you can ONLY eat risk-adjusted returns

Last month my friend Khe published a letter pointing to Money With Katie’s adjustment to the 4% rule for avoiding “lifestyle creep”. The 4% thing is a rule-of-thumb for spending so you don’t outlive your assets in retirement.

My Rule for Avoiding Lifestyle Creep: Don’t Live Beyond Your Assets (2 min read)

Katie’s adjustment is a simple formula that marries both assets and income to come up with a spending rule that balances the desire to spend more as you make more while still saving enough for your future.

The formula = (4% of net worth + post-tax income) / 2

I think of rule-of-thumb like this as an API to a complex code base known as “retirement finance”. Nobel Prize winner William Sharpe said knowing how much to save and spend for retirement is “the nastiest, hardest problem” in finance.

That 4% rule abstracts away the interaction between investment returns, inflation rates, longevity, and taxes because, well because, we can’t let ourselves be paralyzed by this problem before brushing our teeth every morning.

But that 4% rule and any other “rule” is obviously a guideline sitting on assumptions with generation long lookback windows. And as we learned in Sunday’s letter, we don’t have a lot of samples of generation-sized windows to generate any confidence-inspiring inferences.

The entire output of the personal finance industry on the topic of investment history is a streetlight problem. But forgivable. Remember “hardest, nastiest problem” and we still gotta find the toothpaste.

Despite a career in options trading, replete with greek letters and complex financial instruments, I find myself in total agreement with Corey Hoffstein’s recent podcast guest Victor Haghani who despite being a super-quant (sometimes super means flying to close to the sun as he was also a partner in LTCM) admit that when he left high finance he realized he didn’t know how to invest.

From Last of the Tactical Allocators:

After LTCM, I woke up, and it wasn’t a dream — I realized that I needed to focus on managing my family savings. Up until that time, I had worked at an investment bank that took a lot of my compensation and put it into the stock of the company, Solomon. At LTCM, it was pretty natural to invest a lot of my savings in our fund that we managed.

It was a shocking realization to see that I had been working in finance for about 17 years, alongside some really brilliant minds — practitioners and academics — yet I had never really thought much about investing for myself. All of my focus had been on research, to begin with, and then proprietary trading.

[Kris: I wrote a post my own wake-up call: My Investing Shame Is Your Gain]

My situation was typical: you come out of college, go to Wall Street, and get trained in everything related to Wall Street. Unless you’re going into private wealth, which Solomon didn’t even have at the time, you don’t get trained at all in personal finance. So, there I was, looking around to see what my friends and respected colleagues were doing. Everyone was following the Yale Endowment Model that David Swensen had made so popular. Yale’s returns were incredibly attractive.

I knew people in private equity, hedge funds, venture capital, and distressed investments, so I started investing as though I were a one-man Yale Endowment. Meanwhile, I was on sabbatical from working, spending time with my young kids. After four or five years, I had this realization that what I was doing made no sense — from a life perspective or a risk-and-fee-paying perspective.

The final straw was when I sat down with my accountant, David, to review my tax return for one of those years. I asked him, David, why am I paying all this tax? I haven’t had that much income this year. He explained, Well, you have this income here as short-term capital gains, and you have these expenses over here that you can’t deduct because they’re miscellaneous itemized deductions.

It was like an epiphany: Geez, what am I doing? I realized I had to go back to basics.

A category of basics that I think are fundamental to investing is what I broadly call return math. It matters because investing is really a nesting of many re-investments. And compounding is the realm of multiplication. While it’s true that multiplication is just addition on ‘roids, a failure to understand it can mean the difference between the prefix “ste-” or “hemor-”.

We’ll go to Victor for some education.

Eating risk-adjusted returns

Corey, playing devil’s advocate, confronts Victor with a common charge leveled against quants:

“you can’t eat sharp ratios”

Victor: Risk-adjusted returns are the ultimate thing that we care about I think investors should be trying to maximize risk-adjusted returns. And what is a risk-adjusted return? Well, a risk-adjusted return is the return that you expect to get or that you did get minus a cost for risk. And the cost for risk comes from the fact that typically we have a decreasing marginal utility of wealth or consumption that makes us risk-averse.

