Your Portfolio Intuition Is Poor

Summary and takeaways from Bridge Alternatives’ Portfolio Intuition (Link)


Intuition Test

Assume:

  • Your current portfolio has 5% return and 15% volatility for a Sharpe ratio of .33
  • You want to allocate 10% of your portfolio to a prospective asset
  • You want to maximize the Sharpe ratio of the resulting portfolio

Choose between A1 and A2

A1 A2
Return 4.00% 4.00%
Volatility 7.96% 46.04%
Correlation -.20 -.20

Unsurprisingly, most people prefer A1 since it has the same attributes as A2 with 1/6 the risk.

Now let’s run the numbers 

Expected return of the new portfolio is the same whether we choose A1 or A2:

Volatility of the new portfolio if we choose A1:

Sharpe ratio of original portfolio = .33

Sharpe ratio when we add A1 = .049/.13363 or .3667

The Sharpe ratio improved by about 10%

Now what is the Sharpe ratio if we add A2 instead of A1.

First, we must compute the volatility. Go ahead, plug and chug…

That’s right, the volatility is the same!

The volatility of the new portfolio is the same whether we add A1 or A2 which means the new combined portfolio has the same improvement to Sharpe whether we add A1 or A2. This is true despite A2 having a far worse Sharpe than A1! It is counterintuitive because portfolio math and the role of correlation is not intuitive.

To see why, look at the formula for portfolio volatility:

Let’s zoom in on the last 2 terms which come from adding the second asset:

Plot of change in overall portfolio volatility vs volatility of prospective asset (A1 or A2)

As we increase the asset’s risk, the first term grows exponentially, and the second term shrinks linearly (remember, the correlation is negative). It turns out that, at least temporarily, the shrinking effect from the negative correlation outweighs the exponential term.

There are 2 observations to note once you are done reeling from the bizarre impact of correlation.

  1. When adding a negatively correlated asset to a portfolio its risk must be incredibly high before it starts to degrade the Sharpe ratio of the final portfolio.
  2. Notice how, at least until we hit the vertex, if we move from left to right, representing an increase in risk, we’re actually reducing return. Put differently, if we added risk and didn’t reduce return we’d deliver more than a 10% improvement; risk has a positive payoff here, which is very cool. There is a significant range where we are reducing the prospective assets’ Sharpe and actually reducing the volatility of the new portfolio.

More Preference Tests

B1 B2 C1 C2 D1 D2
Return 10.54% 3.57% 9.33% 6.50% 6.43% -2.64%
Volatility 20.00% 20.00% 27.50% 12.50% 10.00% 40.00%
Correlation .80 -.20 .40 .40 .50 -.60

Most people agree:

  • B1 was slightly preferred to B2. For the same risk, B1 delivers much more return, though B2’s correlation is better.
  • C2 was preferred. It’s Sharpe is higher (about 0.52 versus about 0.34).
  • D1 was preferred to D2. D1’s Sharpe ratio is much higher. D2’s return is negative

The punchline, of course, is that every one of these assets improves the Sharpe of the portfolio by the same 10%. Your intuition would tell you would prefer a portfolio in the upper left green box since those assets have the best Sharpe (risk/reward), so it is probably uncomfortable to learn that the final portfolio is mathematically indifferent to all of these assets.

Correlation Is The Key

Here’s the same plot relating these equivalent portfolios by their respective correlations

As the correlation drops (corresponding to lines of “cooler” coloring), less return is required to deliver the same 10% improvement!

While Sharpe ratios are “mentally portable”, they are shockingly incomplete without being tied to correlation. To create a compact formula which links Sharpe ratios with correlation, it is helpful to view indifference curves.

Indifference Curves

RRR= Sharp Ratio of prospective asset
RRRb = Sharp Ratio of original portfolio

If Relative RRR > 1 the Sharpe of the prospective asset is greater than the Sharpe ratio of the original portfolio

The indifference curve represents an equivalent tradeoff between Sharpe ratio and correlation for various mixing weights. For example, the light green line assumes you will allocate 20% of the original portfolio to the prospective asset.

