Order Flow MTF

Overview

The Order Flow MTF strategy is VECTRA's most advanced and recommended strategy. It combines Multi-Timeframe Analysis, Premium/Discount Zones, Fair Value Gaps, CVD Divergence, Market Structure detection, full Regime Adaptation, Correlation Awareness, and Order Flow Imbalance into a single, highly-selective signal generator.

Category: Multi-Timeframe Order Flow Timeframe: Triple (HTF + MTF + LTF) Best Regime: All (regime-adaptive) Typical Hold Time: 1-4 hours Min Confidence: 0.70-0.78 (preset-dependent)

Timeframe Presets

Preset
HTF
MTF
LTF
Typical Hold
Best For

BOT_24/7 (Recommended)

1h

15m

5m

1-2 hours

Automated 24/7 operation

DAY_TRADE

1h

15m

5m

1-4 hours

Active day trading

SWING

4h

1h

15m

4-12 hours

Longer-term positions

SCALP

15m

5m

1m

15-60 min

High-frequency scalping

CONSERVATIVE

1d

4h

1h

1-3 days

Low-frequency, high-confidence

Strategy Parameter Presets

Preset
Min Confluences
Min Confidence
SL Mult
TP Mult
ADX Range

DEFAULT

3

0.70

1.2

3.0

25-50

BOT_24/7

3

0.72

1.2

3.0

25-50

AGGRESSIVE

2

0.68

1.0

3.5

20-60

CONSERVATIVE

4

0.78

1.5

2.5

30-45

Multi-Timeframe Analysis Flow

Higher Timeframe (HTF) Analysis

  • EMA alignment (20/50/200) for trend direction

  • Market Structure (HH/HL = bullish, LH/LL = bearish)

  • ADX for trend strength measurement

  • RSI for extreme exhaustion detection

Lower Timeframe (LTF) Signal Generation

The LTF analysis gathers up to 10+ independent confluences:

1

Premium/Discount Zone

Is price in the favorable zone for the trade direction?

2

Fair Value Gap

Is there an unfilled gap confirming the setup?

3

Market Structure

Is structure aligned with the trade direction?

4

HTF Alignment

Does the higher timeframe confirm or contradict?

5

Volume Expansion

Is volume above average, confirming interest?

6

Pullback Depth

Is the pullback to a meaningful Fibonacci level (0.382)?

7

Fibonacci Golden Pocket

Is price in the 0.618 golden pocket zone?

8

Order Flow Imbalance

Is the flow favoring the trade direction?

9

CVD Divergence

Is there a divergence confirming reversal potential?

10

Liquidity Sweep

Has a sweep occurred and held, showing structural strength?

Confidence Scoring Model

The Order Flow MTF strategy uses a sophisticated sigmoid-based confidence model that replaced the earlier multiplicative approach.

Sigmoid Parameters:

  • Midpoint: 5.0 confluences (center of the curve)

  • Steepness: 0.5 (controls spread of scores)

  • Pre-clamp: 0.85 (prevents early saturation)

  • Final cap: 0.95 (maximum possible confidence)

Regime-Indexed Weights — The weight of each confluence type changes based on the detected market regime. For example, in a Strong Trend, structure alignment gets ×1.15 boost while in Ranging markets, FVG zones get ×1.15.

RSI Regime Thresholds — Overbought/oversold levels adapt to regime:

  • Strong Trend: 85/15 (momentum can sustain extreme RSI)

  • Ranging: 72/28 (mean reversion kicks in earlier)

  • Volatile: 75/25 (slightly tighter)

Correlation Awareness

Before executing a trade, the strategy checks:

  • Cross-asset correlation with existing positions

  • Sector exposure (L1, L2, DeFi, Meme sectors)

  • Same-symbol opposite-direction hedge prevention (Hyperliquid uses net positioning)

  • Maximum portfolio gross exposure

Adaptive Learning

The strategy maintains per-symbol trade history and calculates adaptive adjustments based on recent performance. If a particular symbol has been producing losses, the confidence requirement tightens automatically. If it has been profitable, it stays at default.

Kelly Criterion Sizing

When sufficient trade history is available, the strategy calculates the optimal Kelly fraction for position sizing, capped at half-Kelly for safety.

Integration Points

  • Tier 2 Quality Enhancement — Signal quality scoring layer

  • Tier 4 Advanced Analyzers — News sentiment, volume profile, smart money flow

  • Microstructure Analysis — Spread, depth, and liquidity assessment

  • Coinglass Intelligence — OI, Funding, LSR, Liquidation data