How do you measure your portfolio’s return?
June 16, 2008Thanks for visiting! If you like what you're reading, you may want to subscribe to my RSS feed.
Admittedly, it’s been getting very quiet on the blog front and you’ve all heard the excuses of working late and being busy, so I won’t bore you for very long before moving on to more interesting stuff. But can I just say that I also walked 20 miles for charity and that took away some blogging time!
I bet that’s a new one for most of you…
Anyway, as I promised in my last post (yes it’s been a while) I have had an idea about a series of posts that might be of interest to you, especially if you really really like numbers (like I do). While reallocating my pension across several funds, I kept wondering how to best measure how well (or badly) my choices were performing compared to the market in general. For a start I have split money fairly evenly across index funds and actively managed funds in a way that will hopefully allow me to compare apples with apples - i.e. simply speaking, for each asset class I have picked an index fund as well as an actively managed fund to compare their performance against each other.
Somehow, that didn’t seem good enough and so I did some research on what else I could do. As I said, I like Maths and numbers because they have an inherent logic and beauty… great, now I sound like a total geek. Or idiot. Your choice
Hence, here’s my line-up of posts that will hopefully appear throughout June and July (bear with me as I’m also going on holiday in three days). I’m not going to explain much (or anything) at this stage, because otherwise there’s not much point in writing separate posts about each. I simply hope you’ll be excited to read what’s coming up and all the things you might be able to learn soon(ish).
1. Post : The Basics
- arithmetic mean (average loss, average gain)
- geometric mean
- frequency distribution
- maximum value
- minimum value
- positive # of years / months / weeks
- negative # of years / months / weeks
2. Post : Risk
- VAR: value at risk
- M-squared
3. Post : Statistics
- standard deviation
- semi-variance (semi-deviation)
- downside variance
- below-target probability
4. Post : All About Interaction
- covariance: degree of variability of returns between two assets
- correlation coefficient
- units of annual return per unit of std. dev.
- expected final value of $1.00 / £1.00
5. Post : First lesson in Greek
- beta coefficient or an assets’ degree of responsiveness to market movements
6. Post : Advanced Greek
- alpha or superior returns
7. Post : More Jargon
- sharpe ratio
Some of these will be rather obvious, or aren’t even really mathematical but I thought they were nevertheless useful when analysing your portfolio. I’m going to try my best to explain even the more complex concepts in a straight-forward way that will make you (and me) understand why exactly a particular formula might in fact be useful.
Knowing myself, all of the above will eventually end up in a big spreadsheet, which I naturally will also make available to you so you don’t have to play with Excel for hours to get it all onto one page (surprisingly enough not everyone finds that sort of stuff fascinating).
I’m getting rather excited while writing this, so hopefully my energy won’t be wasted and you’ll enjoy it as well!
Let me know if you think I’ve omitted anything absolutely obvious that shouldn’t be missing from a series of posts on portfolio calculations.
















