「Bollinger Bands Mean Reversion(GBPJPYversion)」ロゴ
cBot
バージョン 1.0、Nov 2025
Windows、Mac, Mobile, Web
「Bollinger Bands Mean Reversion(GBPJPYversion)」アップロード画像
「Bollinger Bands Mean Reversion(GBPJPYversion)」アップロード画像
「Bollinger Bands Mean Reversion(GBPJPYversion)」アップロード画像
「Bollinger Bands Mean Reversion(GBPJPYversion)」アップロード画像
「Bollinger Bands Mean Reversion(GBPJPYversion)」アップロード画像
「Bollinger Bands Mean Reversion(GBPJPYversion)」アップロード画像
10M
取引数量
10.64K
獲得pips
20
販売
990
無料インストール

Strategy Name: Bollinger Bands Mean Reversion and Momentum Strategy
Author: ApexVector
Symbol: GBPJPY
Timeframe: m9
Leverage Used: 1:200
Testing Period: 17/07/2024 – 10/11/2025
Spread: Fixed 0.9 pip(s)


📈 Overview (GJ version optimized) First 10 copies were sold for $19. After that, the price will rise to $34.

Developed by ApexVector, a fintech student passionate about quantitative finance and algorithmic trading, this strategy blends Bollinger Bands mean reversion with momentum confirmation to capture both pullbacks and short-term breakouts. It dynamically adjusts to volatility, filtering false signals and optimizing trade timing.


⚙️ Core Logic

  • Mean Reversion Module: Identifies price extremes using Bollinger Bands to trade reversals back to the midline.
  • Momentum Filter: Confirms entries using directional momentum strength to avoid premature countertrend trades.
  • Dynamic Position Management: Applies stop-loss, take-profit, and trailing parameters to balance risk and reward.
  • No Martingale / No Grid: Focuses on clean, single-entry trades for transparency and reliability.


💡 Key Backtest Results (GBPJPY, 1Y3M)

MetricResult

ROI: +58.46%

Net Profit: $5,845.82 (from $10,000 starting capital)

Profit Factor: 1.76

Total Trades: 89

Winning Rate: 42.7%

Largest Win / Loss: $935.44 / -$236.41

Average Trade: $65.68

Max Consecutive Wins / Losses: 5 / 8

Drawdown (approx.): Low to Moderate


🔍 Trade Behavior

  • Balanced performance across long and short trades (Long: $3,039 | Short: $2,806)
  • Works efficiently under typical GBPJPY volatility environments


🧩 Recommended Usage

  • Suitable for both semi-automated and fully automated traders
  • Best run on ECN accounts with low spreads
  • Ideal for medium-risk traders looking for sustainable, consistent growth over time


🧭 Developer’s Note

I’m a fintech student exploring algorithmic trading and crowdfunding innovation. This strategy represents months of testing and optimization around Bollinger dynamics and volatility filters. My goal is to make data-driven trading accessible and scalable for everyone.

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