why use companies' stock price to predict NASDAQ-100 Index?

[gao27024037]

your code in main.py line189, the code of getting data is below, why do you use companies' stock price to predict NASDAQ-100 Index?

raw_data = pd.read_csv(os.path.join("data", "nasdaq100_padding.csv"), nrows=100 if debug else None)
logger.info(f"Shape of data: {raw_data.shape}.\nMissing in data: {raw_data.isnull().sum().sum()}.")
targ_cols = ("NDX",)
data, scaler = preprocess_data(raw_data, targ_cols)

NDX should be calculated by these stock prices, isn’t it? why u have to learn the calculation formula by RNN?
The DA-RNN paper gives a time series predicting model, right? But where is your time series predicting? I am confusion.

That's what I found when I read the code repeatedly, If I got wrong or missed something, please tell me.
Thank you.