October 05, 2026
The foundation of modern investing originated from an unexpected source: Scottish botanist Robert Brown, who observed in 1827 that tiny particles suspended in liquid move in a continuous, random jitter—a phenomenon later named Brownian motion.1 At the turn of the 20th century, French mathematician Louis Bachelier applied this insight to financial markets, proposing that stock price movements mirror this same random walk around their true intrinsic value. Because price changes respond to unpredictable news, Bachelier famously theorized that “the mathematical expectation of the speculator is zero”.2
Decades later, Nobel laureates Paul Samuelson and Eugene Fama formalized these ideas into the Efficient Market Hypothesis (EMH).3 Fama categorized efficiency into three distinct forms:
At its core, every stock price is a real-time tally of all investors’ expectations. Market efficiency does not mean prices are always perfectly "correct" or immune to hindsight mistakes. Rather, it means that because knowable facts are already reflected in the price, the next directional move is unpredictable. Consequently, paying high management fees to search for "mispriced" securities is often a costly effort in a game stacked against the picker.
A persistent myth in finance is that sharp market swings prove markets are irrational or broken. When unexpected news hits—such as sudden tariff announcements, geopolitical shifts, or oil price fluctuations—prices reprice rapidly.
Far from proving inefficiency, volatile movement demonstrates market efficiency in action. A functioning market should reprice immediately when surprising news arrives. If markets adjusted slowly, professional traders could easily exploit the lag for risk-free profits.
Michael Jensen’s landmark 1968 study of mutual funds confirmed this reality. After accounting for expenses and trading costs, professional fund managers consistently failed to beat a simple buy-and-hold strategy.4 They generated no net "alpha" (excess returns above risk-adjusted market performance).
Market efficiency is not static, and dynamics evolve over time. Practitioners like Cliff Asness, founder of AQR Capital Management, note that retail trading trends and headline noise can create occasional pockets of short-term inefficiency.5 Even so, the fundamental takeaway holds: after accounting for trading costs, taxes, and management fees, active stock picking consistently underperforms the market.6
Connecting efficiency to portfolio management requires understanding Harry Markowitz’s Modern Portfolio Theory and Burton Malkiel’s principles from “A Random Walk Down Wall Street”.7 Grounded in market efficiency, financial science divides risk into two categories:
Holding a concentrated portfolio of a few individual stocks exposes an investor to substantial company-specific risk without a higher expected return. Conversely, holding a broad index fund containing thousands of companies minimizes uncompensated risk, helping align the portfolio directly with broad economic growth.
To see market efficiency at work, consider two everyday scenarios where investors frequently misunderstand how prices move:
When a company reports record profits, investors are often surprised when its stock drops the same morning. Why? Because an efficient market already priced in high expectations based on public data. If profits rise 15% but the market expected 20%, the stock falls because the results fell short of what was already built into the price. You are unlikely to profit from headlines because the market adjusts instantaneously.8,9
| Company & Earnings Date | The "Good News" (Actual Results) |
The Priced-In Expectations | The Market's Reaction (Stock Drop) |
Why It Fell (The "Hidden" Catch) |
|---|---|---|---|---|
| Paychex (PAYX) September 23, 2026 |
- Revenue: $1.63B (5.8% YoY) - Adj. EPS: $1.34 (vs. $1.32 expected) |
Record full year profits were already priced in, leaving little margin for error. | Dropped ~9% following their Q4 earnings release. | The shortfall: Earnings beat expectations but concerns around future growth and the company’s forward outlook caused a rapid drop in price. |
| NVIDIA (NVDA) August 27, 2026 |
- Revenue: $96.2B (+106% YoY) - Adj. EPS: $2.22 (vs. $2.10 expected) |
Wall Street already expected stellar results, so beating estimates was merely the baseline. | Dropped 1.8% in immediate after-hours trading. | The shortfall: Despite doubling revenue, management guided that future gross margins would temporarily dip to 71%–72% due to rising memory chip costs. |
Political rhetoric and election anxiety frequently tempt investors to exit to cash during U.S. midterm cycles. Pre-election noise subdues performance (S&P 500 averages -0.32% in the six months prior). But once election results resolve legislative ambiguity, the market rapidly reprices asset values (+13.36% average gain in the six months post-election across 20 cycles from 1946–2022).10 Market timers exiting early frequently miss the rebound because the efficient market reprices risk far faster than individuals can react.
| Period Relative to Midterm Election | Average S&P 500 Return | Median Return | Positive Return Frequency |
|---|---|---|---|
| 6 Months Before Midterm | -0.32% | 2.00% | 11 of 20 cycles (55%) |
| 6 Months After Midterm | 13.36% | 14.48% | 19 of 20 cycles (95%) |
Our core investment philosophy directly translates these academic foundations into disciplined client portfolios. Because liquid public markets process new information rapidly, attempting to outperform through stock selection or tactical market timing imposes uncompensated risk with limited upside.
Understanding market efficiency fundamentally changes how investors could view headlines, political cycles, and short-term market swings. As Burton Malkiel, Eugene Fama, and decades of financial research have demonstrated, short-term price movements reflect the rapid processing of unexpected news rather than market failure.
Rather than treating volatility as a trigger to alter long-term strategy or pursue uncompensated risks through stock-picking, disciplined investors let market efficiency work in their favor. By maintaining low-cost indexed asset allocations, focusing on underlying business earnings, and remaining disciplined through every cycle, clients can position themselves for long-term financial success.
One Day In July LLC is an SEC-registered investment advisor. Registration does not imply a certain level of skill or training. One Day In July LLC does not guarantee actual returns or losses. The content of this newsletter is for educational purposes only and is not investment advice. Individual circumstances may vary.
Sources:
[1] EBSCO. Brownian Motion. https://www.ebsco.com/research-starters/history/brownian-motion/
[2] History of Data Science (June 2021). Louis Bachelier. https://www.historyofdatascience.com/louis-bachelier-an-underappreciated-revolutionary/
[3] EBSCO. Efficient-Market Hypothesis (EMH). https://www.ebsco.com/research-starters/social-sciences-and-humanities/efficient-market-hypothesis-emh/
[4] The Journal of Finance. Performance of Mutual Funds (May 1968). https://onlinelibrary.wiley.com/doi/full/10.1111/j.1540-6261.1968.tb00815.x
[5] AQR (November 2024). Journal of Portfolio Management. https://www.aqr.com/-/media/AQR/Documents/Perspectives/TheLessEfficientMarketHypothesis.pdf?sc_lang=en&hash=7630BDE83CDFC603F55633DDCCDA8560
[6] SPIVA (September 2026). https://www.spglobal.com/spdji/en/spiva/article/spiva-us/
[7] One Day In July (December 2025). Active vs. Passive Investment Management: A “Random Walk Down Wall Street.”. https://www.onedayinjuly.com/active-vs-passive-investment-management
[8] Paychex (September 2026). Earnings Release FY27 Q2. https://finance.yahoo.com/markets/stocks/articles/paychex-payx-beat-earnings-then-124531122.html
[9] NVIDIA (August 2026). Earnings Release FY27 Q2. https://finance.yahoo.com/markets/stocks/article/nvidia-tops-q2-expectations-offers-strong-q3-outlook-revenue-96-billion-112502189.html
[10] MacroTrends “S&P 500, Daily Since 1927” and S&P Global 2025 S&P 500 Performance Data. https://media.onedayinjuly.com/media/pdf/ODIJ_AllTime_Highs.pdf