You cannot estimate a regression model with 6 IVs and only N = 5. You literally can't even estimate this model, let alone do so with any reasonable statistical power.
You will need to consider whether you can dramatically increase your sample size, or perhaps change your unit of analysis (e.g., to financial performance by year, for many different years, with year nested in company).
With the year-by-year data your model is technically estimable, but doing so is (imo) effectively pointless. Your sample size is so small that your estimates will be so imprecise as to be almost uninformative. And you have time series data, but insufficient data to identify any correlated error process (which you would need to). I think you need to go back to the drawing board and figure out what would be a more suitable data source to answer the research questions you have. Sorry - this is not a case where a clever statistical approach is going to help.
Yeah, I guess if the OP can get a new and larger sample, that'd be a much wiser approach than trying to come up with a clever solution that would be bogged down in caveats. I also think that this is probably a case where more data is available or the question can be restructured to make a larger data set more attainable. Good point.