OK so maybe that's a bit misleading. I didn't actually spend the weekend in Monte Carlo. I did, however, spend the weekend learning about and doing a few Monte Carlo simulations.

For the uninitiated, Monte Carlo simulations are a statistical process for forecasting event outcomes. The process involves repeatedly running a scenario whose outcome is determined by the interplay of various parameters. The parameters themselves are subject to some statistical variance. The Monte Carlo process repeats the scenario process any number of times using these random variations and tabulates the results, yielding a distribution of likely outcomes.

What I set out to do this weekend was educate myself in the ways of using a spreadsheet to perform Monte Carlo simulations on various mixes of securities. I wanted to know - I still want to know - just what sort of diversification scheme is most suited for me and my investment style.

It's not hard to understand that taking on more risk can result in a much larger nest egg down the road; but that taking on that risk also greatly increases the chances of going bust. Alternatively, shunning risk greatly reduces the chances of going bust, but your portfolio's future value can be severely limited. Monte Carlo simulations against various mixes of low and high risk securities in a portfolio can help us to understand what future portfolio values we might expect at a given level of risk.

My models are producing interesting results. Not altogether unexpected, but they do illustrate the importance of being well diversified and accepting some amount of risk.

And isn't that what you'd expect? As they say, "You get what you pay for." If you want to be comfortable in your later years you have to pay for them. The price is hard work, careful planning and yes, taking on some risk.

I'll be looking at some of my Monte Carlo simulations using various mixes in the future and will report my findings here.