Can someone give me some insight for this?
I have a functional magnetic resonance imaging research background in which I analyzed a lot of time series data, and I would like to analyze the time series of stock prices (or returns): 1) In a particular market area, Model series of successful historical stock of this successful stock with modeling successful stock and then with other new shares to see important relationships; 2) To predict its future values, use stock price time series model and prediction (for example, exponential smoothing). I want to use non-linear modeling methods (ARIMA and ARCH) to do this.
Many questions: How often are the ARMIs and ARCH modeling methods (given that the person who applies them to that is right) they actually target stock time series data, and the optimum fit Can i expect To this extent, does this model fit analogous data to that extent, in which the stock time series predicts future values?
Rather than comparing stocks or selecting models, if the benefit is my goal then what is it
Any ideas about which data program Most user friendly?
Be great and set a long way for me.
Thank you, Brian
I'm learning a different language to know speed on STATA I have done some work in the field of Vector Automobile Time Series model. It interacts between two time series and has a fairly recent (1980s) approach for many time series - especially with those who Interact at intervals. STATA handles this type of analysis
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