We could write down a formula in an idealized world for what risk-adjusted return is, but let’s just think about what it is qualitatively. I mean qualitatively what it is is that I come to you and you have your optimal portfolio of equities and safe assets and whatever, and I say to you all right, that’s it, I’m going to take away that portfolio from you and I’m going to give you in its place a 100% safe portfolio. But you can’t have the portfolio that you have right now that has all these risky assets in it. What is the lowest return that you would accept on a totally safe portfolio so that you would be not happier or less happy than you were with this risky portfolio that had this positive extra expected return?

Well, when you answer that question you’ve just answered the question of what is the risk-adjusted return on your portfolio. The risk-adjusted return could also be termed the certainty equivalent return of your portfolio. It’s basically what would be the 100% safe annuity that you could turn your wealth into without taking any more market risk. That is what you eat. That’s what you’re going to spend on your food. That’s the only thing that you have to eat — that’s the annuitized risk-adjusted stream of consumption that your wealth will support. And so that is what you eat with the appropriate inflation adjustment.

[Kris: There’s a question bandied around Twitter every now and then cutting to the heart of this — what would the TIPs yield need to be for you to plow all your savings into it and not concern yourself with investing anymore? In this interview, Corey and Victor frequently speak in terms of real returns and what sticks out to me is how much higher people think equity real returns are above TIPs but in reality that number over long periods is ~ 3% give or take 2%, maybe 3%. If the TIPs yield were 4% you could really live by the 4% rule without worrying. Except for taxes of course. But if we are going to talk about taxes, that’s the muscle movement that makes any realistic form of alpha look like 10lb dumbbell curls as far as impact. Reclassifying your entire income to a friendlier tax code is a better use of time than trying to outsmart markets. Unless your answer to a calendar with no meetings is afternoon delight with the solar credits section of the IRS code.]

Sharp ratio is not what you eat. Sharp ratio is we’re looking for portfolios that have the highest sharp ratio, but we’re not trying to maximize the sharp ratio of our portfolios. We’re trying to maximize the risk-adjusted return of our portfolio, and there’s going to be all kinds of cases where you’re going to prefer a lower sharp ratio portfolio to a higher one depending on what your constraints are and other things. But it’s the risk-adjusted return that you’re eating. You’re not eating the sharp ratio, and nobody’s claiming that you’re eating sharp ratio.

[Kris: In this next part, Victor doesn’t use the words “arithmetic” and “geometric”. That’s ok. He’s a gentleman, you buy someone a drink before you go there.]

What you’re not eating is you’re not eating expected return. If you start eating expected return, bad things happen. Let’s take a toy example where somebody tries to eat their expected return. Say you have your wealth, you’re retiring, and you look at your portfolio. You construct this portfolio, and you believe that this portfolio has a 5% real return after cost of living adjustments. So, you got this portfolio. The only problem is that you had to build this portfolio with a bunch of risky things, unfortunately, because maybe you were a pharmaceutical person. So, you’ve built it with different pharmaceutical companies, and this is a pretty risky portfolio, but it has a 5% average annual real return.

And let’s just say the volatility of this thing is much higher than the market volatility, that it’s got 30% annual volatility. You got $10 million, and you say, “Oh, well, the expected annual return of this portfolio is $500,000 a year. I’m going to spend $400,000 a year adjusted for inflation for the rest of my life, and I should be fine because my portfolio has a 5% average annual return. So, I’m just going to spend $400,000 — you know, that’s the 4% rule — I’m going to spend $400,000 adjusted for cost of living for the rest of my life, and everything should be fine.”

What’s your most likely amount of wealth in 25 years? Your most likely amount of wealth in 25 years is zero. You’re going to be wiped out. Why are you going to be wiped out? Because the up 30, down 30 is killing you. The first year you went up 35%, so you went up to $13.5 million. You spent $400,000. Beautiful. It’s all great. But the next year you went down 25%. You went down to 30%, but there’s the 5% expected return. The next year you go down 25%. Uh-oh. Now after you spent the $400,000, you have less wealth than you started off with. It’s volatility drag, and that volatility drag means that your median portfolio has gone to zero before 25 years. Once it starts going down, it really starts going down fast.

