Source: YouTube URL: https://www.youtube.com/watch?v=cShmWoe9tvY Date: 2025-10-11 Duration: 6:18
This video concludes a three-part series testing bold trading strategy claims, specifically evaluating MACD indicator settings for crypto trading. The dual-MACD strategy uses histogram-only settings (fast: 13/21, slow: 100/200/50) to detect pullbacks and overall trends. While backtesting shows marginally better results than CCI and steady growth patterns, the strategy suffers from ~50% drawdown and false signals around zero-line crossings. The verdict: These strategies can work but require additional confirmation signals, proper exit rules, and extensive forward testing—contradicting the “never fail” claims.
The video presents the third and final test of trading strategies from a source video making extraordinary claims about “never failing” indicators. This MACD-based approach deviates from traditional MACD usage by focusing exclusively on histogram values rather than signal line crossovers.
Technical Setup: - First MACD: Fast length 13, slow length 21 (pullback detection) - Second MACD: Fast length 100, slow length 200, smoothing 50 (trend detection) - Both indicators merged onto single window for visual clarity - Histogram-only analysis—signal lines not used
Long Trade Logic: 1. Slow MACD histogram must be above zero line (bullish trend confirmation) 2. Fast MACD drops below zero (indicating pullback/retracement) 3. Fast MACD crosses back above zero (pullback ending, resuming uptrend) 4. Enter long position at this crossover
Short Trade Logic: 1. Slow MACD histogram below zero line (bearish trend confirmation) 2. Fast MACD rises above zero (counter-trend pullback) 3. Fast MACD crosses back below zero (resuming downtrend) 4. Enter short position at this crossover
The Python-based automated backtesting and TradingView strategy scripts revealed several important performance metrics:
Positive Indicators: - Marginally better results than CCI indicator from previous video - Steady equity curve with gradual incline rather than volatile spikes - Performance numbers “quite normal for such simple trend trading strategies” - Predictable growth pattern suggests consistency over time
Concerning Indicators: - Maximum drawdown approaching 50%—a psychologically and financially devastating level - Less certain than CCI indicator due to histogram volatility - Equity curve less impressive than CCI’s big trend-catching waves - Slower growth compared to CCI’s more aggressive gains
Risk Assessment: The creator emphasizes that 50% drawdowns aren’t just historical artifacts—they’re likely to recur in future trading. This level of drawdown means a $10,000 account could drop to $5,000, requiring 100% gains just to break even. Many traders would be forced out psychologically or financially before recovery occurs.
A critical weakness emerges when visualizing the strategy on Dogecoin charts: histogram zigzagging around the zero line generates numerous false signals.
Example Scenario: During bearish trends, the fast histogram oscillates above and below zero multiple times, creating frequent “potential short signals” that don’t develop into profitable trades. This behavior results from: - High sensitivity of shorter timeframe MACD (13/21 settings) - Choppy market conditions without clear directional movement - Lack of momentum filters to distinguish genuine reversals from noise
The creator suggests several enhancement approaches to address the strategy’s limitations:
1. Indicator Setting Adjustments: - Fine-tune MACD lengths to reduce zero-line zigzagging - Increase fast MACD parameters for less sensitive pullback detection - Adjust smoothing factors to filter out market noise
2. Entry Signal Refinement: - Use pullbacks as additional confirmation rather than sole trigger - Implement standard cross-down entry mode for clearer signals - Add third confirmation indicator (volume, RSI, support/resistance)
3. Exit Strategy Development: Since the original video provides no exit rules, traders must create their own: - Aggressive exits: Close on any fast MACD reversal around zero - Trend-following exits: Hold until slow MACD trend reversal - Risk-based exits: Fixed stop-loss and take-profit based on R:R ratios
4. Asset-Specific Testing: The Dogecoin example shows promise with proper settings, but results vary significantly across different cryptocurrencies. Traders must: - Backtest on their preferred trading pairs - Optimize parameters for specific asset volatility characteristics - Conduct forward testing before live deployment
Across all three videos testing RSI, CCI, and MACD strategies:
RSI (Video 1): Failed to meet expectations—poor performance CCI (Video 2): Showed promise—caught major trend waves effectively MACD (Video 3): Mixed results—steady growth but high drawdown
Final Verdict: The “these settings NEVER FAIL” and “impossible to lose” claims are misleading marketing hyperbole. However, the strategies aren’t worthless: - CCI and MACD show genuine potential after optimization - All strategies require additional confirmation signals - Proper exit rules are essential (absent from original video) - Forward testing is mandatory before real capital deployment - Moving average overlays on RSI might salvage that approach
The creator’s honest assessment: “These strategies do indeed not fail, but only after some real good testing.” This acknowledges that raw strategies need substantial work before becoming reliably profitable systems.
The creator provides both Python backtesting scripts and TradingView Pine Script implementations through their Patreon, enabling: - Automated backtesting across multiple timeframes and assets - Visual trade representation on charts - Parameter optimization capabilities - Access to additional strategies and an algorithmic trading ebook
The video also promotes Bybit.eu as a MiFID-licensed exchange for European traders, offering affiliate bonuses through provided links.
“These settings never fail. Impossible to lose with this strategy.”
“Unfortunately, these draw downs are looking a little bit worrisome and almost 50% draw down is never nice to see because you can expect these kinds of draw downs in the future as well.”
“These false signals can only be prevented by additional trading rules.”
“The CCI and MACD rules are certainly worth trying out further and doing some more forward tests is also advisable.”
“So, in a way, these strategies do indeed not fail, but only after some real good testing.”
