This is One Question - where I set the stage and let my guest take it from there.

Introduction

I am honored and excited to kick off the One Question series with Aleksey Chernobelskiy. I can’t recall when or how I became acquainted with Aleksey’s excellent Substack: LP Investing Lessons. But I do know that I immediately consumed everything he had produced up to that moment, and have read everything since.

In a space dominated by GP promises and investor dreams, Aleksey delivers a rare voice of truth that every LP desperately needs to hear - with the math to back it up.

Aleksey is a busy guy. He:

• Writes a weekly newsletter at LP Investing Lessons;

• Created LP/GP Match, an online deal sourcing tool;

• Consults with LPs and GPs on current and future deals; and is

• Hosting a small-format Real Estate LP/GP Summit in September.

Prior to advising LPs, Aleksey ran STORE Capital’s $10 billion commercial real estate portfolio and oversaw the firm’s underwriting team. He is a graduate of the University of Arizona with a quadruple major in Finance, Mathematics, Economics, and Accounting.

Connect with Aleksey on: LinkedIn | X | Substack | LP/GP Match.

My One Question to Aleksey

In response, Aleksey suggested revisiting a topic he covered just over two years ago that remains just as relevant today: Why LP investments won’t let you quit your 9-5.

Apparently we LPs can be slow learners…

To see the original post, click here. An updated version with my comments follows.

Why LP investments won’t let you quit your 9-5

As I peruse websites and LinkedIn pages of syndications, I continue to see the “quit your 9 to 5” narrative. I recently even saw it written as “grind to five”… which honestly just reminded me to write this article - welcome back! 😊

Today I’m going to try to explain, using a model, why these marketing messages are -at best - misleading.

Side note from me: unlike public equities, private equity does not have ethical and regulatory standards controlling marketing claims. Buyer beware.

I’ve been outspoken about this in the past (screenshot below), and I know many don’t like it.. but I’m here to show my work and will obviously take any and all criticism as always - in fact here’s a link to post your refutation! :)

Leave a comment

Today’s agenda:

1. What is a monte carlo simulation?

2. Why is it relevant to LP investing?

3. Assumptions

4. Discussing the results

5. Takeaways

Let’s dive in.

1) What is a monte carlo simulation?

I mean, first of all, what in the world is a monte carlo simulation?! Good question.

Simply said, a monte carlo simulation is where you start at a given point, assume some things about what happens along the way, and see where you end up! The result looks something like this (a random picture I found on Google).

You’ll notice that everything starts in the same spot… and then the results vary quite a bit depending on what happens probabilistically at each step of the model.

One easy way to think about this is coin flips:

• Take 50 people, and give them 100 coins each.

• Heads means they win a dollar, tails means they don’t make anything.

• You can imagine a chart of outcomes in your head:

  • Each person would have somewhere between $0 and $100 dollars.

  • All 50 people started at $0 and the outcomes will vary.

Ok, cool… but why is this relevant to us? 😊

2) Why is it relevant to LP investing?

Monte carlo simulations are relevant to LP investing because outcomes (even with the best due diligence) will vary … and to add to that, they’re generally outside of your control after you invest. This is why I always say that the best passive investments take active work in the beginning.

Most (all?) of the websites and ads that preach this “passive income to quit your 9-5” story want you to think that investing in syndications will lead you to retirement .. and the question I have is whether that’s actually true!

Side note from me: I can’t wait to hear this. I have searched in vain for data to support the cause for PE. If you know of data that supports the argument for or against PE, please email me: hello@netzeroisawin.com.

3) Assumptions

Recall that our goal is to figure out whether “investing as an LP will help me quit my 9-5.”

Let’s subdivide the “population” into 3 categories:

1: “Very wealthy”

• If someone already has the cash saved up to retire through dividends in the stock market (or investing in bonds, treasuries, etc), investing in LP investments doesn’t change the fact that they can retire.

• Therefore, this can’t be the case these websites are speaking of, since the individual is already ready to retire!

• QED (that’s short for a proof being over, sorry to bring you into my math major nightmares haha)

Side note from me: I believe there are a number of people who are already in this category and may not know it. There is no other plausible reason to take on more work and risk, unless the person enjoys it and/or has higher goals than funding one’s own retirement.

2: “Accredited”

• This is the section we’ll be dealing with in the analysis below

• Note that the accredited world is large - roughly 18.5% of US households (which includes the “very wealthy” group above as well)

• Nobody, in my opinion, should put all of their investments into one strategy (with the only exception being a business they’re running perhaps, but that’s not our topic).

• Therefore, it’s important to allocate only a certain percentage to LP investments - which is the case we’ll deal with in this article! We will assume $100k below.

Side note from me: today the number of accredited households is pushing 20%, and has lost nearly all of the intended restrictive nature from when it was crafted in 1982. To understand the history and modern implications of “accredited” status, check out “HEURISTICS: Accredited = Astute”.

3: “Non-accredited”

• Both 506(b) and Reg CF (regulation crowdfunding) investments allow investors that aren’t accredited

• There’s a lot to say on this, but for the sake of simplicity let’s remember that this is ~81.5% of the US population and I would argue one of these will always be true:

  • Investor doesn’t know how to vet LP investments (i.e. loss probability is high).

    • I would also argue that for many people that fall into this bucket investing the capital into themselves (e.g. education) or using the time they would spend on vetting these deals on advancing their career would probabilistically yield higher returns in dollar terms over a long horizon.

  • Investor doesn’t have enough saved up to make a material dent in saving towards retirement (e.g. if you want to invest 10% of your net worth into syndications a $100k check would already put you into the 1MM net worth bucket that we talked about in point 2 above).

