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Modern techniques like artificial neural networks (ANN) are best used for high frequency trading for several reasons. First, they mimic human intelligence but they mostly don’t reach a human’s level of intelligence, therefore, there is no point in using those techniques on a time scale at which a human could easily be working. Their advantage comes from speed of operation and constant activity. Second, we need a lot of data to train neural networks efficiently and this amount of data will only be found in high frequency trading. Forex has all in all quite few instruments with limited relevant past data on the daily or weekly time-scale. Furthermore, High frequency trading is a type of scalping strategy where we identify noise around the true value of the instrument. This is different from long-term trading that attempts to follow meaningful movements of the instrument according to fundamental analysis.Artificial Neural networks A good time-scale to work on is the minute time-scale. This time-scale is full of noise which will be captured by the algorithm in order to sell at a local high and buy at a local low. This can be proven using a simple neural network trained to predict the f…
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Efegen avatar
Efegen 16 Apr.

Just a thought. If this system works why don't you use it in larger timeframes. So the costs will be more minimal and deviation will be less?

Victor avatar
Victor 18 Apr.

good one.. nicely written

SpecialFX avatar
SpecialFX 30 Apr.

Another very intriguing and interesting article! :) Regarding your comment about Holy Grail, no need to look for it, because it doesn't exist... well, it does, but that will be for another time... ;)

nippur72 avatar
nippur72 21 Nov.

The reason why you are able to predict "high to high" and not "close to close" IMHO is very simple: when you predict "high to high" you are not forecasting the future, but you are forecasting (partially) the past, since the High(-10 to 0) is a point back in time. It's a common pitfall that I've also experienced myself when experimenting with neural networks. As a rule of thumb, when you see hit rates easily going above 65% there is chance you are doing something wrong, e.g. forecasting the preset or the past.

olga avatar
olga 24 Nov.

You are totally right and strangely enough I had realized this before and I made the mistake again. I also found similar pitfalls when training and testing instances aren't totally separated including the period you gather information on and the period you try to predict when you use cross-validation. It’s very easy to get excited about good results and in this article, it totally happened to me. In conclusion, kudos for pointing out the flaw that destroys any interest lying in this article and I believe more and more that high-frequency trading has no solution.

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21/40
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Introduction Artificial neural networks are a special family of artificial intelligence models and in this article I will explain how they work to predict the forex in a way that anyone can understand but also in a way that people familiar with artificial neural networks may see quite precisely what is being done. When switching from a tick chart to an hour candlestick chart, a huge amount of information has been lost. We would like our automated strategies not to be limited to looking at one or two timeframes at once. We want it to be aware of every movement on every time-scale, identify the important ones, and act accordingly. Today I’ll explain how to identify a single chart feature with the help of a special artificial neural network (ANN). Compressing data/ extracting features This technique requires optimization and I’ll never state this enough; you cannot test your strategy on the same period it’s optimized, that’s just cheating and the strategy will most probably not work on other data!! All the training/optimization/validation here is done using data from January 2009 to June 2011 while the rest of the data up to the present is used for testing and every result reported …
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olga avatar
olga 7 Mar.

Allright yes, I'll explain better how ANNs work in the next article. they are a wonderful family of algorithms that can model any system with sufficient examples don't complain if it bores you to tears though

LSD avatar
LSD 9 Mar.

Good stuff. +1

citikot avatar
citikot 12 Mar.

I sniff the smell of HFT here :)

olga avatar
olga 12 Mar.

You're right, but I'm not sure I can be profitable with high frequency trading because of commissions and spread, I want to achieve low frequency trading but also take into account low time-frame data to optimize entry and exit points. in part two I explain how I intend to do that but I haven't implemented the entire method yet.

drishti avatar
drishti 12 Mar.

@ olga : You are writing in right direction. Using ANN for trading is a very good approach, however there might be only few who can understand the whole part, how it works and how to build it.

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