Solved Problems

№2 in the series

A Wide & Deep Pond

a field survey of diversification · drewbreyer.com

The mathematical expectation of the speculator is zero.

L’espérance mathématique du spéculateur est nulle.

Louis Bachelier, Théorie de la Spéculation (1900), trans. Boness1

Abstract

We consider an investor placing $100,000 for 30 years in a diversified market portfolio returning 7.0% with 16% volatility, against a single ordinary stock granted — charitably — the same expected return at 45% volatility. The two bets have identical expected terminal wealth: $532,803 in today’s dollars. They are not the same bet. The pond delivers $362,909 to its median holder; the single stock delivers $25,550 to its median holder and beats the pond in only 12.5% of futures. Diversification does not shrink the prize; it changes who receives it — from a lucky few to nearly everyone. We survey a century of measurement showing that this arithmetic is the solved core of retirement investing, and we price what a gambling habit costs if, knowing this, you keep one anyway.

Median outcome, the pond
$362,909
today’s dollars
6.0 years of your spending
Median outcome, one stock
$25,550
today’s dollars
0.4 years of your spending
Odds one stock beats the pond
12.5%
a coin flip is the ceiling
Fee-equivalent of a refilled sleeve
1.33%
per year, a 5% habit at the current game

A note on posture. In an investment club, the contrarian position is not a hotter stock pick. Everyone in the room has one of those. The contrarian position is that the game was solved between 1900 and 1974 — priced by Bachelier, proportioned by Markowitz, indexed by Bogle — and that everything since has been measurement confirming it. What follows is that measurement. The author’s zeal is spent not on finding the winning stock but on refusing, with citations, to pretend anyone reliably can.

IMEASURED

The shape of the pond

Begin with what the pond actually contains. The market’s long-run return is not a property of its typical fish; it is carried by a thin tail of extraordinary ones. Miss the tail and you did not fish a smaller pond — you fished a different one, with different odds.

Fig. 1

Most stocks are not the market. A handful of extraordinary companies carry the whole pond; everything else, on net, could have been T-bills.

The wealth field. Each dot is 0.1% of all US-listed firms since 1926; 43 account for all net wealth creation6, 574 trailed T-bills over their lifetime. The market’s return is a tail event. MEASURED
Beat one-month T-bills over their lifetime642.6%
Median lifetime buy-and-hold return6−2.29%
Median listing life690 mo (7.5 yr)
Suffered an effectively complete loss611.83%
Reduced aggregate shareholder wealth (1926–2022)758.6%
Firms for half of all net wealth (2016 → 2022 → 2025)6,7,890 → 72 → 46
Top wealth creators, 1926–2022 ($B)9,7: Apple 2.7T · Microsoft 2.1T · ExxonMobil 1.2T · Alphabet 1.0T · Amazon 764B · Berkshire Hathaway 704B · Johnson & Johnson 661B · Walmart 629B · Chevron 583B · Procter & Gamble 581B
Anything that is huge, profitable, famous, or influential is the result of a tail event.
Morgan Housel, “Tails, You Win,” The Psychology of Money (2020)48

IIMODELED

Width

The model below concedes everything a stock picker could ask: the stock is average, β = 1, and it is paid the market’s full expected return. Nothing is taken away except the other stocks. What remains is the arithmetic of what you gave up.

Assumptions console — governs every modeled figure
Market world

The calibration concession. The modeled stock is granted the market’s full arithmetic mean — 8.4% at these settings. Idiosyncratic risk is taken but not paid (CAPM). This is charity, not cynicism: the measured record in §I says the typical stock does worse than this model assumes.

Fig. 2

Ten stocks feel diversified. The wobble says otherwise.

The price of narrowness. Volatility diversifies fast — the next figure states why that is not enough. MODELED
Fig. 3

Adding stocks gets you back to a coin flip against the market — never past it.

Odds of trailing the pond. Width buys you back the coin flip; nothing buys you past it. MODELED
Diversification is both observed and sensible; a rule of behavior which does not imply the superiority of diversification must be rejected both as a hypothesis and as a maxim.
Harry Markowitz, “Portfolio Selection,” Journal of Finance (1952)2

The celebrated aphorism — that diversification is “the only free lunch in investing” — is attributed to Markowitz everywhere and sourced nowhere; we checked. The 1952 sentence above is what he actually wrote, and it is better.