Observations

  • As the weight allocated to the asset increases (the lines move upward, from green to purple), the asset must be more performant in order to do no harm; it must be better relative to the portfolio. Put differently, as the role played by the asset increases, more is required of it, and that sounds about right.
  • A less performant asset, ie one with a worse Sharpe ratio than the original portfolio can compensate with low or negative correlations

Getting Practical

The investor’s natural question when evaluating a new asset or investment is:

“What is required from an asset (in terms of return, risk and correlation) in order to add value to my portfolio?”

With math that can be verified in the paper’s appendix we find a very handy identity:

This equality describes what’s required, in an absolute bare-minimum mathematical sense, of a prospective asset in order to do no harm. 

How to use it

For a given prospective Sharpe ratio, you very simply compute the maximum correlation the new asset can have to be accretive to the portfolio. For example, if the prospective asset has a Sharpe ratio of .10 and the original portfolio has a Sharp ratio of .40 then the prospective asset requires correlation no greater than .25 (ie .10/.40).

For a given correlation, you can compute the minimum required Sharpe ratio of the new asset to improve the portfolio. If the correlation is .80 and the original portfolio has a Sharpe ratio of .70 then the prospective asset must have a Sharpe ratio of at least .56 (ie .80 x .70).

Insights and Caveats

  • Correlation is best understood as a sort of performance hurdle. For assets exhibiting low correlation, less is required of their standalone performance (i.e. return over risk), all else equal.
  • Prospective assets with a Sharpe ratio greater than the original portfolio are always additive.
  • If you happen to find a truly zero-correlation asset it will be additive as long as it has positive returns. And as we saw with asset D2, a negative Sharpe Ratio asset can be additive if it has a negative correlation!
  • This cannot be used to somehow rank prospective assets. It can only serve as a binary filter: yes or no. This might feel like a real limitation. Sharpe ratios are absolutely rankable. They are measurements of the same unit (risk). But as we’ve shown in this paper, those rankings are not indicative of their true value within the context of a portfolio. Making decisions based only on return and risk is like ranking runners based on their times without asking how far they ran. It doesn’t make sense. If you take away one thing from this paper, this should be it!

My Own Conclusions

  • Correlations make portfolio math extremely unintuitive.
  • Negative and low correlations can make poor or losing stand-alone investments great additions to a portfolio. The implications for the diversifying power of low or negative-yielding assets are significant. Bonds, cash, commodities, gold.
  • Highly volatile assets with a negative correlation are tamed and even subtractive to the total risk of a portfolio.
  • While the importance of low or negatively correlated assets is well known it’s possible it remains underappreciated.

Further reading

Breaking The Market’s outstanding post Optimal Portfolios For Two Assets

You will learn:

  • How to mix assets by comparing their geometric returns.
  • Correlation’s effect on portfolio construction is not linear.
    • The closer correlations are to 1 the more they impact the recommended mix.
    • Negative correlations are deeply valuable in portfolio construction, adding to the long term return. Positive correlations are harmful, limiting the benefit of diversification.
    • The mixing range for the geometric returns is the combination of each asset’s variance, expanded or contracted based on the correlation between the two assets.
    • Negative correlation is wonderful.

Tool

You can save your own copy here

You can also play with the numbers directly below

The Income Inequality Myth?

Blind luck matches your unborn spirit to a physical baby body on Earth. The spirit didn’t audition for the part. Where you arrive? To whom? In what century? Blind, dumb luck.  But the second the baby opens her eyes her conditions and her genes interact. A unique trajectory unfolds.

Repeat this process billions of times across geography and history. Interject randomness, a magical insight or a stray bullet. Watch as outcomes diverge just as a narrow river flows down a hill, widens at the mouth, then spreads into a vast ocean.

The combinations are infinite and we can’t help but wonder what variables along the way cause which outcomes. Consider the life of an attractive woman. I’m ready to non-ironically play the violin for exceptionally pretty girls. Why? Because I can’t imagine how they must navigate all the distorting signals they receive, an excessive quota of creepers they’re going to attract (in addition to desirable mates), the baggage they might have incurred in the process, and the feedback loops that sweep them up. It’s easy to see how arrows of causality rarely point in one direction. Every blessing rides with its own curse.

