
This strategy is a multi-level dynamic cost averaging (DCA) trading system that combines the Relative Strength Index (RSI) and Average True Range (ATR). It primarily identifies oversold market conditions for staged position building while using ATR to dynamically adjust take-profit levels for swing trading profits. The strategy features risk diversification, cost optimization, and stable returns.
The strategy operates on 4-hour or daily timeframes, with core logic including: 1. Entry signals based on RSI below 30 indicating oversold conditions, allowing up to 4 staged entries 2. Position sizing based on $200 total risk amount, calculating holdings dynamically using 2x ATR 3. Position management using dynamic average cost tracking, calculating real-time average price after multiple entries 4. Take-profit set at 3x ATR above average price, adapting to market volatility 5. Real-time display of average price and take-profit levels through marker lines for visual tracking
The strategy achieves a trading system balancing risk control and stable returns through the combination of RSI and ATR indicators. The staged entry mechanism provides cost optimization possibilities, while the dynamic take-profit design ensures reasonable profit realization. Although some potential risks exist, the strategy’s overall performance will be further improved through appropriate parameter settings and implementation of optimization directions.
/*backtest
start: 2024-02-21 00:00:00
end: 2025-02-18 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Binance","currency":"DOGE_USDT"}]
*/
//@version=6
strategy("DCA-Based Swing Strategy (Risk $200) with Signals", overlay=true)
// === Main Indicators ===
// RSI for identifying oversold conditions
rsi = ta.rsi(close, 14)
// ATR for volatility estimation
atr = ta.atr(14)
// === Strategy Parameters ===
// Risk management
riskPerTrade = 200 // Total risk ($200)
atrRisk = 2 * atr // Risk in dollars per buy (2 ATR)
positionSize = riskPerTrade / atrRisk // Position size (shares)
// DCA Parameters
maxEntries = 4 // Maximum of 4 buys
takeProfitATR = 3 // Take profit: 3 ATR
// === Position Management ===
var float avgEntryPrice = na // Average entry price
var int entryCount = 0 // Number of buys
var line takeProfitLine = na // Take profit line
var line avgPriceLine = na // Average entry price line
// === Buy and Sell Conditions ===
buyCondition = rsi < 30 and entryCount < maxEntries // Buy when oversold
if (buyCondition)
strategy.entry("DCA Buy", strategy.long, qty=positionSize)
// Update the average entry price
avgEntryPrice := na(avgEntryPrice) ? close : (avgEntryPrice * entryCount + close) / (entryCount + 1)
entryCount += 1
// Display "BUY" signal on the chart
label.new(bar_index, low, "BUY", style=label.style_label_up, color=color.green, textcolor=color.white, size=size.normal)
// Update lines for average entry price and take profit
if (not na(takeProfitLine))
line.delete(takeProfitLine)
if (not na(avgPriceLine))
line.delete(avgPriceLine)
takeProfitPrice = avgEntryPrice + takeProfitATR * atr
// Sell condition: Take profit = 3 ATR from average entry price
takeProfitPrice = avgEntryPrice + takeProfitATR * atr
if (close >= takeProfitPrice and entryCount > 0)
strategy.close("DCA Buy")
// Reset parameters after closing
avgEntryPrice := na
entryCount := 0
// Remove lines after selling
if (not na(takeProfitLine))
line.delete(takeProfitLine)
if (not na(avgPriceLine))
line.delete(avgPriceLine)