Overview
The Multi-Trend Confirmation RSI-SuperTrend Dynamic Trading System is a comprehensive quantitative trading strategy that integrates multiple technical indicators. This strategy combines RSI (Relative Strength Index), EMA (Exponential Moving Average), SuperTrend, Donchian Channels, and volume data to form a complete trend identification and entry system. Through cross-confirmation of multiple indicators, the strategy aims to capture strong trend movements while using multi-layered filtering conditions to reduce false signals and improve trading accuracy and stability. This strategy is suitable for medium to long-term trading and performs well in both oscillating markets and clear trend markets.

Strategy Principles
The core principle of this strategy is to identify strong trends and execute trades through multiple indicator confirmations. The specific implementation logic is as follows:

Indicator Calculation Layer:

• Short-term EMA (8-period) and medium-term EMA (21-period) for identifying price momentum
• 14-period RSI for measuring relative price strength and weakness
• SuperTrend indicator (parameters 2.0 and 10) for confirming trend direction
• 10-period volume moving average for identifying volume anomalies
• 20-period Donchian Channel for tracking price range movements
• 50-period EMA for confirming long-term trend direction

Trade Signal Generation:

• Long entry conditions: RSI crosses above 50, Donchian middle band rising, price above 50 EMA, SuperTrend bullish direction (direction=1), and volume spike
• Short entry conditions: RSI crosses below 50, Donchian middle band falling, price below 50 EMA, SuperTrend bearish direction (direction=-1), and volume spike
• Exit condition: Price crosses the 21-period EMA

Execution Logic:

• When entry conditions are met, the strategy opens a full position in the corresponding direction
• When exit conditions are met, the strategy closes all positions

The unique aspect of this strategy is that it requires multiple conditions to be satisfied simultaneously to trigger a trade, and this "multiple confirmation" mechanism effectively reduces the generation of false signals.

Strategy Advantages

1. Multiple Trend Confirmations: The strategy combines market information from multiple dimensions, including momentum (RSI), trend (EMA, SuperTrend), price structure (Donchian Channel), and volume. Trades are only executed when multiple indicators provide confirmation, greatly reducing the false signal rate.

2. Strong Adaptability: By integrating short-term, medium-term, and long-term indicators, the strategy can adapt to different market environments and find trading opportunities in both oscillating markets and clear trends.

3. Volume Confirmation: The strategy incorporates a volume anomaly detection mechanism, entering positions only when volume significantly increases (1.5 times above the 10-period average), helping to capture genuine trend breakouts.

4. Dynamic Stop Loss: The SuperTrend indicator inherently possesses adaptive characteristics, dynamically adjusting according to market volatility, providing an implicit risk control mechanism for the strategy.

5. Clear Exit Mechanism: The exit strategy based on price crossing the EMA is straightforward and can exit positions in the early stages of trend reversal, protecting already gained profits.

6. Fully Automated: The strategy is designed to run fully automated without human intervention, particularly suitable for traders who do not have time to closely monitor the market.

Strategy Risks

1. False Breakout Risk: Despite multiple filtering conditions, the strategy may still generate false breakout signals in high-volatility markets, leading to erroneous trades. A solution is to consider adding confirmation periods, requiring signals to persist for multiple periods before executing trades.

2. Full Position Trading Risk: The strategy defaults to using 100% of funds for trading, which may bring significant drawdown risk in extreme market conditions. It is advisable to adjust position sizing according to individual risk tolerance or implement a phased entry strategy.

3. Delayed Trend Reversal Identification: The exit mechanism based on moving averages may be slow to react during major trend reversals, resulting in some profit giveback. Consider adding more sensitive exit conditions, such as ATR-based take-profit strategies.

4. Parameter Sensitivity: The strategy uses multiple fixed parameters (such as EMA periods, RSI period, SuperTrend parameters), and different markets and timeframes may require different parameter settings. It is recommended to conduct thorough parameter optimization and backtesting before live trading.

5. Consecutive Loss Risk: In oscillating markets or periods with unclear trends, the strategy may generate consecutive losing signals. Consider adding market environment filters to pause trading in unfavorable market conditions.

Strategy Optimization Directions

1. Dynamic Parameter Adjustment: Introduce an adaptive parameter mechanism that automatically adjusts EMA, RSI, and SuperTrend parameters based on market volatility, allowing the strategy to better adapt to different market environments. This can be implemented based on ATR or historical volatility metrics.

