I have converted the stock price indices time series data into stationary by differencing once so, $d=1$. I also have removed the seasonal component of the data. I want to develop a model for forecasting future values of SPX. These are PACF and ACF plots obtained. I am not able to determine the values of $p,q$.

I have read a little about minimum AIC values as well however, we need a rough estimate of the $p,d,q$ to make guesses towards the correct model in that as well.

I have converted stock price index time series data into stationary series by differencing once, so $d=1$. I also have removed the seasonal component of the data. I want to develop a model for forecasting future values of SPX. These are PACF and ACF plots obtained. I am not able to determine the values of $p,q$ for ARIMA modeling.

I have read a little about minimum AIC values as well; however, we need a rough estimate of $p,d,q$ to make guesses towards the correct model in that as well.

I have converted the stock price indices time series data into stationary by differencing once so, d=1. I also have removed the seasonal component of the data. I want to develop a model for forecasting future values of SPX. These are pacf and ACF plots obtained. I am not able to determine [![][2]][2]the values of p,q. I have read a little about minimum AIC values as well however, we need a rough estimate of the p,d,q to make guesses towards the correct model in that as well.

I have converted the stock price indices time series data into stationary by differencing once so, $d=1$. I also have removed the seasonal component of the data. I want to develop a model for forecasting future values of SPX. These are PACF and ACF plots obtained. I am not able to determine the values of $p,q$. 

I have read a little about minimum AIC values as well however, we need a rough estimate of the $p,d,q$ to make guesses towards the correct model in that as well.