Summary of "La ÚNICA ESTRATEGIA de trading que usaré en 2026 (paso a paso)"

High-level focus

A step-by-step, rule-based trading strategy the presenter (Alex) will use in 2026. Emphasis on a multi‑timeframe, indicator-assisted approach (EMA50 + Fibonacci) adaptable to swing, day and scalp styles. The method is illustrated with real examples and claimed to be supported by an audited track record.

Tickers / assets / instruments / sectors mentioned

• ETFs: IBB (iShares Biotechnology ETF) — used as a sector shortcut to pick constituent stocks.
• FX: EUR/USD (explicit example); generic references to Forex (some transcript noise such as “USD CAT” may be mis‑transcriptions).
• Asset classes: US equities, indices, metals, cryptocurrencies, Forex, ETFs, commodities (implied).
• Sectors: airlines, banking, software, semiconductors, internet, renewable energy, aerospace, biotechnology, gaming.
• Platforms / tools: TradingView, Trading Lab, ChatGPT (used to compute an illustrative annualized return).
• Technical tools / constructs: Fibonacci retracements (0.382, 0.5, 0.618), 50‑period Exponential Moving Average (EMA50), diagonal trendline breaks, candlestick price action (impulse/pullback/continuation), multi‑timeframe (fractality) analysis.

Core rules and pre‑trade checks

Do NOT trade if any of these conditions apply:

• Routine was not followed the previous night or the current day.
• You are emotionally restless, busy, angry, or distracted.
• You cannot justify the trade in one or two sentences.
• The largest timeframe (daily/weekly/monthly) is not “clean” (no clear directional structure).
• You have hit daily, weekly, or monthly loss limits.

Additional behavioral checks (implied): avoid scarcity bias, overtrading, and forcing setups.

Three‑timeframe framework (methodology / step‑by‑step)

Use three aligned timeframes appropriate to your style. The framework is: Large timeframe → Intermediate timeframe → Small timeframe.

1. Large timeframe — direction & context

   • Identify direction over the next 2–3 candles on the largest timeframe appropriate to your style:
     • Swing: weekly → daily → hourly
     • Day: daily → hourly → 5‑minute
     • Scalping: hourly → 5‑minute → 1‑minute
   • Use horizontal support/resistance and major structure (higher highs / lower lows) to define bias.

2. Intermediate timeframe — pattern selection & entry zone

   • Find the setup: impulse → pullback → continuation, value gap, moving‑average confirmation, or candlestick pattern.
   • Apply a Fibonacci retracement from recent high to low and focus on 0.382 / 0.5 / 0.618 as preferred entry zones.

3. Small timeframe — execution & trigger

   • Drop to the smallest timeframe to time the execution. Entry triggers include:
     • Break of a diagonal trendline (discretionary).
     • Break of the 50‑period EMA on the small timeframe (EMA50 — objective).
   • Two execution options: (A) discretionary diagonal break; (B) objective EMA50 break — both valid; EMA50 is more objective.
   • Typical stop loss placement: at/beyond the 0.618 Fib or above/below the previous swing high/low depending on context.
   • Typical take profit: previous structure lows/highs or a predefined R ratio (examples include 2:1).

Position management / trade management rules

• Use a trailing/objective rule based on the EMA50 to move stops as the trade progresses (move stop progressively to the EMA to lock profit).
• Avoid discretionary micromanagement: no averaging in, no adding positions, avoid emotional partials.
• Partial profit‑taking is not a primary technique for the presenter; preference is EMA‑based stop adjustment.
• Two execution styles: aggressive (earlier EMA break) vs conservative (wait for diagonal break + EMA confirmation).

Concrete numeric metrics & performance claims

• Typical frequency: ~80 trades per year.
• Average per‑trade “risk‑return” (subtitle phrasing ambiguous): ~1.55% (interpreted as average R per trade).
• Win rate: 57%.
• Average win size: 1.30% (per winning trade).
• Average loss size: 0.73% (per losing trade).
• Example computed annualized return (using the stated metrics via ChatGPT): ≈34% per year (illustrative).
• Performance anecdotes: “almost 15% profitability live in 9 hours”; “more than $5,000 in a single month”; also examples of large losses (e.g., >$30,000 in a month; ≈$10,000 in a single trade).
• Recent month examples: June 2025 = −0.67%; May 2025 = −0.04 (treated as break‑even).