2. Phased Entry and Exit: Improve entry and exit logic by adopting phased position building and phased position closing strategies to reduce single-point risk and optimize the overall equity curve. For example, allocate different position sizes based on trend strength.

3. Time Filters: Add time filtering conditions to avoid trading during known high-volatility periods (such as important economic data releases, major market openings and closings), reducing the probability of being affected by abnormal fluctuations.

4. Stop Loss Optimization: Add explicit stop-loss mechanisms, such as ATR-based dynamic stop-losses or key support/resistance level stop-losses, rather than relying solely on EMA crossover exits, improving risk management precision.

5. Market Environment Classification: Introduce market environment classification mechanisms to apply different trading rules in different types of markets. For example, use trailing stops in clear trends and more conservative entry criteria in oscillating markets.

6. Indicator Weighting System: Assign weights to different indicators and build a comprehensive scoring system that triggers trading signals only when the composite score exceeds a specific threshold, rather than simple condition judgments, making the decision-making process more quantitative and refined.

Summary
The Multi-Trend Confirmation RSI-SuperTrend Dynamic Trading System is a well-designed and logically strong quantitative trading strategy that constructs a complete trading decision framework by integrating the advantages of multiple technical indicators. The core strengths of the strategy lie in its multiple confirmation mechanisms and volume filtering conditions, effectively reducing the rate of false signals. Its main risks come from fixed parameters and full position trading mode. By implementing the suggested optimization measures, such as dynamic parameter adjustment, phased trading, and more refined risk management, this strategy has the potential to achieve more stable and excellent performance in various market environments. This multi-layered confirmation mechanism is particularly applicable for medium to long-term traders seeking high-quality trading signals, especially in markets with significant volatility but clear trends.

Strategy source code

/*backtest
start: 2024-04-26 00:00:00
end: 2025-03-15 00:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"SOL_USDT"}]
*/

//@version=5
strategy("Nirvana Mode PRO v2 - FULL AUTO", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100, calc_on_every_tick=true)

// === Indicators ===
emaFast = ta.ema(close, 8)
emaSlow = ta.ema(close, 21)
rsi = ta.rsi(close, 14)
[supertrend, direction] = ta.supertrend(2.0, 10)
volAvg = ta.sma(volume, 10)
volSpike = volume > volAvg * 1.5

donchianUpper = ta.highest(high, 20)
donchianLower = ta.lowest(low, 20)
donchianMiddle = (donchianUpper + donchianLower) / 2

donchianUpSlope = donchianMiddle > donchianMiddle[1]
donchianDownSlope = donchianMiddle < donchianMiddle[1]

magicTrendUp = close > ta.ema(close, 50)
magicTrendDown = close < ta.ema(close, 50)

// === Long Conditions ===
longSignal = ta.crossover(rsi, 50) and donchianUpSlope and magicTrendUp

// === Short Conditions ===
shortSignal = ta.crossunder(rsi, 50) and donchianDownSlope and magicTrendDown

// === M1 Supertrend Trigger ===
longEntry = longSignal and direction == 1 and volSpike
shortEntry = shortSignal and direction == -1 and volSpike

exitCond = ta.cross(close, emaSlow)

// === Test Mode ===
testLong = input.bool(false, title="Manual LONG signal trigger")
testShort = input.bool(false, title="Manual SHORT signal trigger")
testExit = input.bool(false, title="Manual EXIT signal trigger")

// === Open/Close Positions ===
if (longEntry or testLong)
    strategy.entry("ENTER-LONG", strategy.long, comment="ENTER-LONG_BITGET_BTCUSDT_Nirvana Mode PRO v2_15M")

if (shortEntry or testShort)
    strategy.entry("ENTER-SHORT", strategy.short, comment="ENTER-SHORT_BITGET_BTCUSDT_Nirvana Mode PRO v2_15M")

if (exitCond or testExit)
    strategy.close_all(comment="EXIT-ALL_BITGET_BTCUSDT_Nirvana Mode PRO v2_15M")

// === Alert Conditions ===
alertcondition(longEntry, title="Long Signal", message="ENTER-LONG_BITGET_BTCUSDT_Nirvana Mode PRO v2_15M")
alertcondition(shortEntry, title="Short Signal", message="ENTER-SHORT_BITGET_BTCUSDT_Nirvana Mode PRO v2_15M")
alertcondition(exitCond, title="Exit Signal", message="EXIT-ALL_BITGET_BTCUSDT_Nirvana Mode PRO v2_15M")

Strategy parameters

The original address: Multi-Trend Confirmation RSI-SuperTrend Dynamic Trading System