Annualized Return
Once upon a time I wrote a tutorial about a calculation that gives, very nearly, the Annualized Return if you know the Mean Return and Standard Deviation. In fact, there was a cute geometric picture like so

>And how good is it, this "very nearly" value?
Aah, I'm glad you asked! That's what I want to talk about.

Figure 1
There are two (at least!) such approximations.
If we let the Mean Return be M and the Variance or (Standard Deviation)2 be V then the Annualized Return, R, is given by:

[1]       R = M - (1/2)V
[2]       (1+R)2 = (1+M)2 - V

>The second one is Figure 1, eh?
Anyway, I tested both on a bunch of stocks (and indexes) over the past ten years and here's what I got:

Well ... uh, that's approximation [2], as in Figure 1.

>And YOU invented it?
Hardly, but I did generate the formula here ... although I'm sure it's been generated a jillion times before

>And it's just for "annualized" returns, right?
No, [1] and [2] are both reasonable approximations not just for annual returns and variance but, for example, monthly ... like so:

>You're talking a monthly compound growth rate?

>Which do you prefer, [1] or [2]?
If I'm interested in calculating an Annualized Return (asssuming I only know the Mean and Variance), I'd use [2].
However, if I want to do some mathematical analysis, I'd use [1].

>Because it's simpler?
Because it's simpler.

>And you're not concerned about accuracy?
Accuracy? In financial forecasting?
No, I just want to get a feel, to get some indication of how things may vary from one situation to another, to test various scenarios, to ...

>Because it's simpler.
Ummm ... yes.