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MACD Momentum with Trend Filter

Trade MACD crossovers only with the prevailing trend. Combines momentum indicators with trend confirmation for reduced whipsaws.

Strategy Overview​

  • Type: Momentum
  • Indicators: MACD (12, 26, 9), SMA(200)
  • Risk Level: Medium
  • Assets: Single asset (BTC)
  • Pattern: Start/run with ticker

Complete Code​

package main

import (
	"context"
	"time"
	"github.com/wisp-trading/sdk/pkg/types/connector"
	"github.com/wisp-trading/sdk/pkg/types/wisp"
	"github.com/wisp-trading/sdk/pkg/types/strategy"
	"github.com/shopspring/decimal"
)

type MACDMomentum struct {
	w          wisp.Wisp
	name       strategy.StrategyName
	signalChan chan strategy.Signal
	stopChan   chan struct{}
}

func NewMACDMomentum(w wisp.Wisp) *MACDMomentum {
	return &MACDMomentum{
		w:          w,
		name:       strategy.Momentum,
		signalChan: make(chan strategy.Signal, 10),
		stopChan:   make(chan struct{}),
	}
}

// Start launches the strategy's execution goroutine
func (s *MACDMomentum) Start(ctx context.Context) error {
	go s.run(ctx)
	return nil
}

// run manages the internal execution loop
func (s *MACDMomentum) run(ctx context.Context) {
	ticker := time.NewTicker(1 * time.Hour)
	defer ticker.Stop()

	btc := s.w.Asset("BTC")
	usdt := s.w.Asset("USDT")
	pair := s.w.Pair(btc, usdt)

	// Watch the pair on our exchange
	s.w.Spot().WatchPair(connector.Binance, pair)

	for {
		select {
		case <-s.stopChan:
			return
		case <-ctx.Done():
			return
		case <-ticker.C:
			// Analyze market and emit signals
			macd := s.w.Indicators().MACD(pair, 12, 26, 9)
			sma200 := s.w.Indicators().SMA(pair, 200)
			price := s.w.Spot().Price(pair)

			// Only trade with the trend
			inUptrend := price.GreaterThan(sma200)
			inDowntrend := price.LessThan(sma200)

			// Bullish crossover in uptrend
			if macd.MACD.GreaterThan(macd.Signal) &&
				macd.Histogram.GreaterThan(decimal.Zero) &&
				inUptrend {
				signal := s.w.Spot().Signal(s.name).
					BuyMarket(pair, connector.Binance, decimal.NewFromFloat(0.15)).
					Build()
				s.w.Emit(signal)
				s.w.Log().Opportunity(string(s.name), "BTC",
					"MACD bullish crossover in uptrend: Price=%.2f > SMA200=%.2f, MACD=%.2f > Signal=%.2f",
					price, sma200, macd.MACD, macd.Signal)
			}

			// Bearish crossover in downtrend
			if macd.MACD.LessThan(macd.Signal) &&
				macd.Histogram.LessThan(decimal.Zero) &&
				inDowntrend {
				signal := s.w.Spot().Signal(s.name).
					SellMarket(pair, connector.Binance, decimal.NewFromFloat(0.15)).
					Build()
				s.w.Emit(signal)
				s.w.Log().Opportunity(string(s.name), "BTC",
					"MACD bearish crossover in downtrend: Price=%.2f < SMA200=%.2f, MACD=%.2f < Signal=%.2f",
					price, sma200, macd.MACD, macd.Signal)
			}
		}
	}
}

func (s *MACDMomentum) Stop(ctx context.Context) error {
	close(s.stopChan)
	return nil
}

func (s *MACDMomentum) GetName() strategy.StrategyName { return s.name }
func (s *MACDMomentum) Signals() <-chan strategy.Signal { return s.signalChan }
func (s *MACDMomentum) LatestStatus() strategy.StrategyStatus { return strategy.StrategyStatus{} }
func (s *MACDMomentum) StatusLog() []strategy.StrategyStatus { return []strategy.StrategyStatus{} }

How It Works​

  1. Start(): Launches the run goroutine
  2. run(): Watches BTC/USDT on Binance, ticks every hour
  3. Determine Trend: Use 200 SMA to identify trend direction (price above = uptrend, below = downtrend)
  4. Check MACD: Look for bullish (MACD > Signal) or bearish (MACD < Signal) crossovers
  5. Filter: Only trade crossovers aligned with trend direction
  6. Emit: Push signals asynchronously to avoid whipsaws in choppy markets

Key Concepts​

  • MACD Crossover: When MACD line crosses the signal line, momentum is changing
  • Histogram: Shows the magnitude and direction of crossover (positive/negative)
  • Trend Filter: Using 200 SMA prevents counter-trend trades, increasing win rate
  • With-Trend Only: Buy signals only in uptrend, sell signals only in downtrend
  • Event-driven: Strategy owns its loop and emits signals asynchronously
  • Reduced Whipsaw: Trend filter reduces false crossover signals

Backtesting​

Run with:

wisp backtest

Expected characteristics:

  • Moderate trade frequency (roughly 1-2 trades per week)
  • Better win rate than raw MACD (no counter-trend whipsaws)
  • Avoids chop in ranging markets
  • May miss early trend entries (lags at turning points)
  • Works best in strong trending markets

Improvements​

Consider adding:

  • Histogram strength: Only trade when histogram is significantly positive/negative
  • Volume confirmation: Require volume on crossover bar
  • Multiple timeframes: Confirm on daily before trading on hourly
  • Stop loss: Place below recent swing low (use ATR for dynamic stops)
  • Partial exits: Scale out when histogram weakens