Diversification is your buddy.
attributed to Merton Miller by his colleagues Eugene Fama and David Booth — attributed2

IIIMODELED

Depth

Time is usually sold as the retail investor’s edge. It is — but only in wide water. Concentrated risk does not wash out with the years; it compounds in. The two curves below are the same investor, the same horizon, and the same expected return.

Fig. 4

Both bets promise the same average. Only one of them usually keeps the promise.

Two ponds, one expected return. Same mean path, diverging medians — pond $0 vs one stock $0 to the median holder. MODELED
Expected (mean) terminal — both
$532,803
identical for pond and stock, by construction
8.9 years of your spending
Median terminal, the pond
$362,909
what the typical diversified holder gets
6.0 years of your spending
Median terminal, one stock
$25,550
what the typical concentrated holder gets
0.4 years of your spending
Fig. 5

Given time, a wide portfolio almost never loses to cash. A single stock usually does.

What time does to risk. Probability of ending below the cash (3%) floor — the Bessembinder benchmark when set to cash. Time heals wide risk and deepens narrow risk. MODELED
In the short-run, the market is a voting machine — reflecting a voter-registration test that requires only money, not intelligence or emotional stability — but in the long-run, the market is a weighing machine.
Warren Buffett, 1993 Berkshire Hathaway letter — his rendering of Benjamin Graham’s 1934 voting-machine passage41,42

IVMEASURED

The professionals have already tried

Perhaps skill can beat the arithmetic. The most-resourced investors on earth have run that experiment continuously since 1976, in public, with scorekeeping. The scores follow.

Fig. 6

The people paid most to beat the market mostly don't — and the longer the race, the fewer survive.

The professionals’ record. Share of active large-cap funds underperforming the S&P 500 by horizon, SPIVA Mid-Year 202513. The gray rule is the coin flip. MEASURED

Persistence is worse than chance: of large-cap funds in the top quartile as of December 2021, 0% remained top-quartile through December 202515. Skill, properly measured, rarely clears its own costs.

The bet — index fund vs five funds-of-hedge-funds, 2008–201717
+125.8%
the index fund (8.5%/yr)
+36.3%
the five funds, average (21.7% · 42.3% · 87.7% · 2.8% · 27%)

The five funds-of-funds got off to a fast start, each beating the index fund in 2008. Then the roof fell in.

Properly measured, the average actively managed dollar must underperform the average passively managed dollar, net of costs.
William F. Sharpe, “The Arithmetic of Active Management,” Financial Analysts Journal (1991)4
[A] major industry appears to be built largely on an illusion of skill.
Daniel Kahneman, Thinking, Fast and Slow (2011), ch. 2045

VMEASURED + MODELED

The casino annex

None of this abolishes the itch. A fraction of readers — the author declines to estimate it from the room — will speculate regardless, and a survey that pretends otherwise is decoration. So we price the itch instead. Below: each game, its sum after costs, its measured retail result, and the rules under which a small sleeve does bounded damage.

The gameSum after costsThe measured resultIf you insist
The pond (broad index)Positive — you are paid to waitthe equity premium6this is the savings, not the sleeve
One ordinary stockPositive expectation, lottery-shapedmost lifetime-trail T-bills; ~4 in 10 suffer a catastrophic, unrecovered decline6,10the cheapest itch to scratch — same expectation, wilder ride; sleeve it
Active fundsPositive minus ~1%/yrmost trail the pond at every horizon; winners don’t persist13,15you already met this arithmetic at /fees
Retail optionsZero-sum minus spreads, fees, and the counterparty knowing moremeasured retail losses at every study24,28the default sleeve preset above, charitably
CryptoNo cash flows; a monetary-premium wagermost retail buyers entered and lost; drawdowns >75% are routine30,31if held at all: lottery-ticket sizing, one ticket
Prediction marketsZero-sum minus the fee — but priced by informationinformation value is real; retail P&L unstudied — absence of evidence, noted35,37house rule 5
ARKK −81.0%11GameStop −91.6%11Bitcoin −77.0%31

Myth check, both directions: roughly a third of option contracts expire worthless — not the 90% of lore29. The retail losses above come from spreads and prices paid, not from expiry trivia. This survey’s case does not need the myth. And on the other side: 75% of concentrated stockholders would have benefited from some diversification10.

When the capital development of a country becomes a by-product of the activities of a casino, the job is likely to be ill-done.
John Maynard Keynes, The General Theory (1936), ch. 1243
The sleeve — price the itch
Game
Policy
Fig. 7

A small, capped gambling budget costs surprisingly little. A refilled habit compounds like a fee.

