Concrete's comments

Thank you! We've got some premium features in the works. In the meantime, I'd like to keep the site clean (I hade the way advertisements muddy up the UI)and just let folks use the baseline simulator for free.

Thank you! We've got quite a few ideas for additional simulation features, reports, and data exporting services. In due time, we might make these extras part of a premium/paid tier. In the meantime, unless we run into some unforeseeable costs, I'd like to keep the baseline version of the simulator free for folks.

Really appreciate this feedback. I actually agree with you on the account requirement (I hate making accounts too, and then I went and created an app that requires one; the irony isn't lost on me!). But I'm a bit paranoid about server costs. Once we're certain that scaling this in AWS is going to be as cost effective as we think (and it's looking pretty good), I'll feel more comfortable removing the friction of having folks make accounts. My real expertise is finance, so I'm outsourcing much of the tech stuff, and I'm leaning heavily on my team for their input in these areas.

As for having to log back in immediately after exiting the app (and not saving assumptions)--that's a real pain. I'll have my guys get that fixed ASAP.

We're a small team building professional-grade financial planning tools for everybody. Our aim is to democratize the powerful resources traditionally made available only to financial advisors.

The financial independence movement is popular and growing, and folks have more resources available to them than ever before. Unfortunately, some of the most popular "Retirement Calculators" online are flawed and misleading. We'd like to give people better tools.

We recently launched our MVP: a powerful Monte Carlo portfolio simulator with "fat tails" and "Black Swan" features. It's entirely free to use.

We understand that making an account is a pain and seems unnecessary. But here's the skinny: we're scaling this with Amazon Web Services. Since we're new and growing, we sincerely don't know how much it's going to cost to keep everything running 24/7 in the cloud. The affordability is looking promising, and we'd love to give folks free and powerful software. But until we get a better grasp on the potential overhead, we need a way to filter for usage abuse and other shenanigans. Having folks make accounts is the best way for us to monitor this for now. We plan to soon add Google and social media log-in options, too.

For what it's worth, we never share or sell your email address, but we understand the skepticism, and we want folks to use the tool in any event. So, if it's a dealbreaker, we encourage you to use a temporary/disposable email address. The only downside to this approach is that we won't be able to alert you when we've made updates. And we've got some cool things coming.

We'd love to hear your feedback and answer any questions.

Great questions. I strongly encourage folks to be careful with portfolio “back-testing”. There are a number of problems with using historical returns (or “boot-strap” sampling) for forward-looking analysis. The most conspicuous concern is the prevailing level of interest rates. Using historical stock and bond returns would entail annual performance of 10%-ish and 5%-ish for each asset class, respectively. In today’s environment, given high stock price levels (P/E ratios) and with interest rates fluctuating near historical lows, the consensus is that we should expect considerably lower returns for the foreseeable future.

For example, J.P. Morgan’s most recent capital market assumptions forecast a compound annual return of just 4.1% for large-cap U.S. stocks (e.g., S&P 500 Index) over the next 10 to 15 years. This is in stark contrast to the 10% to 12% historical returns pop-finance personalities often cite when setting expectations for future returns. For this reason, performing forward-looking analysis based on historical investment performance could result in grossly optimistic results and a false sense of security.

Monte Carlo simulation does in fact account for sequence of return risk through volatility and random number generation (but perhaps I misunderstood your point on that front).

As for the cyclical nature of returns, that’s a topic that continues to be debated. The historical behavior of markets in a developed country with enforced property rights, relatively strong institutions, and victories in two World Wars (e.g., the U.S.) is much different compared to other parts of the world. Maybe mean-reversion exists, or maybe we like to see patterns in data. In any event, we do plan to add customizable mean-reverting functionality in the near future.

Here’s some more info you might find helpful:

Studies of Market Behavior in Academia:

https://www.honestmath.com/learn/academia

Perspectives on how little we actually know, and how little historical returns might actually tell us:

https://www.honestmath.com/learn/nobody

Some more relevant thoughts:

https://www.honestmath.com/learn/simulation-probabilities-ar...

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.

Happy to answer any questions you may have.