My friends and I created a retirement calculator with many professional-grade capabilities. The model uses a 10,000 trial Monte Carlo simulation. We've made this pretty flexible, and have opened up the statistical settings for modification. We've also wired in "Fat Tails" for stock returns and added a "Black Swan" feature.
Each simulation requires generating millions of random variables and performing tens of millions of calculations. We understand requiring a sign-up seems like an unneccessary hassle, but we're scaling this on AWS and want to filter bot traffic due to the computational requirements. We apologize for this annoyance.
I'm curious why you chose to use the monte carlo approach? Other tools in familiar with use historical market data instead.
A lot of what I've read suggests that monte carlo doesn't approximate the market very well. The market is not random. It has well defined historical cycles (bull, bear, sideways). Also, issues like sequence of returns appear to have a large impact on portfolio longevity. How are you thinking about these sorts of issues?
[+] [-] Concrete|4 years ago|reply
Each simulation requires generating millions of random variables and performing tens of millions of calculations. We understand requiring a sign-up seems like an unneccessary hassle, but we're scaling this on AWS and want to filter bot traffic due to the computational requirements. We apologize for this annoyance.
Happy to answer any questions you may have.
[+] [-] cyb_|4 years ago|reply
I'm curious why you chose to use the monte carlo approach? Other tools in familiar with use historical market data instead.
A lot of what I've read suggests that monte carlo doesn't approximate the market very well. The market is not random. It has well defined historical cycles (bull, bear, sideways). Also, issues like sequence of returns appear to have a large impact on portfolio longevity. How are you thinking about these sorts of issues?