

I want to do a daily, weekly and monthly regression between InvestmentGrade 
Credit Spreads (Dependent Variable) and Treasuries (Independent Variable).

My starting point is daily spread data and daily prices for US treasuries.

Should I convert the US Prices into log returns i.e. log(Pt/Pt-1) or simple 
daily returns (Pt/Pt-1 - 1) for this analysis.

What about Credit Spreads - credit spreads is like a return - so should I take 
log(spread) or simply use the spread.

Lastly , the aggregate from daily to weekly or monthly , what functions should I 
use - Do I aggregate the log returns or
the simple returns - do I take a simple sum or a cumulative aggregation - and 
how would I do it in R

I am inclined to use the log returns for everything as regressions, correlation 
calculations all assume normality.

But then to aggregate I would need to use the original returns (or spreads) - 
aggregate cumulatively - and then take the log ?


      
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