I've dived into the field of neural networks and I became enthralled with them.
I have finally developed an application framework for testing trade systems in stock exchanges and now I'm going to implement my first neural network in it. Very simple and primitive one, not intended for real trading, just for starters.
I only want to know if my approach is good approach.
And if you see I'm missing something (or I'm wrong about something) or you have an idea of what could help a begginer in a field of neural networks in market trading, that would just make me super-happy :)
I have 40 inputs, market values from the stock exchange (S&P e-mini but that's not important).
For these 40 inputs, I know 2 numbers.
- How much money would I earn or lose with a buy order
- How much money would I earn or lose with a sell order
Because of how stock exchanges work, both numbers can actually be negative/positive indicating that I can lose/earn money for either buy and sell (this is because a trade can have attached "loss limitting" or "targetting" orders like STOP, LIMIT etc. which behave differently).
But if that happens, it is an indication that I should not place an order at all, even if both buy&sell orders give positive numbers.
I imagine that the best activation function to use is the ...sigmoid thing but with a range from -1 to 1 (I've found it's called many names on the internet...bipolar sigmoid, tanh, tangent something...I'm no profound mathematician).
With a back propagation learning I teach the network that for the 40 inputs, there is 1 output and this output is one of these numbers.
- -1 which means sell order is going to earn money, buy is going to lose money
- +1 which means buy order is going to earn money, sell is going to lose money
- 0 which means buy and sell are both going to sell/lose money, best avoid trading
I'm imagining that after learning, the network output will be always some number close to -1, 1 or 0 and it's just up to me where I set the threshold for buying or selling.
Is this a right way to use a neural network?
Everywhere on the internet, the output for learning people are giving the back propagation learning machine are the future values of the market chart and not the expected money yield of a different trade entries (buy or sell). I consider that a bad approach because I'm not interested in the future chart values but in the money I want to earn.
Edit: I intend to build a neural network for automated trading, not for decision helping.