How does this relate to income inequality? 

In order to study how people arrive at different outcomes you must follow the same people around and only then do you have a chance to disentangle the interaction of their qualities from their conditions. You must track the water as it travels from peak to basin. If you just sample the water in the starting and ending locations you have no chance of uncovering whys and hows.

The discourse on income inequality makes exactly this mistake. Everyone is familiar with a graph that looks something like this:

If you Google image search “income inequality” you will be bombarded with charts like this showing that the rich’s share of income has increased relative to the poor and median. While it’s true that the bucket of people considered “rich” now earn even more than the bucket called “poor” over time, these studies are all based on snapshots. And they make great kindling for outrage, attention, and political thrust. They sell like steroids at the Jersey Shore.

But it also masks the good news. Regrettably, good news doesn’t have a natural buyer.

Like the Kylie Jenner problem, that chart tells us absolutely nothing about one’s chance of climbing or falling through the ranks. That is the question we really care about. Russ Roberts writes:

What the snapshots show is that the rich today are richer than the rich of yesterday. If rich people are the same people as yesterday, then one’s class determines one’s fate. But if they are not the same people, the snapshots tell you that the dispersion of income has increased. That may or may not bother you, but it doesn’t necessarily mean that there is a distinct group called “the rich” who are capturing all the gains while the rest of us tread water.

A Much Rosier View

In his outstanding essay (link), which I’d go far as to call a PSA, Roberts shows the most dramatic claims by the pessimists that no one is making progress other than the rich are wrong.

1) Distortions in the snapshot methods conspire to make inequality look much worse than it really is.

You can’t use two snapshots to conclude that only the rich have made progress. It’s possible that everyone from the earlier snapshot has actually gotten richer and then been replaced by different people whose incomes will also rise. The people in the snapshots are not the same people. 

Immigration, divorce, and marriage rates all distort measure of progress. Roberts creates this easy-to-follow video showing how snapshot math can make it appear that the poor are doing worse even when everyone’s income doubles!

In this diagram captured from the video he creates a hypothetical to demonstrate how divorce rates impact snapshots.

Imagine 5 quintiles with 2 families in each bucket. Every person earns the same amount. 30 years later we take another snapshot and every individual’s income doubles but half the families divorce resulting in 5 more households. Now when you look at the quintiles it appears the top 2 quintiles benefitted at the expense of everyone else, yet in this example every person in society is benefitting equally from the stronger economy.

Immigration and marriage rates will reveal similar effects.

2) Longitudinal studies > snapshot studies

Roberts emphasizes the biggest problem with the pessimistic studies is that they rarely follow the same people to see how they do over time.

The data crunchers at DQYDJ, a leading site for income studies, make similar warning when viewing data that is not longitudinal:

You can not draw any conclusions about the performance of individual households from this data. Households in certain income brackets move up or down the income spectrum, but the data as presented doesn’t give any history or hint of movement. The only fair way to draw conclusions about the performance of last year’s households is with repeat surveys given to the same subjects.
3) The American dream is alive and well

Roberts reveals encouraging conclusions when you look at the results of longitudinal studies. Many are summarized in this video.

The pessimistic story based on comparing snapshots of the economy at two different points in time misses the underlying dynamism of the American economy… When you follow the same people over time, the largest gains over time often go to the poorest workers; the richest workers often make no progress.

4) What it actually looks like when “the ladder has been pulled up”

Nassim Taleb observes social mobility in the US vs Europe:

Static inequality is a snapshot view of inequality; it does not reflect what will happen to you in the course of your life

Consider that about ten percent of Americans will spend at least a year in the top one percent and more than half of all Americans will spend a year in the top ten percent. This is visibly not the same for the more static –but nominally more equal –Europe. For instance, only ten percent of the wealthiest five hundred American people or dynasties were so thirty years ago; more than sixty percent of those on the French list were heirs and a third of the richest Europeans were the richest centuries ago. In Florence, it was just revealed that things are really even worse: the same handful of families have kept the wealth for five centuries.