The price of the sleeve. A refilled 5% habit at −20%/yr expectation prices as a 1.33%/yr fee — dearer than every fund your club has ever argued about. MODELED
Fee-equivalent
1.33%
per year, refilled — closed form
Median cost of the sleeve
$0
vs 100% pond, today’s dollars
Mean cost of the sleeve
$173,994
expected shortfall — closed form

House rules for a sleeve

  1. 1Size it once: at most 5% of investable assets, in a separate account39.
  2. 2If the game has negative expectation, fund it once and let the ticket ride; refilling a losing game converts a ticket into a subscription (the arithmetic above). If you believe your game has positive expectation, harvest winnings annually back into the pond — belief deserves an audit.
  3. 3Winnings above the cap flow to the pond, never to bigger bets.
  4. 4Keep score against the pond, in writing, after costs. Most members discover their edge is a fee.
  5. 5Prediction markets only: your edge must exceed the fee plus your own overconfidence; this is the one counter where domain knowledge plausibly prices in your favor, and it is still entertainment — size it like theater tickets, not like savings.
I recommend you have a funny money account of no more than 5% of your portfolio … I’d be astonished if at least 95% of those funny money accounts don’t do worse.
John C. Bogle, MarketWatch interview (2014)39

Readers of the companion survey argued at length over a fund charging 0.66%. The refilled sleeve above is that argument, twenty times over. → The Arithmetic of Fees

Speculation is an effort, probably unsuccessful, to turn a little money into a lot. Investment is an effort, which should be successful, to prevent a lot of money from becoming a little.
Fred Schwed, Where Are the Customers’ Yachts? (1940)44

VI

The solved game

Acceptance, written out, is three sentences long.

  1. 1Own everything — a global, capitalization-weighted index at a few basis points.
  2. 2Hold enough safe assets, matched to when you need the money, that no market can force you to sell.
  3. 3Feed the pond on a schedule; when you have won, stop playing.

What this survey does not claim

Not that markets are perfectly efficient — anomalies exist, factor premia exist, and a handful of investors have beaten the arithmetic for decades. Not that prices are magic: they are informative precisely because zealots spend careers competing to correct them (Grossman & Stiglitz’s paradox5). The claim is narrower and stronger: for a saver, net of costs and taxes, over decades, the diversified default has dominated every implementable alternative — and the reader who indexes free-rides on the very competition they decline to join. It is also, the author concedes, more fun to be right about this at a party than profitable to argue it further.

My advice to the trustee could not be more simple: Put 10% of the cash in short-term government bonds and 90% in a very low-cost S&P 500 index fund. (I suggest Vanguard’s.) I believe the trust’s long-term results from this policy will be superior to those attained by most investors — whether pension funds, institutions or individuals — who employ high-fee managers.
Warren Buffett, 2013 Berkshire Hathaway letter (the instruction in his own will)40
When you’ve won the game, why keep playing it?
William Bernstein, Money interview (2012)47

The companion survey prices the other tax on wealth — fees. → The Arithmetic of Fees

Notes on method
The model

Lump sum, annual steps. Every asset is lognormal in annual log-returns r = m + s·z, gross factor e^r. Geometric inputs (market, cash) map as m = ln(1+g); arithmetic inputs (sleeve games) as m = ln(1+E) − s²/2. The single stock is granted the market’s arithmetic mean (β = 1): its idiosyncratic risk is taken but not paid. The market shock z_mkt is shared between pond and stock — the common-random-numbers identity that makes every comparison ceteris paribus.

Calibration at your settings

m_m = 0.067659 · A_m = 8.38% · m_s = -0.020791 · σ_i = 42.1%

Closed-form cross-checks (live)
  • Mean multiple, both assets: 11.2×
  • Median multiple — pond 7.6×, one stock 0.54×
  • P(one stock beats the pond): 12.5%
  • Sleeve mean — refilled 7.5×, one ticket 10.6×
  • Fee-equivalent of the refilled sleeve: 1.33% per year

The Monte Carlo figures reproduce these within sampling error; if a simulated value drifts from the closed form, the closed form is right.

