I am trying to implement based on current stock close price to predict new stock price.
Based on my understanding, the current model prediction can be done based on volatility from Gaussian Random Walk and obtain the future return[‘change’].
My question is, how can we use current stock price as input to predict the return since we can observe or know the previous return and predict the future.
Unless we are doing in sample prediction, we can trace back the volatility based on index of train test split.
My purpose is similar to out of sample prediction, but in strictly not really out of sample, because I try to use previous return as input instead of volatility to make prediction.
I also have an interest in this notebook and was wondering why the prediction for new stock prices is not included in the example. Somehow this is missing.
Actually the prediction could be done if we are doing in sample prediction, by split the data into train and test. Since we know the index, we can trace back the current volatility and predict future returns.
But what I am interest is using current stock price as input instead of volatility since volatility is calculated rather than observed from the data available.
