Lorenz Classification Trading Strategy: A 76% Win Rate Machine Learning Indicator on TradingView

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Introduction

In the dynamic world of trading, discovering high-probability indicators can be transformative. The Machine Learning Lorenz Classification Indicator stands out with its remarkable 76% win rate across multiple asset classes. This article explores its strategic implementation, backtesting results, and optimization techniques for stocks (Nvidia), cryptocurrencies (Bitcoin), and forex (EUR/JPY).


Key Features of the Lorenz CN Indicator

Optimal Settings Configuration:

ParameterValue
Neighbors Count2
Color Compression2
Lookback Window16
Regression Level35
MR FilterEnabled

Trading Rules Breakdown

Long Entry Criteria

  1. Lorenz CN generates a buy signal.
  2. Corresponding candlestick is bullish (closes above EMA 200).
  3. Stop-loss: Recent swing low.
  4. Take-profit: Scale-out or fixed ratio (e.g., 2:1 risk-reward).

Short Entry Criteria

  1. Lorenz CN shows a sell signal.
  2. Associated candlestick is bearish (closes below EMA 200).
  3. Stop-loss: Nearest swing high.
  4. Take-profit: Same as long entries.

Backtest Results (2022–2024)

Top Performing Assets

  1. Nvidia (NVDA) – 30min Chart

    • Trades: 51
    • Win Rate: 76.47%
    • Profit: $377,111
    • Max Drawdown: $38,230
  2. Bitcoin (BTC) – 1hr Chart

    • Trades: 71
    • Win Rate: 67.61%
    • Profit: $268,861
  3. EUR/JPY – 15min Chart

    • Trades: 61
    • Win Rate: 60.66%
    • Profit: $134,168

Enhancing Your Trading Workflow

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FAQs

Q1: What timeframes work best with this strategy?
A: 30min–1hr charts show optimal consistency across assets.

Q2: Does leverage affect strategy performance?
A: Backtests assumed spot trading; leverage requires additional risk management.

Q3: How often does the indicator generate signals?
A: Frequency depends on volatility—expect 2–5 weekly signals in active markets.

Q4: Can I automate this strategy?
A: Yes, via TradingView alerts or API integrations with supported brokers.

Q5: What’s the recommended risk per trade?
A: 1–2% of capital aligns with the strategy’s drawdown characteristics.


Conclusion

The Lorenz Classification Strategy demonstrates exceptional reliability when properly configured. For crypto traders, combining this indicator with 👉 OKX’s integrated trading tools creates a seamless execution environment. Remember to:

  1. Conduct asset-specific backtests
  2. Adhere to strict risk parameters
  3. Continuously optimize settings

Always trade with discipline—no strategy guarantees 100% success.