Larry Williams: Trading Tactics and Indicators I Still Use

Disclaimers / Risk

• Futures and options trading involves substantial risk; you can lose all or more than all of your initial investment.
• Use risk capital (money you can afford to lose).
• Past performance is not indicative of future results.
• Content is educational only, not trading advice or a financial/investment recommendation.

Markets / Instruments Mentioned

• S&P 500 E-mini (referred to as S&P E-Minis; also “E-mini” on charts, including 10-minute bars)
• Dow Jones Industrial Average
• Russell (mentioned in the context of “S&P or the Russell or the E-mini Dow”)
• Apple (AAPL) (discussed for cycles/forecasting)
• Gold
• Crude oil
• Bitcoin
• Wheat
• Bonds / bond market (used for “large range days” and the “hold-to-close” concept)
• References to futures broadly; also mentions stocks, forex, options

Key Tickers / Symbols

• Apple: AAPL
• No other specific ticker symbols are named in the subtitles.

Methodology / Frameworks / Step-by-Step Ideas

1) How Larry thinks indicators should be used (non-redundancy framework)

• Don’t stack multiple indicators that measure the same thing.
• Ask each indicator: “What is the purpose?”
• Use indicators to cover distinct roles, such as:
  • Overbought/oversold
  • Momentum
  • Trend / trend changes
  • Accumulation / smart money involvement
  • Cycles / timing
  • Price patterns
  • Value/fundamentals vs emotion
• He describes himself more as a “conditional trader”:
  • Wait for conditions where different indicator signals align to trigger moves.

2) “Market moves in a cycle/range sequence” (U-shaped intraday: congestion → creation)

Markets shift from:

• Little ranges → big ranges (trading range → trend move)
• Congestion → creation (small ranges → large ranges)

Intraday timing structure:

• Early session: often high volume, then volume dries up mid-day
• Late session: volume increases again
• Volatility connection: range is driven by volume

Practical implication:

• Day traders should focus on times with large ranges/volatility (opening and closing windows).

3) “Closes near extremes” rule for tops/bottoms

• Market tops: often occur when the market closes near the high (high-to-close relationship emphasized as a bearish context after rallies).
• Market bottoms: often occur when the market closes near the low.
• He claims this holds across multiple time frames (weekly/monthly/daily/intraday) and uses it to guide day-trading behavior.

4) “Hold to the close” for capturing intraday trend days

• He argues most traders try to enter near the end of the move; instead he wants to capture the trend move.
• Central rule:
  • On large range / trend days, he prefers to hold to the close because:
    • Large trend days often close on extremes
• Logic:
  • Day trading is time-limited; the priority is capturing the day’s trend run, not “dancing in and out.”

5) Risk/reward performance math (profit depends on payoff structure, not just win rate)

• A study of ~30 million trades (commodity traders) is used to show:
  • Even if traders are correct more often than wrong, they can still lose money if their average loss exceeds average gain.
• Explicit thresholds:
  • In a 12-month sample:
    • Accounts with 1:1 risk/reward turned to net profit about half the time (~50%)
    • Accounts with less than 1:1 risk/reward made money only 19% of the time
• Key takeaway:
  • Don’t focus only on accuracy (win rate).
  • Focus on whether average win ≥ average loss.

6) Larry’s money-management approach (position sizing / horizon alignment)

• He describes a style of:
  • Bet small (example: ~10 S&P contracts)
  • Target a larger move expected to last ~3 days to 15–20–30 days
• If wrong:
  • The loss is capped to be “relatively small” versus potential reward.

7) Cycle forecast method (timing vs magnitude)

• He uses a cycle-based indicator to forecast:
  • Timing of rallies/declines
  • Example horizon: forecast 66 bars into the future (described as roughly ~3 months in daily context)
• Cycles:
  • Used for direction and timing, not magnitude
• Caution:
  • Cycles don’t reliably predict how large the move will be.
  • Magnitude is influenced by fundamentals/other factors, while cycles suggest when swings may occur.

8) Accumulation / distribution tool (On-Balance Volume derivatives + open interest)

• For gold (and conceptually other markets), he uses an accumulation line:
  • Green line = “accumulation” versus price
• Detects divergence, for example:
  • Strong day closes near the high, then next day drops
  • Accumulation line fails to confirm highs → suggests distribution
• Referenced lineage:
  • Original idea attributed to Woods & Magnolia / “husband white team” (subtitles unclear)
  • Joe Granville popularized On-Balance Volume
• Modification:
  • Adds open interest accumulation plus price/volume accumulation to better reflect positioning/participation.

9) Seasonality method (“true seasonality” vs traditional pattern)

• He argues many seasonal studies are flawed because they rely on older patterns that no longer fit current regimes/data.
• His “true seasonality” is described as:
  • Based on seasonal price activity “up to today”
• He states he revised his method about ~10 years ago after realizing patterns had changed.
• Anecdote example:
  • “Sell in May and go away” vs his view:
    • He claims the Dow used to have its best buying period around May/through May until the Fed gained more control (framed around ~1950).

Key Numbers / Timelines / Explicit Claims

Forecasts and charting references

• 2020: “buy signal literally the week of the low” (described as comparable to a current signal)
• Cycle indicator horizon:
  • 66 bars (about ~3 months on daily context)
• Intraday detail:
  • Uses 10-minute charts
  • Mentions limited candles remaining later in the session (e.g., 3:15 show time noted by host)

Day-trading time split (subtitles slightly unclear)

• Price trends about 15% of the time
• Price consolidates about 15% of the time
• Emphasis: there is a limited window where markets actually trend, and traders should focus on it.

Risk/reward study statistics

• ~30 million trades
• 12-month sample
• Outcomes:
  • ~50% net profit for 1:1 risk/reward
  • 19% net profit for <1:1 risk/reward

Trading championship claims

• Larry Williams:
  • Winner in 1987: $10,000 → $1.1 million (real money)
• Daughter:
  • Winner in 1997: $10,000 → $110,000
• He claims:
  • Championship gains often 200–300% per year
  • Sometimes around ~600% per year
  • Often frequently coming from futures

Futures / open interest data rationale

• Futures have “better data,” including:
  • Commitment of Traders (COT) report
  • Crop reports
  • Longer history

Explicit Recommendations / Cautions (as stated)

• Simplify charts: don’t clutter with redundant indicators.
• Use indicators only when they solve a distinct problem (overbought/oversold, momentum, trend change, cycles, accumulation, etc.).
• Don’t interpret “overbought” as automatically bearish; context matters.
• Prefer directional edge from:
  • Trend + time
  • (“Trend is the basis of all profits” and “Trend is a function of time”)
• For big intraday moves:
  • Hold to the close on large-range days.
• For strategy evaluation:
  • Accuracy isn’t enough—optimize average win vs average loss (risk/reward).
• Cycles:
  • Use cycles for timing, but use other analysis for magnitude.
• Seasonality:
  • Use “true seasonality” rather than outdated patterns.

Presenters / Sources (Named)

• Larry Williams (guest)
• Tom (host of Trader Workshop; name not provided in subtitles)
• Joe Granville (referenced regarding On-Balance Volume)
• Charlie D. Francesca (referenced as “largest bond trader in the history of the world”)
• Ralph Vince (referenced for money management books)
• Brian Shad (referenced; former Navy Seal trader, “hold to the gloves” story)
• Woods and Magnolia husband white team (credited in the subtitles as origin for the accumulation/divergence work; names unclear)