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Topic: Bitcoin Trading Software for MtGox - With Neural Networks. - page 2. (Read 23189 times)

full member
Activity: 217
Merit: 100
Registered and paid through Bitpay, hope to receive key soon.

Same here.

I think you should also now have your beta key and 12mth key.
full member
Activity: 217
Merit: 100
Registered and paid through Bitpay, hope to receive key soon.

Just sent you key out.

Bitpay keys I need to cut by hand and I did it as soon as I woke up, before I brushed my teeth!
legendary
Activity: 2478
Merit: 1362
Registered and paid through Bitpay, hope to receive key soon.

Same here.
donator
Activity: 229
Merit: 106
Registered and paid through Bitpay, hope to receive key soon.
full member
Activity: 224
Merit: 100
Thanks for that!

I just read a study on artificial intelligence, where neural networks were taught to include technical analysis as well. Will this be implemented in the feature? It did increase their ROI from 11,X% to over 15% p.a. in Forex trading. That is quite the number there.

That's an interesting idea, thanks for sharing.

The technical indicators are derived solely from the raw OHLCV price data. So if we show the neural network the same raw data then it should model internally any functions that might improve prediction. But I suppose presenting it with chosen indicators might give it a head start and reduce training time. It would need extra input nodes to read these indicators and we would need to feed it quite a few data points from each indicator line, and so iterating and training time would increase. Of course we might only feed it the indicator signals and this might reduce training time? interesting.

I plan to make a dedicated neural net "lab" window giving the user more control over training, what signals are used as input, and the desired output function we wish to train to. In this new lab window I will include options to include data from any indicator on the chart.

Hey, i thought it might be cool to actually share the study instead of just talking about it:

http://www.dabi.temple.edu/~zoran/papers/chenoweth96.pdf
full member
Activity: 217
Merit: 100
Thanks for that!

I just read a study on artificial intelligence, where neural networks were taught to include technical analysis as well. Will this be implemented in the feature? It did increase their ROI from 11,X% to over 15% p.a. in Forex trading. That is quite the number there.

That's an interesting idea, thanks for sharing.

The technical indicators are derived solely from the raw OHLCV price data. So if we show the neural network the same raw data then it should model internally any functions that might improve prediction. But I suppose presenting it with chosen indicators might give it a head start and reduce training time. It would need extra input nodes to read these indicators and we would need to feed it quite a few data points from each indicator line, and so iterating and training time would increase. Of course we might only feed it the indicator signals and this might reduce training time? interesting.

I plan to make a dedicated neural net "lab" window giving the user more control over training, what signals are used as input, and the desired output function we wish to train to. In this new lab window I will include options to include data from any indicator on the chart.
full member
Activity: 224
Merit: 100
Hi, quick question for understanding: I buy the 12 months now, i get the 6 month beta PLUS 12 months membership?

And: Do you have a good explanation somewhere that gets me an understanding of the mathematics behind NN trading?

Yes, When you buy the 12 month subscription you get a 12 month key for use on the final polished release. You also receive free monthly beta keys for as long as Cortex7 is in beta phase, this is expected to last ~6 months, possibly more.

The artificial neural network (ANN) tries to predict if the chart is about to go up or down.

The ANN is first trained by showing it alot of history data and also telling it what points in that history would have been good buy/sell points.

After training the ANN is able to predict when to buy and sell with better accuracy than random walk.

Of course one must realise that this is not a dead cert indicator, but it is much better than random and can give further confidence to technical charting that you may do.

The ANNs in cortex7 are multilayer perceptrons with backpropogation training:

http://en.wikipedia.org/wiki/Artificial_neural_network

Thanks for that!

I just read a study on artificial intelligence, where neural networks were taught to include technical analysis as well. Will this be implemented in the feature? It did increase their ROI from 11,X% to over 15% p.a. in Forex trading. That is quite the number there.
full member
Activity: 217
Merit: 100
Hi, quick question for understanding: I buy the 12 months now, i get the 6 month beta PLUS 12 months membership?

And: Do you have a good explanation somewhere that gets me an understanding of the mathematics behind NN trading?

Yes, When you buy the 12 month subscription you get a 12 month key for use on the final polished release. You also receive free monthly beta keys for as long as Cortex7 is in beta phase, this is expected to last ~6 months, possibly more.

The artificial neural network (ANN) tries to predict if the chart is about to go up or down.

The ANN is first trained by showing it alot of history data and also telling it what points in that history would have been good buy/sell points.

After training the ANN is able to predict when to buy and sell with better accuracy than random walk.

