I’d been wandering for a while just how long a ‘long term investment’ is. There’s lots of good stuff written on this, but for me there’s no substitute for getting my hands dirty in data. So I dusted off Excel and took a look at the numbers. This analysis is not unique, I’m sure. It’s probably not even entirely accurate. I’m looking forward to hearing about all the ways in which it is flawed, so that I can do v2.
Here are the results (click to get a good look). The method, and a little analysis of the results, are below.
You’re looking at 6 different lines, one for each different ‘investment length’. For example, the blue line shows the distribution of returns on a 1 year investment in the S&P500, taken over all the possible 1 year periods that occurred between Jan 1950 and Oct 2008. The orange line show the distribution of returns on a 30 year investment, which as you’d expect, is much tighter.
A few things stand out for me:
- Five years is not a ‘long term investment’, unless you’re willing to accept a fair chance (~25%) of performing at (or well under) a savings account like return (~4%)
- Even at twenty years, there is a ~20% chance of getting a return between 2% and 4%, which would be a bit disappointing as an investor, IMO.
- Based on the last 58 years of data, it looks like 30 years could be considered ‘long’ (but remember what they say about past performance)
Disclaimer: I’m really not any sort of an expert at this. This is 30 minutes in Excel with data from Yahoo Finance. There are a million nuances that I’m missing.
Of course, this is for investing a lump sum of money at one point in time. Most consumers would actually invest continually over a long period of time, which creates a dollar-cost-averaging effect. Maybe I’ll look at that next..
What does this chart say to you? Let me know in the comments.
I calculated the annualized return by dividing ‘month A closing price’ by ‘month B closing price’. I then raised that number to the power of 1 over the number of years between month A and month B. I then subtracted 1. I then measured frequency of that return by counting the number of occurrences of the return in buckets 2% wide (i.e. count x where: 2%<x<=4%), and dividing by the total number of periods of that length in the test (shown as ‘n’ in the legend). I then plotted the mid-point of that bucket (i.e. 3%) on the horizontal axis, and the corresponding frequency on the vertical axis.
I’m looking forward to hearing your thoughts, and suggestions for v2.