Risk / sizing specifics

• Stop loss and take profit placement are structural (0.618 Fib, previous highs/lows).
• Explicit position sizing (percent of account per trade) is not stated in the subtitles; risk per trade can be implied from R ratios (examples include 2:1 and 0.8:1).
• For swing trades the presenter references taking larger size (he said he may “risk triple” in swing examples — implying larger nominal position sizing vs intraday).

Examples shown

• Swing example (EUR/USD): weekly resistance → daily pullback to 0.618 Fib → execute on hourly with diagonal + EMA break; 2:1 R example; stop hit during EMA‑based management but price later continued to TP (illustrates management differences).
• Day trading: daily → hourly → 5‑min sequence; entry on 5‑min EMA/diagonal break; stop above previous highs; quick move to TP.
• Scalping: hourly → 5‑min → 1‑min; Fibonacci + 1‑minute double top break for execution; stop at 0.618 zone; TP at previous lows.

Philosophy, behavioral points & cautions

• Adapt trading to personal schedule and lifestyle — don’t force session timing.
• Prefer quality over quantity: prioritize clean structure and higher‑probability setups.
• Emphasizes fractality: the same impulse/pullback/continuation pattern across timeframes — align large→small.
• Warnings: avoid emotional trading, scarcity bias, and overtrading.
• Indicator stance: the presenter defends indicators and argues top competitors use them; EMA50 is central to his objective rules.

Explicit recommendations / tactical rules (summary)

• Only trade when the large timeframe structure is “clean” and aligned with intermediate and small timeframes.
• Use Fibonacci retracements (0.382 / 0.5 / 0.618) on the intermediate timeframe to plan entries.
• Execute on the small timeframe when EMA50 or a diagonal trendline is decisively broken.
• Place stop loss at the 0.618 Fib or beyond recent structure; take profit at previous structure highs/lows.
• Manage open trades by trailing the stop to the EMA50 as price moves.
• Enforce emotional limits and daily/weekly/monthly loss caps; prefer fewer high‑quality setups.
• Adapt the same method to swing/day/scalp variants.

Disclosures and caveats noted by the presenter

• The strategy is the presenter’s method and “just because it works for me doesn’t mean it will work for you.”
• Losses are inevitable; the presenter shows both large gains and large losses publicly.
• An “audited track record” is referenced in the video (no auditor named in subtitles).
• Further learning materials and performance evidence links are provided in the video description / first pinned comment (whiteboard lesson, monthly statements, contest evidence).
• ChatGPT was used as an illustrative tool to compute annualized returns from stated metrics — not a guarantee.

Potential ambiguities / likely transcription noise

• Some asset names appear garbled in the transcript (e.g., “outcat,” “USD CAT”) — likely mis‑transcriptions. Use explicit references (IBB, EUR/USD) and treat others as general asset classes.
• The subtitle phrase about “average risk‑return of 1.55% (from the maximum to the minimum…)” is awkward; interpreted here as the average per‑trade R used in performance examples.

Sources / presenters cited

• Presenter: “Alex” (only first name appears in subtitles).
• Platforms / references: TradingView, Trading Lab, ChatGPT, an “audited track record” (no auditor named).
• Additional evidence: pinned comment/description links to a whiteboard lesson, account statements, and a trading contest win.

Bottom‑line summary

A repeatable, 3‑timeframe method built around EMA50 + Fibonacci entries, objective execution rules (EMA50 or diagonal break), and EMA‑based trade management. Adaptable to swing, day and scalp trading, it emphasizes alignment across timeframes, routine, loss limits, and quality over quantity. Stated performance metrics (illustrative): ≈80 trades/year, 57% win rate, avg win 1.30%, avg loss 0.73%, avg per‑trade R ≈1.55%, and an example annualized return ≈34% (computed for illustration). Results are personal and not guaranteed to transfer.

Category

Finance

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