You do not create dynamic equality just by raising the level of those at the bottom, but rather by making the rich rotate –or by forcing people to incur the possibility of creating an opening.

The way to make society more equal is by forcing (through skin in the game) the rich to be subjected to the risk of exiting from the one percent

Or, more mathematically

Dynamic equality assumes Markov chains with no absorbing states

Our condition here is stronger than mere income mobility. Mobility means that someone can become rich. The no absorbing barrier condition means that someone who is rich should never be certain to stay rich.
Pulling from a NYTimes op-ed, this tweet maintains that economic rotation remains alive and well in the US.

Final Takeaway

As you get bombarded this election season with discussion of income inequality, remember, the snapshot view you are being fed is:

a) politically useful

and

b) doesn’t answer the question you care about: what are the prospects for me and my loved ones?

That the rich today are richer than the rich of yesterday is a very different finding than that the rich are getting all the gains. Too many economists have treated these as identical. The snapshot approach does not capture the impact of economic growth on people’s material well-being or provide evidence that the rich or the poor are static categories no one ever escapes. [While none] of these studies is decisive, [what they] show is that the economic growth of the last 30–40 years has been shared much more widely than is generally found in the cross-section studies that compare snapshots at two different times, following quintiles rather than people.

Extra credit question I have for the finance-minded

Are low real interest rates actually progressive by flattening the compounding effect of wealth. Asked differently: do low rates of return in markets make being rich less of an absorbing barrier?

Reading Recs From the Pros

This week I asked about 25 people from my network of portfolio managers, CIOs, and independent investors for the books which have most impacted how they think about risk-taking, investing, and trading. Here’s the Investing Pro’s Library (Link).

Besides books, the web is teeming with analysis and discussion in finance. It wasn’t always this way. 20 years ago when I started at Susquehanna in the options and ETF world there the best places to learn online were not blogs. They were forums. You could come across brilliant gamblers and traders on sites like 2+2 and Wilmott. Fast forward to 2019 and you can gain a substantial education in finance if you follow the right authors. The problem is no longer discovery but curation.

Here’s my short list of who you can’t miss today:

For breaking down high finance topics:

Matt Levine
Byrne Hobart

Quantitative Investing

Philosophical Economics
Econompic
Newfound
O’Shaughnessy Asset Management 
Alpha Architect
Convexity Maven

Susquehanna’s Raise Your Game

Valuation

Musings on Markets by Aswath Damodaran

General Investing

Of Dollars and Data
Movement Capital
Morgan Housel
Michael Mauboussin

History

Investor Amnesia
American Business History

A more extensive list of blogs to follow can be found on my site. Note that this is only a subset of all the feeds I think are worth subscribing to. If anybody is interested in that giant list, just reach out.

The Investing Pro’s Library

In my 20 years of option market-making, trading, and portfolio management I’ve been fortunate to meet many talented risk-takers. I took the opportunity to ask some of them what the most influential books or papers they have read in their careers.

I asked a cohort of 25 investors. They are CIO’s, PMs, and independent investors whose livelihood depend on the bets they take. Half of the respondents have had an options focus and more than 80% would be classified as quantitative. That word is a bit nebulous so my own clarification would be “non-bottoms-up”.

Let’s jump in.

The Most Influential

Topics: Risk/Reward

Nassim Taleb

  • Fooled By Randomness (Link)
  • Antifragile (Link)
  • The Black Swan (Link)

Peter Thiel: Zero to One (Link)

Aaron Brown: Red Blooded Risk (Link)

Peter L Bernstein: Against the Gods (Link)

Howard Marks

  • The Most Important Thing (Link)
  • Quarterly Memos (Link)

David Sklansky

  • Getting the Best of It (Link)
  • Theory of Poker (Link)

Topic: Process to Extract Edge

AQR research

  • Expected Returns by Antti Ilmanen (Link)

“The Bible”. “Don’t tell others”

  • Papers by Tobias Moskowitz (Link)

Turtle Trading

  • Way of the Turtle by Curtis M. Faith (Link)

“Drilled into me the importance of process, even if simple, before my career really ever began”

  • The Original Trading Rules pdf (Link)

Jack D Schwager

  • Market Wizards (Link)
  • The New Market Wizards (Link)

