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 ?
[[alternative HTML version deleted]]