Too Good to Be True

A friend of mine was laid off a few months ago and has had a tough time on the job market since. After weeks of applying and getting nowhere, they received a bit of hope—a glowing email response.

The email stated that my friend was just the candidate the company was looking for and that, to move the process forward, they needed to fill out some paperwork and complete some proficiency tests. All of this would be done through an online messaging portal. So my friend logged into the portal and gave them the information they asked for.

After a few days of back and forth, they were informed that they got the job. The position would be 100% remote, included new computer equipment, and the company would even pay for their internet. My friend was ecstatic. All they had to do now was fill out an I-9 employment verification form (which asked for their Social Security number).

But, before accepting the offer, my friend got a little suspicious. Was this job real? After all, they hadn’t physically spoken to a single person (and they weren’t applying to work at Gumroad). So my friend dug deeper.

They searched LinkedIn for the employee they had been messaging with through the online portal and found them without issue. Then they checked the company’s website and, once again, nothing looked amiss. Lastly, they called the company for a final confirmation. That’s when everything came undone.

There was no job. The person they were messaging with wasn’t who they said they were. The entire process was a scam to harvest identities and Social Security numbers. Thankfully, my friend knew to double check. Other job seekers weren’t so fortunate.

The moral of the story is simple—when things seem too good to be true, they probably are. I see this all the time in financial markets, but some ignore it to their own peril.

For example, I remember the pushback I received from some in the crypto community after arguing that cryptocurrencies weren’t income-producing assets. A few people countered with, “What about staking?” For the uninitiated, staking is the act of lending out your crypto and earning some yield on it (which is paid to you in the form of more cryptocurrency).

I didn’t feel comfortable with this idea because I believed it wasn’t picking up the unknown risks inherent to the crypto ecosystem. And, because of these unknown risks, I argued that you couldn’t classify crypto as an income-producing asset. And, after the recent crash in Terra and the halt on withdrawals from the Celsius network, it seems like my intuition was right. The high yields weren’t without risk.

I don’t say this as a gotcha, but as a reminder that true arbitrage rarely exists (at least for retail investors like us). That killer deal you think you’ve found probably isn’t so killer after all. It’s more likely that you found something with hidden, unknown risks. This is why I believe that earning a yield a little higher than U.S. Treasuries is plausible, but earning 20% a year in a “risk-free” stablecoin is not. There’s nothing risk-free or stable about it.

The same goes for any endeavor where you make a lot of money in a short amount of time. For example, consider this thread about a crypto trader who went “from a crypto-millionaire to broke in 6 months due to leverage, a gambling addiction and an accelerating negative spiral.” Or how about this thread about another crypto trader who went from $0 to $10 million in three years and then lost it all in the year that followed?

Both are examples of individuals who should’ve known how lucky they were and stopped (or at least de-risked) while they had the chance. But, they didn’t. In the end, the only thing they realized was that their gains were too good to be true.

Yet this isn’t even the craziest part about these stories. The craziest part is the people in the replies saying, “Don’t worry you’ll make it all back.” What? What planet are these people on? Even when faced with overwhelming evidence that these strategies aren’t sustainable, some refuse to get the message. They can’t accept that these two guys weren’t geniuses, they were just in a bull market.

But, I’m not here to single out crypto traders because the exact same things happen in traditional finance all the time. You hear about the person losing it all trading options or going all in trying to catch a falling knife. Either way the result is the same—people thinking they found a deal where there was nothing at all.

How do I know? Because, even when you find something too good to be true that is actually true, it usually doesn’t last either.

For example, consider what happened to the outside investors in the famed Medallion fund run by Jim Simons at Renaissance Technologies. As Gregory Zuckman summarized in The Man Who Solved the Market:

In 2002, Simons increased Medallion’s investor fees to 36 percent of each year’s profits, raising hackles among some clients. A bit later, the firm boosted the fees to 44 percent. Then in early 2003, Simons began kicking all of his investors out of the fund.

Not only did Simons get away with charging a 5% annual management fee (over double the 2% industry standard), but his performance was so good that he was able to continually increase his fees before kicking all his outside investors to the curb!

I raise these points because markets (and people) are smarter than you think. They don’t act irrationally forever. They will find their way and reach an equilibrium. This is why you can’t expect to yield 20% on your money when everything else is paying less than 4%. You can’t expect to go from $0 to $10 million in a few years and sustain that growth. You can’t expect to discover the greatest money-making machine of all time and have its creator share it indefinitely.

But you can expect to come across more things like this in your future. You can expect to come across more things that will be too good to be true. But, when that time comes, will you know it?

Thank you for reading!

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This is post 299. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data


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