Competition Playbook
Illustrated guide · 2026 edition

How winners play: strategies from the world's investing competitions

From real-money contests like the US Investing Championship to student challenges judged on research, each competition rewards a different style of play. Here's what wins each one, why it works, and what you can safely use in real life.

📚 6 competitions 📊 12 visuals 🎲 1 live simulation ⏱ ~25 min read
US Investing ChampionshipWorld Cup Trading Championships

One-year returns of well-known winners, as publicly reported. Log scale: each grid step is roughly 3×.

The competitions at a glance

The single biggest factor in strategy is how the contest is scored. Pure "highest return wins" contests push players toward risk. Contests judged by experts reward process and reasoning instead.

CompetitionMoneyWho entersLengthHow you winWinning style
US Investing ChampionshipReal moneyIndividual traders and money managersCalendar yearHighest % return in your divisionConcentrated growth and momentum stocks with tight stops
World Cup Trading ChampionshipsReal moneyFutures and forex tradersCalendar yearHighest net % returnLeveraged trend and breakout trading
Virtual stock games
MarketWatch, Investopedia, The Stock Market Game
VirtualStudents, classes, the publicWeeks to a semesterHighest portfolio valueHigh-volatility, concentrated bets
Wharton Global High School Investment CompetitionVirtual $100kHigh-school teamsSeveral monthsJudged on strategy and reasoningClient-driven, diversified portfolio
CFA Institute Research ChallengeNo portfolioUniversity teamsSeveral monthsJudged on report and presentationDeep fundamental analysis and valuation
Quant tournaments
Numerai, Kaggle finance challenges
Stakes / prizesData scientists and codersRolling roundsScore on unseen (live) dataRobust models that don't overfit
The strategy map. When only the final return counts, risk-taking rises. When judges score your reasoning, careful process wins. Positions are a qualitative summary.
Foundations4 min read · interactive

Why "highest return wins" rewards taking more risk

Before looking at each contest, it helps to understand one idea: in a winner-takes-all contest, volatility is your friend, even if it makes your typical result worse.

Imagine 100 players. Only the person in first place wins. If you invest sensibly and earn a solid 8%, you will almost never beat the luckiest of the other 99 players. Coming 30th and coming last pay the same: nothing. The smart move becomes swinging for the fences, because you only need to be lucky once.

Economists call this a convex payoff. Fund managers chasing year-end rankings face a milder version of it. Use the simulation below to see the effect for yourself. Every player has the same small positive edge; the only thing you control is how volatile your portfolio is.

🎲 Try it: the volatility advantage

Your chance of finishing 1stYour chance of losing 30% or moreFair share (1 ÷ players)
–
Chance you finish 1st
–
Fair share
–
Your typical (median) return
–
Chance you lose ≥ 30%

Simulation: 3,000 contests per setting. Rivals use normal volatility (0.6–1.8% a day). Everyone shares the same small upward drift. Runs entirely in your browser.

The key takeawayRaising volatility can multiply your chance of winning many times over, while your typical result gets worse (this is called volatility drag). That trade-off explains most behaviour in return-only contests, and it's why copying contest winners with your savings is dangerous.
Real money · Stocks6 min read

US Investing Championship: momentum, leadership and ruthless stops

Run by Norm Zadeh since the 1980s, this is the best-known real-money stock-picking contest in the United States. Its winners have shaped a whole school of growth-stock trading.

Format
Real brokerage accounts, ranked by % return
Period
One calendar year
Divisions
By account size and asset (stocks, options, futures)
Famous winners
David Ryan, Mark Minervini, Oliver Kell

Because results come from real accounts, the US Investing Championship (USIC) is a test of both skill and nerve. Winning returns in the stock division are routinely in the triple digits. David Ryan won three years running (161%, 160% and 118% from 1985 to 1987). Mark Minervini won with 155% in 1997 and returned in 2021 to win with 334.8%. In 2020, Oliver Kell posted 941%.

Their styles differ in the details but share a common playbook: buy the strongest stocks in the strongest market, at precise entry points, and cut losers fast.

1. Trade only market leaders (CAN SLIM)

David Ryan trained under William O'Neil, whose CAN SLIM checklist looks for: strong Current quarterly earnings, strong Annual earnings growth, something New (product, management or price high), tight Supply and rising demand, Leaders not laggards, Institutional buying, and a healthy Market direction. The idea is that the biggest winners of every cycle share these traits before they make their big moves.

2. Buy only in "Stage 2"

Stan Weinstein's stage analysis says a stock's life repeats in four phases. Contest winners avoid the slow base (Stage 1) and the decline (Stage 4). They concentrate their money in the strong uptrend: Stage 2.

The four stages of a stock A stock moves sideways in Stage 1, trends up in Stage 2, tops out in Stage 3 and falls in Stage 4. Buying happens at the breakout from Stage 1 into Stage 2. Stage 1 · Base Stage 2 · Advance ✓ Stage 3 · Top Stage 4 · Decline ✗ ↑ Breakout: buy zone starts ━ price ╌ 30-week moving average
Stage analysis. Buy when the price breaks out of a long base and the 30-week average turns up. Sell or avoid once the average rolls over.

3. Precise entries: SEPA and the VCP

Minervini's SEPA method (Specific Entry Point Analysis) waits for a Volatility Contraction Pattern (VCP). The stock pulls back several times, and each pullback is shallower than the last, with trading volume drying up. This tells you sellers are running out. The buy point (the "pivot") is the moment price breaks above the top of the final, tightest pullback on a surge in volume.

Volatility Contraction Pattern Three pullbacks shrink from 25% to 12% to 6% while volume dries up. Price then breaks above the pivot on heavy volume. A stop-loss sits a few percent below the entry. Pivot = buy point Tight stop (e.g. 7–8% max) −25% −12% −6% tight Volume dries up as the pullbacks shrink Volume surge on breakout
The VCP. Each pullback is roughly half the previous one. The tight stop means a failed breakout costs little, while a successful one can run for months.

4. Small losses, big winners, and pyramiding

USIC champions are often right less than half the time. They still win because their average gain is several times their average loss. Typical rules:

  • Cut every loss quickly, often at 5–8% below the buy price, with no exceptions.
  • Pyramid into winners: start with a partial position and add only as the trade proves itself.
  • Concentrate in a handful of top ideas when the market is healthy. In a one-year contest, a diversified portfolio of 40 stocks rarely wins.
  • Go to cash when breakouts start failing. Several champions credit sitting out bad markets as much as picking stocks.

Oliver Kell describes his approach as a "cycle of price action", with named setups such as the wedge pop and EMA crossback. The aim is to buy early in a new uptrend and add as it confirms.

Watch outOne-year triple-digit returns usually come with big drawdowns, high turnover, short-term tax bills and many small losses. The same concentration that wins a contest can wipe out a year in a bad market.
Real money · Futures5 min read · interactive

World Cup Trading Championships: leverage and position sizing

The World Cup Championship of Futures Trading is the futures world's most famous real-money contest, and home to the highest return on record.

Format
Real accounts, ranked by net % return
Markets
Futures, plus forex divisions
Entry
Small accounts (historically about $10,000 for futures)
Record
Larry Williams, 1987: 11,376%

In 1987, Larry Williams turned $10,000 into more than $1.1 million, an 11,376% return that still stands as the contest record. Ten years later his teenage daughter, Michelle Williams (later an Oscar-nominated actress), won with a reported return of about 1,000%.

Futures let traders control large positions with little cash (this is called leverage). A 2% move in the underlying market can mean a 20% or 40% move in the account. That makes the contest less about what you trade and more about how much you bet on each trade.

1

Volatility breakouts

Buy when price moves more than a set share of the previous day's range. Williams popularised this short-term approach.

2

Trend following

Ride big moves in commodities, bonds or currencies, using wide stops and trailing exits so winners can run.

3

Systematic rules

Fully automated strategies remove emotion. Algorithmic traders such as Kevin Davey have placed near the top.

4

Aggressive sizing

Risking a large share of the account per trade. This is the real engine of record returns, and of most blow-ups.

Same edge, three bet sizes

Below, three traders take exactly the same 120 trades. Each trade wins 45% of the time, and a win pays twice what a loss costs, so all three have a real edge. The only difference is how much of the account they risk per trade. Press reshuffle to see a new sequence of wins and losses.

Position sizing beats stock picking. The 17.5% line is the "Kelly" bet, the maximum-growth size for this edge. Betting beyond it adds risk and lowers long-run growth. The 40% trader sometimes leads early, which is why leaderboards can mislead. Log scale; accounts that fall 95% are marked ruined.
What leaderboards don't showEach year, many leveraged entrants lose most of their account. You only hear about the survivors. Even Larry Williams' record year reportedly included severe swings along the way.
Virtual money · Free4 min read

Virtual stock games: the "nothing to lose" problem

Classroom and online simulators such as MarketWatch's Virtual Stock Exchange, the Investopedia Simulator and SIFMA's The Stock Market Game are many people's first taste of investing. They are great for learning, but they create some odd incentives.

Format
Virtual cash (often $100,000)
Players
Students, classes, friends, the public
Length
A few weeks to a semester
Downside
None, which changes everything

With no real money at risk and only first place counting, the maths from the simulation above takes over. A sensible portfolio almost never tops a leaderboard of hundreds of players over six weeks. A single wild bet sometimes does.

Why gamblers top leaderboards. The steady player (narrow curve) has the better typical result, but almost no chance of reaching the +40% usually needed to win a big game. The gambler (wide curve) loses more often but owns the right-hand tail.

Strategies you'll see in the wild

1

All-in concentration

Putting everything into one or two volatile stocks, such as small biotechs before trial results or meme stocks.

2

Leveraged ETFs and options

Where allowed, 3× ETFs or short-dated options magnify every move.

3

Event bets

Buying just before earnings or news announcements, where a single day can move a stock 20% or more.

4

Leader "covers", chaser gambles

Late in the game, the leader cuts risk or copies rivals' holdings to protect the lead. Those behind must take even bigger bets.

How to play it well (and actually learn)Check the rules first: many class games now cap how much you can put in one stock, or add a written report. Set yourself a personal rule, such as no position above 20% and a written reason for every trade, then judge yourself on that process, not just your rank.
Virtual $100k · Judged4 min read

Wharton Global High School Investment Competition: invest for a client

Run by the Wharton School's Global Youth Program, this team contest flips the incentives: judges score the quality of your strategy and reasoning, not just the size of your returns.

Format
Team manages a virtual $100,000 portfolio
Players
High-school students worldwide
Twist
A case-study "client" with goals and constraints
Judged on
Strategy, rationale, teamwork, fit with the client

Teams receive a client profile, for example a family saving for a goal, with a time horizon, risk tolerance and preferences. They build and manage a portfolio and submit reports and a final presentation. A team that earns 40% by buying one volatile stock would score badly, because it ignored the client.

The winning process

Understand the clientGoals, time horizon, risk, values
Write the planAn investment policy statement (IPS)
Set asset allocationThe split between stocks, bonds and cash
Pick holdingsA one-paragraph thesis for each
Monitor and rebalancePre-agreed rules, not panic
ExplainClear story, honest about mistakes
    An example allocation for a moderate-risk client with a five-to-ten-year goal. This is illustrative only. The point is that every slice is explained by the client's needs.
    Research · Judged4 min read

    CFA Institute Research Challenge and stock pitch contests: win the argument

    There is no portfolio here at all. University teams research one real listed company, write a professional equity research report, and defend a buy, hold or sell call in front of industry judges.

    Format
    Research report plus live presentation and Q&A
    Players
    University teams, local to global rounds
    Subject
    One assigned public company
    Judged on
    Analysis, valuation, clarity, defending your view

    Here, "strategy" means the strategy of a persuasive, well-supported investment case. Winning teams treat it like professional sell-side research. University stock pitch competitions reward the same skills in a shorter format.

    What winning teams do

    1

    Find a variant view

    State clearly where you disagree with the market consensus and why, backed by evidence.

    2

    Triangulate valuation

    Combine a DCF (discounted cash flow) with peer multiples, and show how sensitive your target is to your assumptions.

    3

    Name the catalysts

    Explain what will make the market change its mind, and roughly when.

