+140% Return Trading A Million - How to Dominate the Next Bull Market Like a Pro Trader Clement Ang

Business/strategy takeaways (execution-focused)

• Performance is path-dependent: even if traders/investors chase the same tickers, outcomes diverge based on the sequence of decisions. Mistakes early can cascade into later underperformance and poor mental/state readiness.
• Maximize returns by optimizing decision timing (“when to step on the gas”):
  • Be most aggressive at the beginning of momentum cycles, typically after a long consolidation / correction.
  • Reduce risk as the cycle matures because setups deteriorate and markets become crowded/choppy (“feeding the ducks”).
• Relative Strength (RS) is the primary edge selector:
  • Look for stocks/groups that diverge vs. the index during corrections (e.g., higher lows while the index forms lower lows).
  • Use RS “phase” status (e.g., whether RS line is holding vs. breaking down) as a situational-awareness barometer.
• Corrections function like a “reset” process:
  • Institutions and positioning dynamics clear out weak hands and crowding.
  • This increases the probability that leadership forms constructive bases and then launches quickly when the environment improves.
• Character change = risk regime shift:
  • Specific market “tell” events (e.g., a character change bar) can mark when the easy trade environment ends and chop/choppy volatility begins.
  • After character change, adjust style: less aggression, more selectivity, tighter process discipline.

Frameworks / playbooks mentioned or implied

• Decision-tree / path dependency

  • Every decision (A vs B) changes future options and outcomes.
  • Early mistakes can force later “hole digging,” including psychological impairment that prevents capturing easy periods.

• Momentum-cycle playbook (“easy vs hard mode”)

  • Easy mode: beginning of a momentum cycle after correction; prioritize fast exposure when A+ setups appear.
  • Hard mode: later-cycle maturity / crowded conditions; prioritize reduced risk, fewer trades, and capital preservation.

• Relative Strength (RS) identification workflow

  • Screen for uptrend criteria (stocks above key moving averages) + liquidity/volatility filters.
  • During corrections: use contextual screening based on index position (e.g., index below moving averages → find stocks holding above them).
  • Confirm leadership theme clusters (e.g., AI infrastructure names).

• Progressive exposure (risk sizing) “not too literal”

  • Increase position risk quickly early in the trend once you have traction.
  • Scale down risk later as setups weaken and volatility/crowding increase.
  • Avoid ramping so slowly that you miss “best entry windows.”

• Multi-timeframe setup discipline (daily first, intraday to time)

  • The 5-minute / “6-20” MACD timing tool is not a standalone setup.
  • Must have daily chart confluence first, then use intraday tool to time the inflection.

• Situational awareness via cycle tiering

  • Observe rotation order:
    1. Market leaders
    2. Tier-2
    3. Tier-3 / “laggards” near the end (or during regime transitions)

Concrete process (actionable steps)

A) Weekly/daily screening process to find RS leaders

Weekly (pre-market) scan

• Use a general screen for stocks in uptrends:
  • Trading above 50-day SMA
  • Trading above 200-day (moving averages sloping up)
  • Liquidity filter: average dollar volume > $100M/day
  • Volatility filter: at least ~3.5% ADR
• Create a watchlist of qualifying liquid uptrend stocks.

Daily review (weekday)

• Flip through charts and tag stocks based on technical position.
• Maintain:
  • General watchlist: stocks above major moving averages (e.g., 20/50/200)
  • Breakdown watchlist: stocks below those moving averages

Contextual RS screening

• If index (e.g., QQQ/Nasdaq proxy) is below moving averages during a correction:
  • Find stocks that hold above those same levels
  • Or find setups where index makes lower lows while stock makes higher lows
• Optionally screen for performance divergence by time window (e.g., Qs down X% while certain stocks up Y%).

B) How to enter during early-cycle correction-to-uptrend transitions

• Look for undercut & rally signals at index level (especially near a follow-through day).
• In leaders:
  • RS phase should persist while the index is weak.
  • Prefer low-risk entries after the environment shifts:
    • Pullbacks to structural support (e.g., base area / 20 EMA zone)
    • Or breakout entries when the breakout is low-risk by structure

Risk management heuristics

• Stop placement tied to structural invalidation (e.g., low of day, base lows).
• Avoid “swinging a position” like a shorter-horizon trade (prevents cost-basis inflation and psychological strain).

