Time series data is processed using self-adapting and self-optimizing algorithms, and is fed into the Neural Network. The network is then trained, and the multi-step ahead predictions are generated.
The algorithm is a complex of a number of different mathematical approaches, which processes the time-series data for any stock/commodity/foreign currency/crypto currency.
You can see the 20 Day-Ahead Prediction for FB on the chart. And we will keep posting the Week-Ahead/10Day/20Day-Ahead predictions for different tickers. Please note that the outliers have been filtered out by the algorithm, therefore the results are indicating the moving direction of the price, which passes through the significant points given on the predicted results.
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Questions: have you back test it? Do you factor in the news and economic numbers? Do you consider the related underling assets, sector, and commodities. For instance, if you want to predict the GDX, you need to factor in the gold price, interest rates, and overall strength of the markets around the world. Or instead of all of these, the algo just looks at the technical indicators and assumes all other elements are priced into the chart? For a test, can you run your algo on the GDX and the Gold separately to see how the results compare?
The algorithm has been tested for couple of months already, for different time intervals of different stocks. A part of the time series data has not been fed into the network, and kept as a test set.
We have compared the error values between the predicted results and the test set. The algorihm was improved accordingly.
Any relative time-series data can be fed into the network, such as other correlated stock/commodity prices and/or sentiment data, and the algorithm adapts itself to the time series relation between these factors to make the prediction.
Please note that, the algorithm is still in improvement phase, and additions/changes are still being implemented into the code.