This graphic is awesome primarily because it shows that it is not correct to assume that volatility in the equity markets is averaged out completely during a timespan that is comparable to the average savings portion of a career.

edit: oops, meant to reply to GP

First, as you often see in these studies, they use the S&P500 which has returned a 9 or 10% annualized rate for decades now. How realistic is it to see someone's entire wealth invested in just this benchmark? Diversification will almost always mean returns lower than than the S&P. Ultimately this erodes at the findings of the study.

Second, there's no mention of yield which is basically the guaranteed portion of the return. This portion alone accounts for a quarter of your annual return making it another compelling reason to be invested early.

1) from the visual it seems to me that the starting year is the most relevant. If you start in a good year, it will mostly turn out right, regardless whenever your end (exceptions aside, for which see point 2). If you start in a bad year it will mostly work out badly unless you really have some time to spare or manage to run into a very rare occasion (e.g. starting in 1947 and ending in the mid 1950's). But that's just from the visual, which can be very misleading, so the raw data points would be interesting to do some statistic exercises. If that holds true though, it could be a good guideline - assess the current returns of a particular fund and do not invest [in it] if the current returns are not high enough. While this would make you, by definition, miss out on any really spectacular returns, it could reduce risk enormously without sacrificing much in terms of returns.

2) if you happen to have invested in a fund that took a nose-dive, hang on to it and don't sell for a long while, as in the long run you're apparently very likely to end up at the 20-year median (guess it's called a median for a reason ;-) which is not too bad. At the very least your loss is going to be minimized with time.

It would be helpful if it compared against the same visualization for other straightforward market investments, like bonds, or savings accounts / CDs. Those asset classes would be red (or pink for long-term bonds, perhaps) across the board. Stocks look great in comparison.

But picking a slightly more reasonable color scale would help.

That said I think there's some important drawbacks to point out.

First, that 7% figure that's often quoted is usually meant to mean nominal return. At least, that's the way it works relative to the commonly cited 4% SWR.

Second, buying and selling exactly once will greatly increase the variability of returns and also the likelihood of negative returns. It's important though to realize that this isn't actually how almost anyone invests, so just counting periods of negative returns under that assumption isn't particularly meaningful.

Of course all that tells you is that it's stupid to pay 2% management fees if you can get the same return with lower management fees. That's obvious. Whether you can get the same return by yourself is a separate issue. Now, in the long run, your typical investor is going to get the same return (pre-fees) with active management with 2% fees as he does with an index fund at 0.1% fees, hence he's going to come out ahead using an index fund. But at least in theory what Wall Street is selling you here is better return than what you could make on an index fund.

In a way, it's the same as every other product that drives the modern economy. They're selling you an idea (in this case, that active management will yield higher returns). In reality, its the same cheap Chinese crap everyone else is selling.

Can you source this? If it was that easy to get a consistent 50% return then why aren't more people doing it?

1. Why 10 years as the forward return period -- would be nice to see the situation for other return periods, even close to 10 years. Granted, it is a round number and doesn't appear to be cherry-picked, but still.

2. Why 1952 as the starting point -- presumably because the data from FRED starts there, but can this not be extended further back?

3. Why an implausibly linear relationship between the equity allocation percentage, which is bounded (0%-100%) vs. the returns, which is unbounded on either side, over such a large range of values? What is the mechanism to explain this? In other words, what is the proposed model that transmits allocation percentage into a return, even if the directionality of correlation is at least likely? What happens around 0% and 100% allocation -- do the extreme cases make sense?

I'd like to run my own data before I believe this.

The other thing that the frugality and savings über alles crowd neglects to mention is that different people have different preferences (and that's okay!). Including preferences dealing with intertemporal discounting. It's one thing when you are trying to develop pithy messaging aimed at the general public and quite another to make un-nuanced arguments in forums that allow for them.

The statistic that matters, as Warren Buffett and others have repeated again and again, is COMPOUND RETURN!!!

Consider these two investment options. Option 1 outperforms 60% of the time (three out of five years), but Option 2 produces a greater compound gain:

  YEAR     Option 1  Option 2
  Year 1       8.0%     15.0%
  Year 2       8.0%      7.0%
  Year 3       8.0%      4.0%
  Year 4       8.0%     19.0%
  Year 5       8.0%      6.0%
  
  Total gain  46.9%     61.4%
  Compound/yr  8.0%     10.1%

For example, what if it turns out that only a small number of actively managed funds are consistent long-term outperformers but many of them claim to use the same investment methodology? That would be a very unusual concentration of long-term success. I'd love to see a study with that kind of analysis.

This is well captured in this guy's drawdown charts:

https://portfoliocharts.com/portfolio/drawdowns/

Let me address your methodology comments nonetheless, which are for the most part unfounded.

* I don't have any finding about annual income. I don't think it is mentionned anywhere in my conclusions.

* "delinquencies and public records has a big impact on returns as newer loans are not aged enough": because I average across vintage, and because I don't average based on volume on the platform, I account for the aging biais.

* "Time is not risk [..] kurtosis etc.": I don't say that time is risk. I suggest the reader to look at the return series through time. Essentially to look at the volatility of the returns ( without pronouncing the word volatility to keep the content accessible to a novice reader). I essentially encourage the reader to visually assess his Sharpe ratio. Which is a good universal risk measure.

* "reconsider average across vintage": averaging across vintage is a first approximation. I acknowledge the fact that a better methodology would be to take a weighted average that matches the amortization profile of a loan.

* I maintain that any statistics you compute in 2006, 2007 or 2008 is less reliable (statistically). Yes it is an important period to have because of the crisis. And this is why I put on the chart. However, you can't compute very reliable returns when you have a dozen of loans to average across.

Anyway, I happy to exchange with you in PM on methodology if you would like to continue the discussion

Running the 6 asset classic, it is slightly amusing that the result is essentially just a classic 70-30 stock/bond mix (risk dependent obviously), and the other 4 assets are <5% of portfolio.

Would be nice if you could include also representative ETFs of a given asset class (I assume they exist) to make the results more actionable.

I'm still convinced that the general advice out there is highly out of whack, and that someone's expected returns should be very low. I'm currently modeling under 2% (post-inflation, more like 4% with) for the future, for a simple allocation model and a 10-year window.