Key metrics / targets / performance figures (explicit)

• 2024: returned over 80%
• 2025 (million-dollar division): returned 140%
• Momentum “easy periods” (qualitative durations):
  • Momentum markets described as usually 1–3 times per year (sometimes 0 in bear markets)
  • Easy momentum cycles cited:
    • Shortly after “Liberation Day” (May 2025)
    • September → October 10th window (quantum/strategic mineral themes)

Trade/risk sizing specifics mentioned (rule-of-thumb, not KPIs)

• Examples of scaling risk “too literally” causing late entries.
• Example cap referenced: ~15% drawdown off equity-curve highs as an upper bound he claims he exceeded in one cycle (due to gaps/chop).

Trade management examples

• Micron extension rule: if extension reaches ~8–10x ATR from the 50-day, he takes position off (sold too early at ~7x then watched further gains).
• ARM: reported large winner but with follow-on management issues due to average cost inflation and adding/reducing.

Concrete examples / case studies (what to copy)

Index/leadership clues (“tells”)

• Undercut and rally (index): early evidence of leadership returning (e.g., prior low undercut then rebound).
• RS divergence under adverse narrative: while news implies weakness (e.g., crude vs equities narrative), equities behave differently—interpreted as positioning reset / news failure.
• Weekend derisking & reversal as a tell: multiple March weekends showed de-risking; then early April showed gap-down reverse higher and close at highs into a long weekend—interpreted as decoupling and accumulation.

Stock/trade walkthroughs

• UTCT (AI infrastructure pick-and-shovel)

  • Setup traits:
    • AI infra/theme
    • Higher-low relative strength during correction
    • RS phase indicated (TraderLine RS line)
    • Volume drying up during base (less supply)
    • Pullback buy into 20 EMA
  • Outcome (approx.): held partially through April run; exited ahead of earnings after adverse gap; later price continued higher.

• NBIS

  • Expectation-breaker: rejected 20 EMA then gapped below 50 and ripped higher.
  • RS divergence: higher low vs Nasdaq lower low.
  • Mistake: “too active” position handling; cost basis drift from add/reduce cycles caused psychological difficulty holding through a large consolidation.

• STMicroelectronics

  • Caught a leader with wider stop due to chasing concerns.
  • Mistake: sold “arbitrarily” too early (didn’t follow the intended technical sell trigger such as 20-day moving average touch).

• ARM (major winner)

  • Initial entry:
    • Catalysts tied to “agentic AI GPUs/CPU theme” (plus other AI/catalyst leaders like Marvell/AHR)
    • RS phase while market was falling
    • Pullback buy to structural support with “multi-layer guardrails” (base support + 20 EMA + 200 SMA zone context)
  • Mistake: repeated add/reduce actions shifted average cost upward; later had to capitulate during choppy pullback.

• Micron

  • Theme tailwind: memory names (SanDisk, Seagate, WDC) setting up together.
  • Entry: pullback turn using 5-min 6-20 chart MACD timing, after daily confluence.
  • Mistake: overscaled selling into strength; sold when extension ~7x ATR instead of waiting/using the rule more effectively.

• Software rotation examples (cycle-tiers)

  • Post-March breakout, software names gained traction:
    • Twilio earnings catalyzed narrative shift (“AI helps software”)
    • Examples: DDOG, FROG, DOCN, SNOW, CrowdStrike; plus Cloudflare/Zscaler-related setups.
  • Execution pattern:
    • Earnings-related big gaps (≥ ~30%) often pulled back intraday, then baselined and resumed.

Situational awareness / regime-change checklist (from the talk)

When deciding aggression vs caution, check:

1. Market leadership behavior: are leaders wide and loose (unstable) or in constructive consolidation?
2. Theme/setups proliferation: do you still see many actionable setups, or does the opportunity set shrink?
3. Trading traction & emotion: are last few trades net-positive, and does it feel “easy” vs aggravated?
4. RS leadership deterioration: RS line breaking its own trend / short-term MA across many leaders = choppier environment.

Presenter / source attribution

• Presenter: Clement Ang (portfolio manager; US Investing Championship top performer)
• Source referenced in content: Richard (conference host/interviewer)
• Mentors/books/trader references mentioned:
  • Dan Zanger
  • William O’Neil (How to Make Money in Stocks; CAN SLIM)
  • Mark Minervini
  • Jesse Livermore
  • Gerald Loeb
  • John Boik
  • Gil Morales (for the 5-minute 6/20 chart concept)
  • “Kina and Anthy, Anthony She” (swing cycle concept)
• Sponsor/platform mentioned: Defiance (Trading platform)