Of course one must realise that this is not a dead cert indicator, but it is much better than random and can give further confidence to technical charting that you may do.

The ANNs in cortex7 are multilayer perceptrons with backpropogation training:

http://en.wikipedia.org/wiki/Artificial_neural_network
legendary
Activity: 2478
Merit: 1362
Can't wait !
full member
Activity: 224
Merit: 100
It seems to me, that the system needs an abstraction layer between the trading logic and the exchange interface?

Indeed. In the finished version the neural net signals will be just one trade signal that the user can use as visual reference or can mix with other generated signals for use in autotrading. This way the neural net signal can be used as a confidence bias instead of an absolute signal.

Other trade signals will be generated by a simple scripting interface giving access to all of the charted information, including: all technical overlays and underlays, user drawn trendlines, open/high/low/close/vol, exchange-lag.

The scripting will initially just be able to spot crossings between any pair of signals mentioned and set boolean flags. These flags can be logically mixed with AND,OR.

This is a few months down the road. First off is to actually get the trading interface coded and tested.

Eventually I would like to open it up further and give user simple script API to access entire array history of signals mentioned and perform their own math etc.



Hi, quick question for understanding: I buy the 12 months now, i get the 6 month beta PLUS 12 months membership?

And: Do you have a good explanation somewhere that gets me an understanding of the mathematics behind NN trading?
full member
Activity: 217
Merit: 100
It seems to me, that the system needs an abstraction layer between the trading logic and the exchange interface?

Indeed. In the finished version the neural net signals will be just one trade signal that the user can use as visual reference or can mix with other generated signals for use in autotrading. This way the neural net signal can be used as a confidence bias instead of an absolute signal.

Other trade signals will be generated by a simple scripting interface giving access to all of the charted information, including: all technical overlays and underlays, user drawn trendlines, open/high/low/close/vol, exchange-lag.

The scripting will initially just be able to spot crossings between any pair of signals mentioned and set boolean flags. These flags can be logically mixed with AND,OR.

This is a few months down the road. First off is to actually get the trading interface coded and tested.

Eventually I would like to open it up further and give user simple script API to access entire array history of signals mentioned and perform their own math etc.

legendary
Activity: 965
Merit: 1000
It seems to me, that the system needs an abstraction layer between the trading logic and the exchange interface?
full member
Activity: 217
Merit: 100
Any BTCE trading bot? TKS

I'm still working on the trade engine for MtGox. I have coded with adding exchanges in mind, so I will be adding further exchanges, BTCE is on the list, It might not be added until autumn though.

I was going to add bitcoin24 next. My wife even got an account there and she bought a few bitcoins and had them in there for a while, and then.... "pooof.. aaaand it's gone!"
full member
Activity: 217
Merit: 100
I registered. How long to receive my key via email?

You should have it by now, my apologies for the slight delay.
hero member
Activity: 840
Merit: 1000
Any BTCE trading bot? TKS
legendary
Activity: 1498
Merit: 1000
I registered. How long to receive my key via email?
legendary
Activity: 1498
Merit: 1000
Here's a network after being trained to predict for BTCEUR:



and here's it generating green/red buy/sell signals:



Good reply thanks.  you may have sold me. I really like the platform - no errors or glitches to deal with!!  Think or swim offers a similar system for predicting the market. It's very usable but I'm more interested in currency trading (BTC)
legendary
Activity: 2955
Merit: 1049
Looks very epic, if only it was for Linux :-(
+1  Wink
full member
Activity: 217
Merit: 100
Here's a network after being trained to predict for BTCEUR:



and here's it generating green/red buy/sell signals:

full member
Activity: 217
Merit: 100
Can anyone explain precisely how these neural networks work here? What indicators are they working from? What is their predictive process?

The artificial neiral networks (ANNs) are fandown multilayer backpropogation type.

They ANNs inputs are fed windowed historic prices into the input layer and are trained (using backpropogation) to reproduce a buy/sell signal, this is the training signal.

The windowed input randomly hops around all history data until all datums have occupied neuron[0] position, this is one epoch of training. It takes many epochs to train well.

During training it helps to shake all neuronal weights periodically to prevent the ANN landing in a non optimal solution well.

The training signal is derived by choosing good tops/bottoms of the historic price chart. It is the signal that leads to good trades being made when we view the chart with perfect hindsight.

When training the ANN is not allowed to see X latest datums, this way we can check its predictive performance.

Then the ANN produces an output signal that (when trained correctly) approximates this buy/sell function and green/red buy/sell flags are superimposed upon the chart realtime.
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