The random numbers

A mulberry32 stream feeds a Box–Muller pair with caching (cosine first, sine held for the next draw). Each base path draws its full shock set in a fixed order, then runs forward and sign-flipped — antithetic variates. The width engine uses 8000 effective paths; comparisons share the market shock, so differences are pure composition.

seed 42
What the model is not

It prices composition, not accumulation — contributions, decumulation, and taxes are out of scope (contributions are the companion /fees paper’s subject). And it is kinder to concentration than the measured record: the stock is paid the market’s full expected return, which §I shows the typical stock does not earn. Where the model and reality disagree, reality is worse for the concentrated investor.

References

  1. 1.Bachelier, L. (1900). “Théorie de la spéculation.” Annales scientifiques de l’École Normale Supérieure 3(17), 21–86. link
  2. 2.Markowitz, H. (1952). “Portfolio Selection.” Journal of Finance 7(1), 77–91. link
  3. 3.Sharpe, W. F. (1964). “Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk.” Journal of Finance 19(3), 425–442.
  4. 4.Sharpe, W. F. (1991). “The Arithmetic of Active Management.” Financial Analysts Journal 47(1), 7–9. link
  5. 5.Grossman, S. J. & Stiglitz, J. E. (1980). “On the Impossibility of Informationally Efficient Markets.” American Economic Review 70(3), 393–408.
  6. 6.Bessembinder, H. (2018). “Do stocks outperform Treasury bills?” Journal of Financial Economics 129(3), 440–457. link
  7. 7.Bessembinder, H. (2023). “Shareholder Wealth Enhancement, 1926 to 2022.” SSRN 4448099.
  8. 8.Bessembinder, H. (2026). “One Hundred Years in the U.S. Stock Markets.” SSRN 6438198.(working paper)
  9. 9.Visual Capitalist (2023). “The 25 Best Stocks by Shareholder Wealth Creation (1926–2022).” link
  10. 10.Cembalest, M. (2014). “The Agony and the Ecstasy: The Risks and Rewards of a Concentrated Stock Position.” J.P. Morgan Eye on the Market, special edition.
  11. 11.Cembalest, M. (2021; Part IV 2024). “The Agony and the Ecstasy,” updated editions. J.P. Morgan.
  12. 12.Campbell, J. Y., Lettau, M., Malkiel, B. G. & Xu, Y. (2001). “Have Individual Stocks Become More Volatile?” Journal of Finance 56(1), 1–43 (NBER WP 7590, Table 6).
  13. 13.S&P Dow Jones Indices (2025). SPIVA U.S. Scorecard, Mid-Year 2025 (data as of June 30, 2025). link
  14. 14.S&P Dow Jones Indices (2026). SPIVA U.S. Scorecard, Year-End 2025. link
  15. 15.S&P Dow Jones Indices (2026). U.S. Persistence Scorecard, Year-End 2025. link
  16. 16.Fama, E. F. & French, K. R. (2010). “Luck versus Skill in the Cross-Section of Mutual Fund Returns.” Journal of Finance 65(5), 1915–1947.
  17. 17.Buffett, W. E. (2018). Berkshire Hathaway 2017 Shareholder Letter, “The Bet is Over.” link
  18. 18.Ibbotson SBBI (2026). “Stocks, Bonds, Bills, and Inflation 1926–2025,” via New York Life Investment Management.
  19. 19.Dimson, E., Marsh, P. & Staunton, M. (2025). UBS Global Investment Returns Yearbook 2025 (1900–2024). link
  20. 20.Dimson, E., Marsh, P. & Staunton, M. (2026). UBS Global Investment Returns Yearbook 2026, public summary (1900–2025).
  21. 21.Barber, B. M. & Odean, T. (2000). “Trading Is Hazardous to Your Wealth.” Journal of Finance 55(2), 773–806.
  22. 22.Barber, B. M., Lee, Y.-T., Liu, Y.-J. & Odean, T. (2009). “Just How Much Do Individual Investors Lose by Trading?” Review of Financial Studies 22(2), 609–632.
  23. 23.Barber, B. M., Lee, Y.-T., Liu, Y.-J. & Odean, T. (2014). “The Cross-Section of Speculator Skill: Evidence from Day Trading.” Journal of Financial Markets 18, 1–24.
  24. 24.Bryzgalova, S., Pavlova, A. & Sikorskaya, T. (2023). “Retail Trading in Options and the Rise of the Big Three Wholesalers.” Journal of Finance 78(6). link
