The Research Behind the Book

Losses are felt approximately 2.25 times more intensely than equivalent gains. The most important behavioural finding in finance — it explains why investors hold losers and sell winners, why panic selling happens, and why risk questionnaires fail.

Investors who check portfolios daily experience more felt losses (daily returns are negative ~46% of the time vs ~25% annually). The more frequently you look, the more pain you feel, and the more likely you are to make destructive decisions.

Meta-analysis of 94 studies (8,000+ participants): if-then plans improved goal achievement with a medium-to-large effect size (d = 0.65). If-then planning creates "strategic automaticity" — bypassing conscious deliberation under stress. The academic foundation for pre-commitment in investing.

Pre-committed savings rate climbed from 3.5% to 13.6% over 40 months. 78% of employees joined, 80% stayed through the fourth pay raise. Proof that pre-commitment works in financial behaviour — people who bind their future selves outperform those who rely on willpower.

In calm states, people systematically underestimate how fear will override their intentions during volatile periods. The gap is systematic and predictable. This is why risk questionnaires filled out in a comfortable office fail to predict behaviour during a market crash.

17 male traders at a City of London prop firm. Cortisol rose up to 400–500% above baseline during volatile periods (R² = 0.47 between cortisol and volatility). Morning testosterone predicted daily profitability (p = 0.015). Your body trades whether you want it to or not.

Simulation study in the Journal of Financial Planning. Investor panic — selling during drawdowns, re-entering late — cost 8–15% of total wealth over a 10-year period. The gap between strategy returns and investor returns is almost entirely behavioural.

Published in PLOS ONE. Overconfidence in financial knowledge increased the likelihood of partial panic selling by 1.2 percentage points. The more confident you are in your knowledge, the more likely you are to act impulsively when that knowledge is tested.

Identified the tendency for investors to sell winning positions too early and hold losing positions too long. Predicted from prospect theory — realising a gain feels good, realising a loss feels terrible. The most documented bias in investment behaviour.

10,000 US brokerage accounts. Investors were ~50% more likely to sell a winner than a loser. The stocks they sold outperformed the stocks they held by 3.4 percentage points over the following 12 months. They were literally selling their best positions.

The largest dataset in the disposition effect literature: 1 billion+ trades from ~4 million investors. 84% showed the effect. Investors were roughly 2x more likely to sell winners than losers. No capital gains tax in Taiwan eliminates the tax-deferral explanation.

Australian study using ASX IPO and index stocks (1995–2000). Pervasive across all investor classes: retail, institutional, insurance, superannuation, foreign, and government. Not just a retail phenomenon.

46,289 retail accounts on the ASX. Investors using conditional orders (pre-set stop-losses, limit sells) exhibited the disposition effect at roughly half the rate of manual, at-market order users. Automation helps override the bias.

Australian investors underperformed their own funds by –0.40 percentage points per annum. Globally, the gap averages –1.1 to –1.2 pp/yr. Australian investors had a positive gap of +0.65 pp during 2010–2018, but it turned negative after COVID and the 2022–23 rate shock.

Average Vanguard fund investor earns 1–2% p.a. less than the fund itself returns — entirely from behaviour (buying after runs, selling after drops). But during COVID (Feb–May 2020), fewer than 0.5% of Vanguard investors abandoned equities entirely. 99.5% held or rebalanced into the decline.

Average equity fund investor underperforms their fund by 2–4% per year over long periods, almost entirely from buying high and selling low. The longest-running study of the behaviour gap.

In any given year, 60–70% of active Australian fund managers underperform their benchmark. Over 5 years: ~80%. Over 15 years: 85%+. The pattern holds across virtually every market globally. The single most cited statistic in the passive investing literature.

The ASX has never delivered a negative return over any rolling 20-year period in more than a century of data. Time is the passive investor's ultimate edge — but only if the holding period is long enough.

Grew the Yale Endowment from $1.3B to $42.3B — annualised 13.7% over 35 years. The core-satellite approach used in the book's diagnostic is adapted from his endowment model. The IPS was the foundation of everything.

Delivered its strongest relative performance in 25+ years, driven by banks and margin recovery, while the US stayed growth-led on AI enthusiasm. Value mean-reverts — the longer it underperforms, the stronger the eventual recovery.

