I am working on testing the Arbitrage Pricing Theory. So, I have 5 independent variables, or factors (oil price, inflation, industrial production, FX, stock index) that affect the dependent variable (stock return). So, I have a raw data on theses factors for the last 7 years to be processed. I need to find the betas regressing these factors on the computer software (maybe, STATA). But I don't have any idea, how to start this process. Should I create my own .dta format file to regress it on STATA if I don't have such ready to use data file? Is it possible at all?
p/s: I am considering the US stock market, actually S&P500 index. Thanks a lot.
Please from your data collected, it is a time series data. Instead of performing statistical test using Stata, SPSS, SAS, R, etc, i will strongly recommend that you perform econometric test such as Unit root test, Johansen Cointegration test, Granger causality tests, and Ordinary Least Square regression. The most suitable software that i will recommend is the Eviews software.
Time series data are often known to be non-stationary, thus a unit root test should be performed to turn such non-stationary data into stationary at first difference or in rare cases, second difference. The reason is that data for oil price, inflation, industrial production, FX, stock index and so on, were collected from secondary sources and must have been measured in different unit.
Use Eviews (Econometric views) software for your analysis.
Best regards
Owan
Why not using R https://www.r-project.org/, since it is free to use, quite easy to handle if you use for example R-Studio as a user platform https://www.rstudio.com/ and there are thounsands of documentations, examples and templates on the internet which you can use to get an idea how it works.
See Lander, Jared, R for Everyone, 2nd Ed, Addison Wesley, Chapters 6 and 19. This should get you started. R is free software. Best wishes.
Many thanks again, dear Professors. Indeed, R is a great solution tool.
Hi. With Matlab, the calculation process is very simple. The data can be stored in an Excel spreadsheet and then passed to Matlab. I enclose a written function in Matlab for multiple regression analysis.
Please from your data collected, it is a time series data. Instead of performing statistical test using Stata, SPSS, SAS, R, etc, i will strongly recommend that you perform econometric test such as Unit root test, Johansen Cointegration test, Granger causality tests, and Ordinary Least Square regression. The most suitable software that i will recommend is the Eviews software.
Time series data are often known to be non-stationary, thus a unit root test should be performed to turn such non-stationary data into stationary at first difference or in rare cases, second difference. The reason is that data for oil price, inflation, industrial production, FX, stock index and so on, were collected from secondary sources and must have been measured in different unit.
Use Eviews (Econometric views) software for your analysis.
Best regards
Owan
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