  25. 25.Amaya, D., García-Ares, P., Pearson, N. & Vásquez, A. (2025). “New Evidence on the Performance of Customer Options Trades.” Working paper, Cboe Options Institute data.(working paper)
  26. 26.de Silva, T., So, E. & Smith, K. (2026). “Losing Is Optional: Retail Option Trading and Expected Announcement Volatility.” Review of Finance 30(2), 489–535. link
  27. 27.Beckmeyer, H., Branger, N. & Gayda, L. (2023). “Retail Traders Love 0DTE Options… But Should They?” SSRN 4404704.(working paper)
  28. 28.Bauer, R., Cosemans, M. & Eichholtz, P. (2009). “Option trading and individual investor performance.” Journal of Banking & Finance 33(4), 731–746.
  29. 29.McMillan, L. (2001). “How Many Options Actually Expire Worthless?” Technical Analysis of Stocks & Commodities (Jan 2001); with converging industry statistics.
  30. 30.Auer, R., Cornelli, G., Doerr, S., Frost, J. & Gambacorta, L. (2022, rev. 2023). “Crypto trading and Bitcoin prices.” BIS Working Paper No. 1049. link
  31. 31.Cornelli, G., Doerr, S., Frost, J. & Gambacorta, L. (2023). “Crypto shocks and retail losses.” BIS Bulletin No. 69. link
  32. 32.Liu, J., Makarov, I. & Schoar, A. (2023). “Anatomy of a Run: The Terra Luna Crash.” NBER Working Paper 31160. link
  33. 33.CFTC (2022). Press Release 8638-22 (FTX: loss of over $8 billion in customer deposits). link
  34. 34.Kumar, A. (2009). “Who Gambles in the Stock Market?” Journal of Finance 64(4), 1889–1933.
  35. 35.Wolfers, J. & Zitzewitz, E. (2004). “Prediction Markets.” Journal of Economic Perspectives 18(2), 107–126.
  36. 36.Kalshi, Fee Schedule (2025–26); Polymarket, Trading Fees documentation (2026). Both CFTC-regulated venues. link
  37. 37.Akey, P., Grégoire, V., Harvie, B. & Martineau, C. (2025). “Who Wins and Who Loses in Prediction Markets? Evidence from Polymarket.” SSRN 6443103.(working paper)
  38. 38.Shefrin, H. & Statman, M. (2000). “Behavioral Portfolio Theory.” Journal of Financial and Quantitative Analysis 35(2), 127–151.
  39. 39.Bogle, J. C. (2014). MarketWatch interview (the “funny money” 5% account).
  40. 40.Buffett, W. E. (2014). Berkshire Hathaway 2013 Shareholder Letter, p. 20. link
  41. 41.Buffett, W. E. (1994). Berkshire Hathaway 1993 Shareholder Letter (the voting-machine / weighing-machine rendering). link
  42. 42.Graham, B. & Dodd, D. (1934). Security Analysis, p. 23 (the original voting-machine passage). McGraw-Hill.
  43. 43.Keynes, J. M. (1936). The General Theory of Employment, Interest and Money, ch. 12 §VI. Macmillan.
  44. 44.Schwed, F. (1940). Where Are the Customers’ Yachts? Simon & Schuster.
  45. 45.Kahneman, D. (2011). Thinking, Fast and Slow, ch. 20. Farrar, Straus and Giroux.
  46. 46.Ellis, C. D. (1975). “The Loser’s Game.” Financial Analysts Journal 31(4), 19–26.
  47. 47.Bernstein, W. (2012). “The worst retirement investing mistake.” Money interview, Sept 4, 2012.
  48. 48.Housel, M. (2020). The Psychology of Money, ch. 6 “Tails, You Win.” Harriman House. link
  49. 49.Tully, S. (1998). “How the Really Smart Money Invests.” Fortune, July 6, 1998.
  50. 50.Bogle, J. C. (2007). The Little Book of Common Sense Investing. Wiley.
  51. 51.Samuelson, P. A. (2005). Address to the Boston Society of Security Analysts, Nov 15, 2005; as printed in Bogle, The Clash of the Cultures (2012).
  52. 52.Bernstein, P. L. (1992). Capital Ideas. Free Press.
  53. 53.Graham, B. (1973). The Intelligent Investor, 4th rev. ed., Introduction. Harper & Row.

Continue the series →

3 The Yield Illusion

Dividends, covered-call income, and leveraged ETFs: total return relabeled, minus friction.

Solved Problems in Personal Finance

1 The Arithmetic of Fees·2 A Wide & Deep Pond·3 The Yield Illusion

Support this work

bitcoin accepted with thanks

bc1qsk0m…2ujww