After the hard work of last Thursday’s post, where we developed functions to induce correlation onto our random samples, today’s is light relief by comparison, though a bit boring. This post discusses the mechanical aspects of putting it all together into something that works. Read more
Welcome to the third of five (sort of) posts about Monte Carlo risk analysis using Excel VBA. Actually, what was going to have been today’s post has turned out to be much longer than my target of around 3,000 words, so I have decided to split it in two, with the second half appearing tomorrow.
Yesterday we looked at how to generate arrays of random numbers using a combination of inverse transform and ‘latin hypercube’ sampling. Today we get to the heart of the problem and consider how to induce correlation onto our random sample using the Iman-Conover method. This is based on the idea of rank-order correlation. It involves the following steps: Read more
Welcome back! This is number two in a series of five blog posts that describe how to construct a Monte Carlo risk analysis application in Excel VBA. It follows on from yesterday’s, where I gave an overview of the problem and how I propose to tackle it. Today’s post describes how to generate random numbers according to arbitrarily chosen probability distributions using the inverse transform method. Read more
As this is my first blog post, I thought I’d try something slightly more ambitious than just spouting opinions. Unfortunately it’s turned into something of a treatise. If I’d known how big it was going to be I probably wouldn’t have started but, as Magnus Magnusson would have said; “I’ve started so I’ll finish”! I will feel it has been worthwhile if someone somewhere makes use of it. Read more