Multi-Timeframe Analysis (MTF)

Map context, setup, and execution states across fixed timeframes. Higher-timeframe information may help, but it does not automatically dominate; validate aligned and conflicting states separately.

Timeframe Selection

Each timeframe should be 4-6x the one below it. Pick one combination and use consistently.

Timeframe Roles

State Output

Report each timeframe as bullish, bearish, ranging, or uncertain under its objective rule. Combine them as aligned, mixed, counter-context, or incomplete. Do not turn a hand-built score into confidence or position size; size comes from portfolio risk.

Conflict Resolution

When evidence is incomplete or a state was not validated, return no trade.

Workflow

1. Higher TF — establish bias via EMA stack + slope (no ADX — use the canonical slope computation). get_indicators returns one indicator per call — fetch each separately:

   get_candles(symbol=<symbol>, exchange=<exchange>, interval=<htf_interval>, count=120)
   get_indicators(indicator_code="ema_21", symbol=<symbol>, exchange=<exchange>, interval=<htf_interval>, count=120)
   get_indicators(indicator_code="ema_50", symbol=<symbol>, exchange=<exchange>, interval=<htf_interval>, count=120)
   get_indicators(indicator_code="atr_14", symbol=<symbol>, exchange=<exchange>, interval=<htf_interval>, count=120)
   get_indicators(indicator_code="donchian_20", symbol=<symbol>, exchange=<exchange>, interval=<htf_interval>, count=120)

   Then compute trend strength via slope %:

   execute python3 -c "ema50=[<...>]; s=(ema50[-1]-ema50[-5])/ema50[-5]*100; print(f'htf_ema50_slope_pct={s:.3f}')"

   Calibrate price/ATR-normalized slope bands in training data, then combine with the EMA stack. Absolute percentage thresholds are not portable across timeframes/assets.

   Mark major HTF S/R: prior swing pivots, donchian_20 boundaries, Fibonacci extensions, weekly open / prior week high-low.

2. Primary TF — find setup aligned with HTF bias:

   get_candles(symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)
   get_indicators(indicator_code="ema_9",   symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)
   get_indicators(indicator_code="ema_21",  symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)
   get_indicators(indicator_code="ema_50",  symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)
   get_indicators(indicator_code="rsi_21",  symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)
   get_indicators(indicator_code="macd_fast", symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)
   get_indicators(indicator_code="atr_14",  symbol=<symbol>, exchange=<exchange>, interval=<primary_interval>, count=60)

   If HTF bullish → look for bullish setups (pullbacks to ema_21 / ema_50 / 50-61.8% Fib, demand zones, order blocks). Mark setup zones.

   Cite the RSI / MACD slope as a 3–5 value progression (latest value alone is folklore):

   • RSI21 53.2 (49.8 → 51.4 → 52.9 → 53.2) rising ← evidence of momentum continuation
   • MACD hist +8.4 (−1.2 → +3.6 → +8.4) accelerating bull ← evidence of impulse

3. Lower TF — time the entry:

   get_candles(symbol=<symbol>, exchange=<exchange>, interval=<ltf_interval>, count=20)
   get_indicators(indicator_code="rsi_21",    symbol=<symbol>, exchange=<exchange>, interval=<ltf_interval>, count=20)
   get_indicators(indicator_code="macd_fast", symbol=<symbol>, exchange=<exchange>, interval=<ltf_interval>, count=20)
   get_indicators(indicator_code="atr_14",    symbol=<symbol>, exchange=<exchange>, interval=<ltf_interval>, count=20)

   Entry triggers (any ONE confirmed at LTF candle close):

   • BOS in HTF direction — break of structure on LTF (HH for long, LL for short)
   • Rejection candle at setup zone — engulfing, hammer, pin
   • RSI hook back toward midline from extreme (e.g. RSI 36 → 42 in 2 bars after a pullback)
   • MACD histogram flip in HTF direction after a reset

   The LTF candle must be closed (not forming) before counting it as a trigger.

4. Report states: show timestamps, normalized slope, context/setup/execution states, conflict label, closed-bar trigger, invalidation, and valid, watch, or no trade.

Evidence and Validation

• Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
• Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
• Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
• Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
• Research basis: Lo, Mamaysky & Wang supports objective conditional price-pattern analysis; timeframe weights and scores are heuristics that must be frozen before testing.

Key Rules

• Test counter-context and aligned states rather than declaring one meaningless.
• Use higher-timeframe context only when it adds held-out value.
• Fix the number and ratios of timeframes before testing; more timeframes increase multiple-testing risk.
• Apply a predeclared policy to ranging/uncertain context.
• Use the EMA slope % (computed via execute) as the HTF bias gate; do NOT call ADX / DMI / Supertrend (API-billed, not in the free whitelist)
• Use market-regime-detection skill to classify the regime before applying MTF weights; regime determines which timeframe dominates

Related Skills

• market-regime-detection — classify regime before applying MTF; regime determines which TF dominates
• fibonacci-trading — use Fib across timeframes for precise entry and target levels