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On 20.06.2022 we have 1 million dollars for 10 days, so until 30.06.2022, and we want to increase the capital through shares.

(The data of the shares can be found on finance.yahoo.com)

So we want to check which stock has the biggest increase in this period.

So we have to use the final price of each stock and predict what it will do in the said period. So we need to train a neural network with suitable input data.

Do we have to do the following steps ?

1) We are looking for data of the last 5 years on the page.

2) We use moving averages. So to give a value to a day we look a few days before and add all the days and calculate the average. For example, we go 200 days before.

But what kind of moving average do we use? The exponentially smoothed average?

3) We form the input data so that the neural network finds the answer.

4) Of data motives, we look for the 80% for the training and the 20% for the confirmation.

5) So we take all the data of the stocks until 15.06.2022 and train the network. Then we use the weights and start with the forecast for each share from 16.06.2022 to 30.06.2022.

6) We find which stock has the biggest increase.

Is this the right approach?

Could you explain to me in more detail what all this looks like in practice? For example, in step 3, how do we form the input data so that the network can give us an answer? :unsure: