The Woman Who Beat 99.6% Of Hedge Funds: I Know Where The Algorithms Strike. I Used To Run Them!

Summary

Linda Raschke describes a short-term, discretionary trading approach built around price structure, risk control, and repeatable patterns—not trying to identify the institutions behind every order. She argues that large players often disguise their activity, while retail traders can benefit from being more agile and trading smaller size.

The host’s introduction says Raschke managed a $300 million fund whose five-year returns outperformed 99.7% of hedge funds. This is presented as an introductory claim, not independently verified in the discussion.

Trading and market observations

• Short holding periods: Raschke cites Renaissance Medallion, Monroe Trout, and Toby Crabel as examples of highly successful traders or funds with holding periods under 24 hours. She contrasts this with trend-following, which requires trading many markets and can involve drawdowns of around 40%.
• Limits of prediction: Short-term price tendencies may offer a small statistical edge, but confidence falls as the forecast horizon lengthens because more unknown events can affect markets.
• Order flow and large traders: Raschke cautions against trying to infer what large institutions are doing from the order stream. Large orders may be split across accounts or firms, and institutions can take time to adjust positions. She sees algorithms as providers of liquidity, but considers trying to out-read their very short-term activity a misguided game for many individuals.
• Intraday volume-spike test: When an intraday volume spike occurs, inspect the 5-minute and then 1-minute chart to see where the volume traded. Raschke says that about 80% of the time, the spike is associated with a prior intraday high or low, consistent with algorithms triggering around channel breaks. She warns against reacting automatically to such spikes, which may be noisy or news-driven.
• Volume and timing: Volume varies by session opening and close, economic announcements, day of week, season, and market. Breakout or range-expansion setups are often best assessed from a session opening. Grain markets also have crop reports, harvest seasonality, and contract rollovers. Persistent movement on a bar chart can reveal an imbalance without requiring a separate order-flow interpretation.
• Focus on the main market idea: Rather than dissecting every order or indicator, first assess the broad character of the day—such as whether it is moving low-to-high or high-to-low—and consider the trade’s initial location and the risk that location implies.
• Technical indicators: Raschke favors reducing redundant indicators. Moving averages and oscillators are derived from price and therefore cannot get ahead of it. For statistical modeling, she favors measures such as ATR and percentage-based functions over piling on price-derived indicators.
• Exceptional conditions: Large gaps, unusual volume, very large bars, and shifts in historically linked markets may be important but difficult to model because they occur infrequently. One example she gives is 30-year Treasury yields falling below 5% after being above that level for years, alongside changes in the yield curve.

Frameworks and risk management

• Use exits suited to the trade: Raschke outlines three basic target approaches:
  • A small target, such as half an ATR.
  • A larger target, such as three ATRs or a standard-deviation measure.
  • A trailing stop.

A time stop—holding for a set number of bars or days—is another option.

• Trailing stops are not a default solution: Raschke says a trailing stop is ideal for only about 15% of purely technical trades. Possible methods include a parabolic stop, a trailing level based on recent lows, a Keltner or Bollinger Band, or Wilder-style volatility stops. After extensive modeling, she found no single trailing-stop method consistently best across all trades.
• Study trade excursions: Review charts after the session and mark entries and exits. Examine how far price moved against and in favor of each entry, and whether the trade occurred during a quiet period, around lunch, or near a news catalyst. Use those observations to estimate how much adverse movement a valid trade typically tolerates.
• Scale-in approach versus her own practice: Raschke describes Perry Kaufman’s example of adding to a five-unit position in stages—three units relatively close together, then the fourth and fifth farther apart. She generally prefers to put on a position and exit it as a whole rather than routinely scaling out.
• Four profit centers in her former fund:
  1. S&P day trading: Usually one to three trades per day, aiming to capture one or two of the day’s roughly 60–90-minute swings.
  2. Overnight/short swing trades: Trades held overnight or for a few days, including volatility breakouts and setups informed by the Taylor trading technique. Profitable day trades might be held longer; losing ones were not allowed to become longer-term trades.
  3. Weekly/daily technical setups: For example, a weekly correction paired with a daily buy divergence near the end of a technical swing.
  4. Seasonal or market-specific trades: Buying oats at a seasonally favorable time is one example.

Raschke says these profit centers’ relative contributions varied by quarter, which helped diversify results.

• Position sizing: She prefers a uniform bet size across strategies and markets rather than changing size based on subjective conviction. At the start of each quarter, she recalculated unit size using each market’s average dollar range. Examples include a corn average daily range of roughly $500 and an S&P range of roughly $5,000; the goal is to normalize risk across instruments.
• Drawdowns: Raschke distinguishes discretionary trading from systematic trading. A discretionary trader in a prolonged drawdown should consider reducing size, pausing, or checking for execution errors, fatigue, or changes in routine. For a system, cutting size during a drawdown may be counterproductive if the system is near a recovery. She also says sizing should account for losing streaks, including the possibility of six losses in a row—even with a high win rate. This is a caution, not a guarantee that such a streak will occur.
• Stress and process: If losses become emotionally stressful, Raschke recommends stepping back rather than trading in a compromised state. Her own preparation includes writing a game plan the night before, reviewing overnight activity and gaps in the morning, and reducing distractions.
• Practice exercise: She suggests paper-trading a clearly specified volatility-breakout system across five markets, with roughly two trades per market per week. Record each outcome to become less emotionally attached to wins and losses and to test a defined entry, exit, and stop.

Assets, instruments, and references mentioned

• Equities and equity indexes: S&P / S&P futures, stocks, and the stock market.
• Futures and commodities: Gold, crude oil, copper, corn, oats, and grains generally.
• Fixed income: Bonds, Treasury yields—specifically 30-year yields—and the yield curve.
• Currencies: Currencies generally and the Swiss franc.
• Technical tools and concepts: ATR, standard deviation, moving averages, oscillators, EMA, Ichimoku, TRIN, Keltner Channels, Bollinger Bands, parabolic stops, volatility stops, channel breakouts, and three-bar coils.
• Funds and traders cited: Renaissance Medallion, Monroe Trout, Toby Crabel, Perry Kaufman, Richard Arms, and Warren Buffett.

Disclosures and cautions

• No explicit “not financial advice” disclaimer appears in the subtitles.
• The episode includes paid promotions for Alpha Capital, a no-rules prop-funding model, and TradeZella. Promotional claims include Alpha Capital’s stated $100 million in payments and the prop-funding ad’s claims that 41.4% of payments were processed in under 10 minutes and that average payment time was 12 minutes. These are advertisements, not independent performance assessments or recommendations from Raschke.
• Raschke repeatedly emphasizes that no single method is right for everyone; traders should judge methods by their own results and risk tolerance.

Presenters and sources

• Presenter/interviewer: Waqar Asim, Titans of Tomorrow
• Guest: Linda Bradford Raschke
• Other people and sources referenced: Richard Arms, Perry Kaufman, Monroe Trout, Toby Crabel, Warren Buffett, and Steven Kotler.