“Biggest takeaway: a lot of shit works, figure out what aligns with your personality”

Popular Themes

Topic: Numeracy and stats

Nate Silver: The Signal and the Noise (Link)

Darrell Huff: How To Lie With Statistics (Link)

Alex Reinhart: Statistics Done Wrong (Link)

John Allen Paulos: Innumeracy (Link)

Microeconomic Reasoning

Levitt and Dubner: Freakonomics (Link)

Tim Harford: The Undercover Economist (Link)

Value Investing

Munger/Buffet

  • Poor Charlie’s Almanac (Link)
  • Munger Speech at USC, 1994 (Link)
  • Buffet’s original partnership letters (Link)

Seth Klarman: Margin of Safety (Link)

Joel Greenblatt: The Little Book That Beats The Market (Link)

Competitive Markets

Michael Mauboussin

  • Research papers (Link)
  • The Success Equation (Link)

Jesse Livermore (pseudonym)

  • Diversification, Adaptation, and Stock Market Valuation (Link)

“This changed my thinking about how market participants behave and how their learning process can influence future prices”

  • The Single Greatest Predictor of Future Stock Market Returns (Link)

Risk

Benoit Mandelbrot: The Misbehavior of Markets (Link)

William Poundstone: Fortune’s Formula (Link)

Chris Cole: Research Papers (Link)

Parallels to Edge in Sports

Michael Lewis: Moneyball (Link)

Bill James: Win Shares (Link)

Dean Oliver: Basketball on Paper (Link)

History

Daniel Yergin: The Prize (Link)

“It’s a good exercise in rethinking everything-you-know based on a new model.”

Ron Chernow: The House of Morgan (Link)

Emile Zola: Money (Link)

Michael Lewis

  • The Big Short (Link)
  • Liar’s Poker (Link)

William Thorndike: The Outsiders (Link)

Jim Rogers: Investment Biker (Link)

Satyajit Das: Traders, Guns, and Money (Link)

Roger Lowenstein: When Genius Failed (Link)

Scott Patterson: The Quants (Link)

Steve Knopper: Appetite for Self-Destruction (Link)

Behavioral/Psychology

Thomas Gilovich: How We Know What Isn’t So (Link)

Lynne Twist: Soul of Money (Link)

Kahneman and Tversky: Thinking Fast and Slow (Link)

Steven Johnson: Mind Wide Open (Link)

Brett Steenbarger: The Psychology of Trading (Link)

Edward Russo: Decision Traps (Link)

General Investing

William J. Bernstein: The Four Pillars of Investing (Link)

“I’m confident a regular person could read this book, and nothing else, and outperform most professional advisors. It’s an all-in-one book that covers the history of markets, practical portfolio construction, and the emotional side of investing. Despite the wide scope, it doesn’t feel like a compromise in any category. By far my most suggested book.”

Harry Browne: Fail Safe Investing (Link)

Alexander Elder: Trading For A Living (Link)

Novel

Ayn Rand: The Fountainhead (Link)

Herman Melville: Moby Dick (Link)

“A good way meditation on how much you sacrifice if you’re goal-oriented, effective, have a high risk-tolerance, and need to work with a diverse set of stakeholders.”

Reference

Sheldon Natenburg: Option Volatility and Pricing (Link)

Mullis and Orloff: The Accounting Game (Link)

Nassim Taleb: Dynamic Hedging (Link)

Carol Alexander: Market Models (Link)

Peter Kennedy: A Guide to Econometrics (Link)

Lists from others whose work I follow:

Meb Faber (Link)

Dan Egan (Link)

Epsilon Theory Core Curriculum (Link)

Jason Collins’ Economics + Evolutionary Bio list (Link)

Taylor Pearson (Link)

Jason Zweig (Link) and his Top 5 (Link)

Famous Investors’ Reading Lists (Link)

Being A “Disagreeable” Investor

Having a disagreeable streak is an advantage in the investing world. If backed by stakeholders that are not beholden to conventional thinking (rare), you at least have a chance to stand apart from the herd. Some observations I’ve collected on contrarianism and investing.