That’s what happens when you eat expected return. So, you have to eat risk-adjusted return. If you eat your expected return, it doesn’t end well. Maybe that’s where we get all these missing billionaires from — they were eating expected return. People get rich, and they think the expected returns are high, and then they try to eat a fraction of the expected return, but they’re not eating risk-adjusted return.

I will leave you related ideas to chew on.

Dr. Philip Maymin was recently interviewed on the CFA Institute podcast. You might recognize his name because he’s the author of book I constantly recommend, Financial Hacking.

About Philip:

Dr. Philip Maymin is Portfolio Manager and Director of Asset Allocation Strategies at Janus Henderson. He is also the Endowed Schramm Chair of Analytics and the MSBA Program Director at Fairfield Dolan, the CTO for Swipe.bet, and an instructor at Analytics.Bet.

In the past, he has been a portfolio manager at Long-Term Capital Management, Ellington Management Group, and his own hedge fund. He was Assistant Professor of Finance and Risk Engineering at the NYU School of Engineering, as well as an analytics consultant with several NBA teams and the Chief Analytics Officer for Vantage Sports.

Maymin co-founded the journals Algorithmic Finance and the Journal of Sports Analytics. Additionally, he was a policy scholar for a free market think tank, a Justice of the Peace, a Congressional candidate, and an award-winning journalist.

I recommend listening to it for several threads.

There’s a lot about AI. He’s very much in the weeds, so much so that it’s the topic of his next book.

Next, there’s some nice reinforcement of some of Victor’s ideas (maybe not an accident, Maymin was also at LTCM). Both Victor and Philip talk about dynamic vs static allocations. Victor’s firm helps you dynamically size your portfolio according to your risk own risk function as well as expected return (I call it “Kelly aware”). Phillip emphasizes tail risk management (not in a financial product sense necessarily, he’s speaking generally) because like many things in life, it’s a few moments that have most of the impact or if Wu-Tang Financial went quant — ”power law rules everything around me”.

For Maymin, the focus should be on risk management since the forces of competition make it hard to win big on alpha (alpha being defined as capturing excessive return without paying the risk cost) but those same forces do not keep not inhibit you from avoiding disaster which is a nice asymmetry for the individual.

That conclusion flows easily from his articulation of efficient markets hypothesis. His coverage of that idea, what it actually means, and its copious shortcomings are the best I’ve heard. I also remember him covering it in his book to a poetic degree and extending well beyond markets iirc.

Postscripts

• Philip suggests de-risking during higher vol periods because if you don’t then those periods will be a much higher proportion of your performance than the length of time that coincided with those periods which is another way of saying that a fixed position size is bigger part of a risk budget when times are volatile. That’s fairly obvious but the open question I have is whether higher volatility periods also coincide with higher returns. I presume they do in arithmetic terms but not geometric which is what matters so my unverified take is you want to be smaller when vol is high even if the expected returns are higher. My own investing process doesn’t switch gears hard with the vol level so this is an area I need to do some work on.
• I thought about including ideas from Mason Malmuth’s book Gambling Theory and Other Topics, because it emphasize that the most important concept in gambling is to follow a “non-self-weighting” strategy. Which is another way to say “vary your size with the edge”. Such an observation would be banal to this audience but he points to several common strategies that are counterexamples that people generally approve of. He’s a pretty incendiary character, arguing against diversification (he admits this is the largest area of pushback he receives) and claiming that “money management” is a stupid if not moot topic. He also gives the example of nuclear MAD as a self-weighting strategy and the brevity of the Gettysburg address as a non-self-weighting strategy. I gotta admit, reading it again 25 years later, I feel the dude’s a bit of crank. It was required reading at SIG but that must be in spite of the diversification thing. Jeff Yass has repeatedly emphasized that diversification is a free lunch.