Value underperformed Growth by ~28 percentage points across 2017–2019 as momentum dominated. Then clawed back 20 ppts in 2022 alone when rates rose and growth multiples compressed. The cycle always turns — the question is whether you're still there when it does.

Tested both premia across 8 asset classes in 40+ countries. Value alone Sharpe 0.37, momentum alone 0.51, but the 50/50 combination: Sharpe ratio of 0.80. The negative correlation (–0.50 to –0.60) means when one struggles, the other tends to work. The strongest empirical case for method pluralism.

Tested moving-average rules on the Dow from 1897 to 1986 (90 years). Buy signals consistently generated higher returns with lower volatility than sell signals. One of the first rigorous studies to give technical analysis academic credibility.

67 global markets from 1880 to 2016. Time-series momentum delivered positive average returns in every single decade. Crisis alpha in 8 of 10 worst 60/40 drawdowns. Adding 20% trend-following to a 60/40 portfolio improved Sharpe from 0.38 to 0.54 and reduced max drawdown from 62.3% to 50.2%.

Mathematical proof in the Journal of Financial Economics that moving-average rules can function as an optimal allocation overlay when returns are even slightly predictable. The theoretical justification for combining technical signals with fundamental analysis.

By 2015, HFT accounted for 27% of ASX 200 turnover and 47% of all orders. ~50% of resting orders at best bid/offer were algorithmic. By 2018: "Automated trading dominates the Australian equity markets." Industry estimates: 30–40% of all ASX volume is algorithmic. Technical levels are real because trillions of dollars are programmed to trade them.

The largest study of individual trading ever conducted. 87% of day traders lost money in the average year. Less than 1% were consistently profitable. The small profitable subset were experienced, willing to short-sell, and concentrated in familiar stocks. The data nobody in the trading education industry wants you to see.

66,465 US households. The most active traders earned 11.4% p.a. vs 17.9% for the broader index — a 6.5 percentage point gap, primarily from costs. The more you trade, the worse you do.

US equities monthly, Jan 1950 – Dec 2004. In trending and regime-switching environments, stop-loss rules added 50–100 basis points per month (6–12 ppts annually) to buy-and-hold during stop-out periods. Systematic sells outperform emotional sells.

88 years of US data (Jan 1926 – Dec 2013). A 10% stop-loss rule more than doubled risk-adjusted return. Worst monthly drawdown reduced from nearly 50% to just over 11%. The strongest quantitative case for systematic sell discipline.

Multi-factor approach delivered positive real returns across all inflationary regimes, averaging ~2.3 percentage points above the broad market over 150 years. No single factor achieved that consistency. The case for combining methods rather than picking one.

Franking credits added ~1.53 percentage points per annum to ASX 200 returns for tax-exempt investors over 10 years to November 2023, transforming 7.16% total return into 8.69%. Material compounding advantage over a 20-year retirement. This is why pension-phase SMSFs overweight Australian equities — but it can also drive dangerous concentration.

Two Nobel laureates. Leverage from 25:1 to 250:1 with no deleveraging trigger. The thesis was eventually right — they didn't survive to be right. The definitive case study for why risk management matters more than being correct.

Averaged down repeatedly using Martingale betting with no position stop. Destroyed a 233-year-old institution. The losses weren't from a bad initial trade — they were from the absence of a rule that said "stop."

Concentrated positions across multiple prime brokers with no aggregate exposure monitor. $36 billion in losses for the banks. The positions weren't stupid — the absence of an exposure limit was. No IPS, no position limit, no circuit breaker.

Knew tech was a bubble. Said so publicly. No pre-commitment rule. Capitulated near the peak, lost $3 billion in weeks. The analysis was correct. The process failed. Being right about the market and making money from the market are two different skills.

ASX 200 peaked at 7,139 on 20 Feb, hit ~4,546 on 23 March. 36.3% decline in 31 days. Worst single day 16 March: –9.7%. VIX hit all-time high of 82.69. Then recovered ~55% from trough to March 2021. The investors with a written drawdown playbook and cash reserves bought the bottom. Everyone else watched.

ASX All Ordinaries peaked in November 2007 at ~6,850. Didn't sustainably breach that level until late 2019. Twelve years underwater in price terms. Passive investors who held and reinvested dividends recovered much earlier — but the price-only chart tested every conviction.