  • Josh Wolfe on the Invest Like the Best Podcast: Not all contentious ideas turn out great, but all great ideas were contentious. The contentiousness is what allowed them to be underpriced. If everyone loves an idea from the outset than it’s probably overpriced or it’s obvious which increases the chance someone else has tried it and failed for a reason you have yet to discover.
  • Since 1968 [until recent history], Altria has generated average annual returns of more than 20%. No other stock has come close to matching that long-term performance, according to renowned stock market expert and Wharton professor Jeremy Siegel. Jared Dillian would not be surprised. His pet theory of ‘constraints investing’ advocates for owning names that others can’t be seen holding. This is not limited to sin stocks. Mall REITs, brick & mortar retail, and perhaps even the next round of unicorn IPOs are all businesses a constrained investor might not look at since the downside is losing money AND ridicule.
  • Unsexy businesses and careers can be quietly lucrative. My impulse is that people who own funeral homes and sanitation companies are doing pretty well. Small-cap private equity investor Brent Beshore is making a living out of this idea. His company Adventures’ website is a wealth of real business knowledge and he’s one of my favorite follows on fintwit.
  • A very simple math example to demonstrate the importance of divergence when filling out an NCAA bracket: Suppose 4 people are filling out a bracket and the favorite has a 72% chance of winning the tourney. If 3 people choose the favorite and I choose the second best team which has a 28% of winning the tourney (the numbers are silly but it won’t change the conclusion), then I have the most equity. How? If the favorite wins only 1 of the 3 people will claim the prize based upon the rest of their bracket, reducing their initial equity to 72/3 or 24% vs my 28%. Assuming the scoring system is designed to give massive weight to the final game (most brackets do) then the conclusion is apparent: if many people overbet the favorite you want to pick the likeliest teams to win who are relatively ignored! (h/t Steve for help with the example)
  • Many investors create risk management rules that say “if I lose X dollars, I will close the position”. This type of rule fails to acknowledge that the best opportunities often occur when an asset’s path has inflicted max pain. The merit of an investment on a going-forward basis has nothing to do with your p/l up until that point. Instead, consider a risk management framework that recognizes the benefits of contrarianism. Such a system would have its users establish max pain tolerance as an input into sizing the position in the first place. This may sound like a subtle difference but in practice it is not. Work it out yourself to see why.
  • The Allocators’s Dilemma

  • Activist investors are great examples of ‘disagreeable’ personalities. Being funny is a byproduct of their style. Market folk will recall the venom in Dan Loeb’s pen as well.
  • Short sellers are like the investigative journalists of corporate America, sniffing out frauds and accounting anomalies. One of my favorite interviews is with famous short-seller Marc Cohodes. His irreverent, iconoclast reputation is on full display. Being a short-seller requires an extremely ‘disagreeable’ personality streak since they are often battling against charming executives who are masterful story-tellers and fundraisers. Short selling is often condemned by its targets as opportunistic when in fact it serves an imperative truth-seeking function in the markets. For technical reasons I’ve described here, it is one of the most challenging strategies. When short-sellers are sounding off we should actually pay extra attention since the truth they uncover is a byproduct of one of the most masochistic paths to profit.
  • Examples of businesses featured on Guy Raz’s How I Built This born from contrarian thinking.
  • I have concerns about climate change but have reservations about the discourse around it. Let me explain. Dissenting with the scientific orthodoxy immediately gets you associated with the unwoke, the climate deniers, or Trump. In other words, you get camped with uncritical ideologues that are often associated with being stupid. This is a binary view of the world. One of Moontower’s recurring themes is the world is messy and grey. When something becomes that polarized, the ensuing lack of nuance raises an antenna. There’s no short-seller function in discussions like this. Truth-seeking is completely suppressed by signaling tribe allegiance. Honesty is compromised by incentives. Dissension risks academic grants, public ridicule, and maybe even friendships.

Lyall Taylor is an independent investor I read. He answers to nobody. He’s disagreeable. This gives him an edge in finding situations where the baby has been thrown out with the bathwater. His recent post on climate change discourse and ESG discourse is a great way to step through nuanced thinking. Agree or disagree with him, but don’t miss the lesson. Behind every conversation exists an intellectual meta backdrop. The odds of any conclusions need to be discounted by the incentives embedded in the evidence.

