected short-term trend direction within the next two days.
4. The fourth forecasts a ten-day moving average of closes four days into the future to indicate the expected medium-term trend direction within the next four days.
5. The fifth indicates whether a market is expected to change trend direction, making a top or a bottom, within the next two days.

The second document is an accuracy assessment conducted by Dr Warnock on 26 randomly selected instruments over a 2 year period (including some forex pairs such as USDCAD.) His report showed a mean combined accuracy of 78%, forecast for longs were slightly better.

For example, accuracy for longs for USDCAD was 83.3% versus shorts at 80.6%

As there is a 256kb limit to uploads, I could not upload them here (each pdf is more than 1 mb in size). If anyone is interested, pm your email and I will pass them to you that way.

Finally, I encourage everyone to take the free machine learning course from Stanford University as mentioned earlier @ http://www.ml-class.org Professor Andrew Ng does a great job of simplifying the learning algorithms as much as possible and even providing visual examples or what he calls intuitions which help us to see how these "regression" algorithms work.

I look forward to participating actively in this thread.

• 1. The first forecasts the next-day high to help set stops for entry and exit points.
  2. The second forecasts the next-day low to help set stops for entry and exit points.
  3. The third forecasts a five-day moving average of closes two days into the future to indicate the expected short-term trend direction within the next two days.
  4. The fourth forecasts a ten-day moving average of closes four days into the future to indicate the expected medium-term trend direction within the next four days.
  5. The fifth indicates whether a market is expected to change trend direction, making a top or a bottom, within the next two days.

The first four neural networks at the primary level of the hierarchy make independent market
forecasts of the high, low, short- and medium-term trend. These predictions are then input into
the fifth network, along with other intermarket data input at the secondary level of the network hierarchy, to predict market turning points.

This system doesn't sound too tricky to implement using FANN2MQL4 so i'll have a look into this and will post an update probably towards the weekend. I'll pm you my email so i can have a read. I have tried something a lot more simpler than this and it didn't work too well. I think we would need to look at developing a self optimising system that retrains each day (user specifiable) to refresh the NNs using the new data. Do you think it would work for intraday say using the same ideas on a smaller timeframe?

magft wrote:I'v had a read through the VantagePoint PDF and the Networks are as follows:

• 1. The first forecasts the next-day high to help set stops for entry and exit points.
  2. The second forecasts the next-day low to help set stops for entry and exit points.
  3. The third forecasts a five-day moving average of closes two days into the future to indicate the expected short-term trend direction within the next two days.
  4. The fourth forecasts a ten-day moving average of closes four days into the future to indicate the expected medium-term trend direction within the next four days.
  5. The fifth indicates whether a market is expected to change trend direction, making a top or a bottom, within the next two days.

The first four neural networks at the primary level of the hierarchy make independent market
forecasts of the high, low, short- and medium-term trend. These predictions are then input into
the fifth network, along with other intermarket data input at the secondary level of the network hierarchy, to predict market turning points.