So, if twenty years of data on returns is not enough, and 10 years of data on returns basically tells us nothing, what do 10 and 20 years of data tell us about correlations? Thanks.
Reminds me of a t-shirt once seen on a stats professor: "When all fails, manipulate the data" Lol. Jes messin with ya
It's a matter of taste. I always use rf== 0% because I don't want to spend brain cells on backing out this-or-that rf rate. Similarly, I use pre-slippage numbers.
Excellent question. There is no easy closed form, but when I looked at the correlation of US stocks and bonds (which is also slightly negative) after five years the 90% range was about -0.3 to -0.2; and the range doesn't get much tighter after that. So in simple terms we need relatively little data to form an opinion on correlations, and we can be much more confident about our estimates of correlation than we can about Sharpe Ratios. Incidentally the same is true of volatility. If the estimated correlation of Cantab and SP500 was -0.1 then after ten years the range would be around -0.15 to -0.05. GAT
Wouldn't a conservative approach (rf = 10y) be more prudent, over and against convenience, especially considering that rates have been heading higher?
This isn't clear? In simple terms we need relatively little data to form an opinion on correlations, and we can be much more confident about our estimates of correlation than we can about Sharpe Ratios. If the estimated correlation of Cantab and SP500 was -0.1 then after ten years the range would be around -0.15 to -0.05. I'm not trying to prove anything, I'm just answering your question (what the statistics are for correlation estimates). GAT
You are assuming your conclusion, once again begging the question on this claim above re "we need relatively little data". You also contradict your own statements below. If 10-20 years is not enough for statistical knowledge on returns, it is also not enough for statistical knowledge of correlations. Ask LTCM. And btw, do yourself a favor, and be careful about throwing words like "daft" out next time. You never know what's going to come back and hit you.