Here’s the post with my highlights.

A concept I call “Career TANSTAAFL”

There is a psychic premium to jobs that are sexy like chefs or jobs that are rewarding like teaching. So those types of careers will either be very competitive or pay poorly. If a job was lucrative and rewarding everyone would want to do it. Musicians are cool. No way they get to be well paid too. Same for actors, artists, models, athletes. Unless you think being the best basketball player in your state (that’s roughly how good you need to be to have a shot at the NBA) is a legit career plan, recognize that working on cool things means you will need to give up financial comfort.

A tangential, possibly cynical, musing: You can be paid in money. In prestige. In honor. In gratitude. How you weigh these things is personal. And the weights reveal your insecurities.

3 Economic Novels

Introductory Learning Recs

In the past year, I have read 3 relatively simple finance books while flying. They would make great gifts for teens or anyone interested in learning about some basic economic and business concepts. What all three have in common is they are narratives. They teach explicitly but in a fiction wrapper. And while it’s not Shakespeare, this style is underrepresented since I could see it being more resonant than textbook or essay style instruction because the lessons are weaved into the character’s stories. Here’s a link to my notes on:

  • The Rebel Allocator: This book’s device is a junior private equity analyst learning the lessons of capital allocation by a Buffet/Munger composite
  • Invisible Heart: An economic romance novel by leading economist and podcast host Russ Roberts.
  • The Accounting Game: This book has taught scores of people accounting for good reason. By following a boy’s lemonade stand for a summer you will learn how financial statements work to the pros and cons to various accounting strategies and regimes. It’s structured as a workbook so you get to practice constantly. It’s also just fun. Seriously.

For Investors or Inspiring Investors

Adam at Movement Capital is a reader whose business and blog I discovered this year. He’s always putting out content that is pound for pound some of the most educational, useful and concise reading. You can start with his most recent post Investment Switch Calculator. With funds slashing their fees, you may want to compute how long it will take you to break even on a transaction from a higher cost fund to a lower cost fund. This is not as straightforward as it initially appears and requires a tool like his. By walking through the model you are bound to learn something if this is not your expertise. His site is one of the first I’d send someone to if they were trying to learn the basics of portfolio construction and math. His approach is true to Einstein’s advice: “Everything should be made as simple as possible, but no simpler.”

ESG, Trump Tweet Trades, Volatility Follow Ups

The Money Angle from Weekly Moontower #32

  • You will recognize ESG as the latest battleground between corporate axiology, morality, and law.
    • Takeaways from Matt Levine compartmentalizing your role as a corporate citizen from your role as a person. He channels realism and illuminates the downsides of mission driven companies. My notes here.
    • Cullen Roche’s pragmatic view on ESG investing. His pragmatic concerns are drawn from matters of axiology, morality, and law.
    • Aswath Damodaran’s explanation of shareholder vs stakeholder views of the corporation.
  • The article dismantling the conspiracy theories of friends of Trump trading ahead of his announcements. At the end of the article I noticed one of the contributors as an anonymous blogger/trader KidDynamite. I have been following him for nearly a decade. His work is top-notch especially his accounting level forensics to debunk claims that precious metals prices are manipulated.
  • Follow-ups from last week’s discussion about volatility’s toll on compounded returns:
    • My notes on a fun paper about how inept even educated people are about sizing wagers and how you can adapt the Kelly criterion for binary type bets.
    • A walkthrough of my simulation of investing in a 2 coin portfolio including the impact of rebalance and the influence of volatility on mean vs geometric returns.
    • An observation: A friend with some rental properties mentioned he does not aggressively raise his tenants’ rent. This incents the tenants to take good care of the place since they don’t want to lose the apartment. That means lower maintenance costs which is a second-order effect that offsets the first-order effect of keeping the headline rent a bit low. Between that and a very low vacancy rate, the returns of the rental properties are less volatile. And we all learned what volatility does to portfolios. An especially interesting bit to keep in mind since rental properties are usually levered.