This is a follow-up to my post A simulation of angel investing.
Several readers commented on Hacker News that my first stab at a simulation was misleading because it showed negative average returns for low deal sizes, when in fact expected returns should be not only positive but constant regardless of deal size.
They are right.
I had been using payoff as the random variable, but rate of return as the measured variable. The formula for rate of return (x^(1/t)-1) places the most weight on the zero-payoff case (where return = -1.0), so the simulation results were skewed towards negative expectations, especially for low values of D.
In this new post, I present a simplified and more accurate simulation of angel investing.
As before, my goal is to shed some light on this question:
How many angel investments are needed to make the combined payoff look attractive from an investment standpoint?
I coded the following simulation in Python.
1. Create a pool of 10,000 different investors, each investing in D deals, with a fixed distribution of payoffs per deal. Randomly simulate each investor’s combined payoff,>>> READ MORE at: