Help with Time Series prediction

I'm a complete n00b to both this stackexchange and ML so please don't flame me too bad.

I am trying to make a prediction from Time Series data. I have about 10 years worth of 1-minute resolution price data for the SP500. What I'd like to do is treat each DAY in the data as it's own series to predict what the price movement will be for the last 15 minutes of market hours.

I've looked through several books, some tutorials and a lot of articles. I've been trying to leverage an LSTM RNN model for these predictions. The problem, I think, is that all the examples I've been following (whether univariate or multivariate) treat the time series data as a single time series. What I would like to do is treat each day as a time series and try to predict today's final movements based on the past 10 years or daily stock price.

Am I hopelessly far off here? Is this not even the right problem to try to solve with ML?

Anything that could point me in the right direction would be incredibly appreciated! TIA