本影片為三部曲系列最終章，測試大膽宣稱的交易策略，特別評估 MACD 指標設置在加密貨幣交易中的效果。雙 MACD 策略僅使用柱狀圖（快速：13/21，慢速：100/200/50）來偵測回調與整體趨勢。回測顯示表現略優於 CCI 且具穩定成長模式，但策略面臨約 50% 最大回撤和零線附近假信號問題。結論：這些策略可行，但需要額外確認信號、適當出場規則和大量前瞻測試——與「永不失敗」宣稱矛盾。
影片呈現第三個也是最後一個來自某來源影片的交易策略測試，該來源對「永不失敗」指標做出非凡宣稱。這個基於 MACD 的方法偏離傳統 MACD 使用方式，專注於柱狀圖數值而非信號線交叉。
技術設定： - 第一個 MACD：快速長度 13，慢速長度 21（回調偵測） - 第二個 MACD：快速長度 100，慢速長度 200，平滑因子 50（趨勢偵測） - 兩個指標合併至單一視窗以提升視覺清晰度 - 僅分析柱狀圖——不使用信號線
做多交易邏輯： 1. 慢速 MACD 柱狀圖必須在零線之上（確認看漲趨勢） 2. 快速 MACD 跌破零線（顯示回調/回撤） 3. 快速 MACD 重新穿越零線向上（回調結束，恢復上升趨勢） 4. 在此交叉點進場做多
做空交易邏輯： 1. 慢速 MACD 柱狀圖低於零線（確認看跌趨勢） 2. 快速 MACD 升至零線之上（反趨勢回調） 3. 快速 MACD 重新向下穿越零線（恢復下降趨勢） 4. 在此交叉點進場做空
基於 Python 的自動回測和 TradingView 策略腳本揭示了幾個重要的性能指標：
正向指標： - 略優於前一影片的 CCI 指標結果 - 穩定的權益曲線呈現逐漸上升而非劇烈波動 - 性能數字「對於這類簡單趨勢交易策略相當正常」 - 可預測的成長模式顯示時間推移的一致性
令人擔憂指標： - 最大回撤接近 50%——心理和財務上毀滅性的水平 - 由於柱狀圖波動性，不如 CCI 指標確定 - 權益曲線不如 CCI 的大趨勢捕捉波動令人印象深刻 - 相比 CCI 更積極的收益，成長較慢
風險評估： 創作者強調 50% 回撤不僅是歷史數據——在未來交易中很可能再次發生。這種回撤水平意味著 10,000 美元帳戶可能跌至 5,000 美元，需要 100% 收益才能回本。許多交易者在復原前會因心理或財務因素被迫退出。
在狗狗幣圖表上視覺化策略時出現關鍵弱點：柱狀圖在零線附近鋸齒狀波動產生大量假信號。
範例情境： 在看跌趨勢期間，快速柱狀圖多次在零線上下振盪，產生頻繁的「潛在做空信號」，但這些信號並未發展成有利可圖的交易。此行為源自： - 較短時間框架 MACD（13/21 設置）的高靈敏度 - 缺乏明確方向性移動的震盪市場條件 - 缺乏動能過濾器來區分真正反轉與雜訊
創作者建議幾種增強方法來解決策略的限制：
1. 指標設置調整： - 微調 MACD 長度以減少零線鋸齒狀波動 - 增加快速 MACD 參數以降低回調偵測靈敏度 - 調整平滑因子以過濾市場雜訊
2. 進場信號優化： - 將回調作為額外確認而非唯一觸發條件 - 實施標準向下交叉進場模式以獲得更清晰信號 - 添加第三確認指標（成交量、RSI、支撐/阻力）
3. 出場策略開發： 由於原始影片未提供出場規則，交易者必須自行創建： - 積極出場：在快速 MACD 零線附近任何反轉時平倉 - 趨勢跟隨出場：持有直到慢速 MACD 趨勢反轉 - 基於風險的出場：基於風險報酬比的固定止損和止盈
4. 資產特定測試： 狗狗幣範例顯示適當設置下的潛力，但不同加密貨幣的結果差異很大。交易者必須： - 在偏好的交易對上進行回測 - 針對特定資產波動特徵優化參數 - 在實盤部署前進行前瞻測試
在測試 RSI、CCI 和 MACD 策略的三個影片中：
RSI（影片 1）：未達預期——表現不佳 CCI（影片 2）：顯示潛力——有效捕捉主要趨勢波動 MACD（影片 3）：結果參半——穩定成長但高回撤
最終判決： 「這些設置永不失敗」和「不可能虧損」的宣稱是誤導性的行銷誇大說法。然而，策略並非毫無價值： - CCI 和 MACD 經過優化後顯示真正潛力 - 所有策略都需要額外確認信號 - 適當的出場規則至關重要（原始影片缺失） - 投入實際資金前前瞻測試是必需的 - RSI 上的移動平均線疊加可能挽救該方法
創作者的誠實評估：「這些策略確實不會失敗，但僅在經過一些真正良好的測試後。」這承認原始策略在成為可靠盈利系統前需要大量工作。
創作者通過 Patreon 提供 Python 回測腳本和 TradingView Pine Script 實現，支援： - 跨多個時間框架和資產的自動回測 - 圖表上的視覺化交易表示 - 參數優化能力 - 訪問額外策略和演算法交易電子書
影片也推廣 Bybit.eu 作為歐洲交易者的 MiFID 許可交易所，通過提供的連結提供聯盟獎金。
“這些設置永不失敗。使用這個策略不可能虧損。”
“不幸的是，這些回撤看起來有點令人擔憂，近 50% 的回撤永遠不是好事，因為你可以預期未來也會出現這類回撤。”
“這些假信號只能通過額外的交易規則來防止。”
“CCI 和 MACD 規則確實值得進一步嘗試，也建議進行更多前瞻測試。”
“所以，在某種程度上，這些策略確實不會失敗，但僅在經過一些真正良好的測試後。”
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