The second failure, stock price prediction attempt 2.

I, as I wrote in the last article, attempted to predict the stock market again by 1. increasing the amount of data and 2. increasing the classes by two by adding “drastically-up” and “drastically-down” to “up” and “down”.

If the price moves more than 4.8% within two months, my system will consider it a “drastic change”.

I trained the system, and I got an accuracy: of 0.36236390471458435 *100 %.

Since there are four categories, you will likely get an accuracy of around 25% if you guess randomly. Therefore, this result indicates that my model is at least more valuable than a randomized decision.

The questions here are, what does 36% mathematically mean? Is this a significant difference? It should be examined so that I can know whether or not this model is helpful in some way.