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Cuchulainn
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Joined: July 16th, 2004, 7:38 am
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Re: We've developed (free) software to predict volatility + other vital tools...

December 5th, 2018, 5:17 pm

I am using 3 methods to test if the data is random or not, as you can guess most sets of stock prices appear as most likely random according to all of the tests! 

When they aren't I am using the NN, Genetic algo and Levenberg-Marqrant to see what can be predicted and what not or better yet just put them through the volatility test tool to see how much % is the real change on month-to-month basis so that I have an idea if I can buy cheap put/call OTM. 

I am interested in the rationale and the (inner workings) for choosing these three methods. They are a bit of a motley crew. They use a mix of heuristics and have very different properties.

Output from them feels like a description rather an explanation.

1. What is NN in this case? the usual GD, SGD,stuff with BPN and learning rates? 
2. What's the advantage of GA compared to say Differential Evolution which IMO is more versatile? I thought GA was a bit passe, but maybe it's on its way back.
3. LevMar is a Opel Kadette .. it works on most days but it is not very robust.

1 and 2 only produce local minima at best. Can't remember if this is also true of GA..

Do you have reports on how these methods compare to each other based on a range of data.
 
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alpher
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Joined: September 1st, 2012, 4:20 pm

Re: We've developed (free) software to predict volatility + other vital tools...

December 5th, 2018, 7:56 pm

@Cuchulain: i'll get back to you asap or you can PM me if you really like to know :) but long story short:

1. Multy-layer NN, I think the classic: multi layer perceptron
2. Can't say there's a huge advantage other than GA's ability to "learn" quickly from known data (supervised) but it's not CPU friendly (my implmentation at least!) and its predictive power isn't that good compared to LevMar
3. it is yes, it seems better than NN for some cases though. 

I'll show more reports and screenshots soon as promised. 
 
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Cuchulainn
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Joined: July 16th, 2004, 7:38 am
Location: Amsterdam
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Re: We've developed (free) software to predict volatility + other vital tools...

December 6th, 2018, 12:42 pm

GAs are inherently parallel so I would expect parallel design patterns (master-slave etc.) to be useful. These days desktops with lots of processsors are common so this should improve speedup?

For pure optimisation one trick is to use GA/DE to get the initial guess close to the exact solution (first few iterations) and then let LevMar do its job.

I think tackling this problem from three different approaches can't be a bad idea.
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