    4

    Own the risks

    List the biggest risks, how likely each is, and what would prove you wrong. Judges probe these hardest in Q&A.

    The "football field" chart, a staple of winning reports. Each bar is a value range from a different method. When most ranges sit above today's price, the buy case is convincing. Figures are for a hypothetical company.
    Pro tipLead with your conclusion and three supporting points on page one. Judges read dozens of reports, so make yours easy to follow and every chart easy to read.
    Data science · Live scoring4 min read

    Quant tournaments: the enemy is overfitting

    In Numerai and Kaggle finance competitions, you don't pick stocks. You build models that predict market behaviour, and they are scored on data the models have never seen.

    Numerai
    Predict stock returns from anonymised data; optionally stake crypto (NMR) on your model
    Kaggle examples
    Jane Street Market Prediction, Optiver Realized Volatility, Two Sigma news challenge
    Scored on
    Live or hidden "private" data
    Players
    Data scientists, students, ML hobbyists

    Financial data is noisy, and with enough tuning almost any model can look brilliant on past data. Leaderboards on Kaggle often "shake up" when final scores move from the public test set to the hidden one: teams that tuned to the public scoreboard drop, and robust models rise.

    Overfitting curve As model complexity rises, error on training data keeps falling, but error on unseen data falls and then rises again. The sweet spot is in the middle. Underfit Overfit great backtest, fails live Sweet spot Training / public leaderboard error Unseen (live) data error Model complexity / tuning to the leaderboard → Error (lower is better)
    The overfitting trap. Every extra tweak improves your backtest, but past the sweet spot it makes live results worse.

    What consistently works

    Takeaways3 min read

    What carries over to real investing, and what doesn't

    ✅ Worth borrowing

    • Cut losses early and let winners run (USIC)
    • Size each position by risk, not excitement (World Cup)
    • Start from your own goals and time horizon (Wharton)
    • Write down a thesis and what would prove it wrong (CFA)
    • Distrust strategies that only look good on past data (Quant)

    ❌ Leave in the game

    • Maximum-volatility, all-in bets
    • Heavy leverage on money you need
    • Judging success over a few weeks
    • Ignoring taxes, fees and trading costs
    • Copying a winner without seeing the losers
    The maths of losses. A 50% loss needs a 100% gain just to get back to where you started. This is why every champion in this guide, whatever their style, protects against big losses first.
    Survivorship biasFor every contest winner with a 900% return, many others using the same aggressive style lost heavily, and nobody writes about them. Treat headline returns as proof of what's possible, not what's likely.

    Which competition suits you?

    🎓 Student who likes research and writing

    CFA Institute Research Challenge (university) or Wharton (high school). Great for your CV and costs you nothing.

    💻 Coder or data-science learner

    Numerai or Kaggle. Free to enter; staking real crypto on Numerai is optional.

    📱 Curious beginner

    A free virtual stock game with friends. Set your own sensible rules and learn the mechanics.

    📈 Experienced trader

    Real-money contests like the USIC or World Cup. Expect entry fees, and only use money you can afford to lose.

    Jargon buster

    Plain-English definitions of the terms used above.

    Volatility
    How much a price swings up and down. Higher volatility means bigger moves either way.
    Drawdown
    The drop from a portfolio's peak to its lowest point before it recovers.
    Leverage
    Using borrowed money or derivatives to control a bigger position than your cash alone allows. It magnifies gains and losses.
    Stop-loss
    A pre-set price at which you sell to limit a loss.
    Pivot / breakout
    The price level that, once crossed, signals a new uptrend may be starting.
    Pyramiding
    Adding to a winning position in steps as it keeps working.
    Kelly criterion
    A formula for the bet size that maximises long-run growth for a given edge. Most pros bet a fraction of it.
    DCF
    Discounted cash flow: valuing a company by estimating its future cash and converting it to today's money.
    Overfitting
    When a model memorises past noise instead of learning real patterns, so it fails on new data.
    Asset allocation
    How you split money between stocks, bonds, cash and other asset types.

    Sources and further reading

    Important: This page is for education only. It is not financial advice. Returns quoted are as publicly reported and are not guarantees of future results. Strategies built to win contests can lose real money quickly. Talk to a registered financial adviser before investing.

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