    • There are some edge cases here, but I think you’ll agree after reading this that we’ll deal with them via investor #3’s case presented below.

• To be absolutely clear, where I stand here is that for a non-accredited investor it’s very unlikely that these outcomes will lead to helping you retire:

  • QED again :)

  • One path is over allocating and “risking it all,” but I hope we can all agree that’s called luck rather than investing.

Alright, so now let’s get to the fun parts - the modeling!

PS if you’re still reading… you’re in the 1% of nerdy LPs, perhaps an “accredited LP nerd” would be proper!? 🤓

4) Discussing the results

The Methodology

First, let me introduce you to the uniform distribution- this is basically where you pick any number at random between two numbers.

In our case, I chose 0 to 1. The number on one draw could be 0.9999, 1, or perhaps 0.11111. I hope that makes sense.

We will use this variable to determine what happens to someone’s money after a five-year period (which is a typical hold period in a syndication). Then we’ll use it again to see what happens in the next five-year period…for a total of 40 years.

Now, one clear problem is that a multiple between 0x and 1x is clearly unfair - nobody invests in those odds, right?! You’re right, so we’re going to adjust it 3x whatever the number generator gives out.. in other words, pick a number between 0 and 1, and then multiply by 3. This accounts for the fact that some syndications will have outlier results, while others might lead you to lose your money (but recall that our original draw of 0.5x, a loss, will now be 1.5x .. so the odds have moved!).

The Results

Here are the results:

• We start with $100 (for the sake of our example, let’s assume that’s thousands).

• Two examples based on the table below:

  • Investor 3 did well on their first deal - a 2.35x multiple in 5 years, and the second deal was alright, but then the third deal (a random number generator again) didn’t do so well… the experiment continues on until the investor ends up with 150 (vs original 100) at the end of 40 (!) years

  • Investor 18 absolutely crushes it - $56 million from a $100k check!

• Over a 40 year period, the average IRR with this simulation is 8.6%, where you’ll end up with $2.7 million (and you started at $100k, pretty cool!).

  • Let’s remember that there’s inflation…we’re ignoring that

• But remember that averages are skewed by outliers.. and $56 million from above is quite the outlier… so now look at the median… roughly a 2x multiple over a 40-year period, or a 1.9% IRR - ouch!

Here’s a graphical representation of the first 25 (50 gets a bit busy):

A fair question on the above methodology is “but outcomes shouldn’t be equally spread between 0 and 3x. For example, it’s more likely (across a large enough sample size) to get all your money back in a real estate syndication vs losing it all.”

You might even imagine a normal distribution (a bell curve), but the problem is that this curve has no bounds (while with an LP investment, the “worst” outcome is losing it all as opposed to losing more than what you had). I have a few ideas for the right distributions for this and will do part 2 soon for the ultimate accredited LP nerds - stay tuned!

5) Takeaways

I think there are a few lessons we can take away from our work today:

• Accuracy matters - you can see how expensive it is to lose money, in some cases our investors couldn’t recover from the loss in a very long time horizon. More on that here.

• Secondly, and not including inflation, your $100k check will get you to $2.7MM on average… but only $212k using a median (here the median matters more, since it’s an actual outcome, as opposed to the average).

  • Even the average IRR of 8.6% isn’t so incredible… and the entire time you didn’t have liquidity like you would in the stock market (which also averages 8% over a long hold period).

• Having said all that, $2.5MM*~8% is a nice $200k check every year while still having your equity invested … and this doesn’t account for additional investments that you might have invested in along the way!

• I hope this helps you conclude initially (more to come with another probability distribution) that investing as an LP will only help one (of our three populations of people described in the assumptions section) get to retirement (1) AFTER 40 years (!) and (2) with an investment return that doesn’t differ greatly from a stock market index.

  • But to be clear this subset (accredited investors) of the population accounts for roughly 18.5% - while the websites target much more than this.

    • Perhaps one could even argue that within the subset of 18.5% of accredited investors, there are people who are so inexperienced (recall that accuracy matters) at investing that the entire argument falls apart altogether.

  • Again, more coming on this with a new distribution, where I hope to also show how much accuracy of your investments matter.

My Thoughts

My takeaways based on the results of this methodology:

• In the absence of actual results, the modeled data is relevant and worth consideration.

• PE returns are not very compelling:

  • the median PE return is 1.9%, which barely tracks inflation.

  • The (inherently skewed) average return of 8% mirrors a public market index over the long term - and requires far more initial and ongoing work.

• Exceeding the long-term average return of 8% provided by a public market index fund via PE may be possible, but requires the knowledge and dedication to consistently outperform the market - a skill and practice few people may be capable of achieving.

• Approximately 65% of the results fell below an IRR of 8% (the index fund comparable return), and 6% of results fell below a 4.5% return (the treasuries equivalent). Would you risk your retirement on a 65% chance of not achieving an equivalent result?

• Marketing claims are just that: marketing. Making informed decisions requires using unbiased, data-driven information.

Thank you

Thank you to Aleksey for answering my one question so thoroughly and with the math to back it up.

I encourage you to engage with Aleksey on: LinkedIn | X | Substack | LP/GP Match.

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There are so many smart, insightful, and generous people in this world whose words merit sharing. That’s why I am creating a new series, One Question, that is dedicated to providing a platform for those words.

The premise is simple: I pose one question - crafted just for that person - and let them do the rest. I can’t wait to see what they have to share with us.

My guests will be covering a variety of topics like: the lessons we just can’t seem to grasp; the handful of conclusions that only millions of private data points can provide; how to capitalize on losses; the evolution of transparency in private investments; and more.

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