Dynamic Support Resistance Price Action Trading System

Pine ScriptMean reversion Trend following Volatility Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 103 lines
Parameters: 0
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is a trading system based on price action and dynamic support/resistance levels, executing trades near key price levels when specific candlestick patterns emerge. The system utilizes a 16-period dynamic support/resistance calculation method, combined with four classic reversal candlestick patterns - Hammer, Shooting Star, Doji, and Pin Bar to capture potential market reversals. The strategy employs fixed percentage take-profit and stop-loss levels for risk management and uses a sensitivity parameter to control entry signal strictness.

Strategy Principles

The core of the strategy lies in dynamically calculating support and resistance levels to establish price movement boundaries. When price approaches these key levels, the system looks for specific candlestick patterns as reversal signals. Entry conditions require pattern formation within 1.8% (default sensitivity) of support/resistance levels. The system implements a 35% equity management rule with 16% stop-loss and 9.5% take-profit, effectively controlling risk at around 5.6% of total equity per trade. The strategy is implemented in Pine Script with complete trade management functionality and visualization.

Strategy Advantages

Combines two most reliable elements of technical analysis: price patterns and support/resistance, enhancing signal reliability
Uses dynamically calculated support/resistance levels, adapting to changing market conditions
Implements strict money management and risk control measures to prevent significant drawdowns
Clear strategy logic with adjustable parameters, facilitating optimization for different market conditions
Clear entry signals without subjective judgment, suitable for automated trading

Strategy Risks

Support/resistance effectiveness may decrease in highly volatile markets
Relatively wide stop-loss (16%) may lead to significant losses in volatile conditions
Sensitivity parameter settings significantly impact trading frequency and accuracy
Relying solely on price patterns may miss other important market signals
Need to consider trading costs' impact on strategy returns

Optimization Directions

Introduce volume as a confirmation indicator to improve signal reliability
Develop adaptive sensitivity parameters that adjust dynamically based on market volatility
Optimize stop-loss settings, consider implementing trailing stops or stepped stop-loss plans
Add trend filters to avoid reversal trades during strong trends
Develop dynamic position sizing system adjusting trade size based on market conditions

Summary

This price action-based trading strategy provides traders with a systematic trading approach by combining dynamic support/resistance levels with classic reversal patterns. The strategy's strengths lie in its clear logic and controllable risk, though continuous optimization based on actual trading results is necessary. Traders are advised to conduct thorough backtesting and parameter optimization before live trading, and customize the strategy based on market experience.

Source Pine Script

/*backtest
start: 2024-11-26 00:00:00
end: 2024-12-03 00:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © felipemiransan

//@version=5
strategy("Price Action Strategy", overlay=true)

// Settings
length = input.int(16, title="Support and Resistance Length")
sensitivity = input.float(0.018, title="Sensitivity")

// Stop Loss and Take Profit
stop_loss_pct = input.float(16, title="Stop Loss percentage", minval=0.1) / 100
take_profit_pct = input.float(9.5, title="Take Profit percentage", minval=0.1) / 100

// Function to identify a Hammer
isHammer() =>
    body = close - open
    price_range = high - low
    lower_shadow = open - low
    upper_shadow = high - close
    body > 0 and lower_shadow > body * 2 and upper_shadow < body * 0.5 and price_range > 0

// Function to identify a Shooting Star
isShootingStar() =>
    body = open - close
    price_range = high - low
    lower_shadow = close - low
    upper_shadow = high - open
    body > 0 and upper_shadow > body * 2 and lower_shadow < body * 0.5 and price_range > 0

// Function to identify a Doji
isDoji() =>
    body = close - open
    price_range = high - low
    math.abs(body) < (price_range * 0.1)  // Doji has a small body

// Function to identify a Pin Bar
isPinBar() =>
    body = close - open
    price_range = high - low
    lower_shadow = open - low
    upper_shadow = high - close
    (upper_shadow > body * 2 and lower_shadow < body * 0.5) or (lower_shadow > body * 2 and upper_shadow < body * 0.5)

// Support and resistance levels 
support = ta.lowest(low, length)
resistance = ta.highest(high, length)

// Entry criteria
long_condition = (isHammer() or isDoji() or isPinBar()) and close <= support * (1 + sensitivity)
short_condition = (isShootingStar() or isDoji() or isPinBar()) and close >= resistance * (1 - sensitivity)

// Function to calculate stop loss and take profit (long)
calculate_levels(position_size, avg_price, stop_loss_pct, take_profit_pct) =>
    stop_loss_level = avg_price * (1 - stop_loss_pct)
    take_profit_level = avg_price * (1 + take_profit_pct)
    [stop_loss_level, take_profit_level]

// Function to calculate stop loss and take profit (short)
calculate_levels_short(position_size, avg_price, stop_loss_pct, take_profit_pct) =>
    stop_loss_level = avg_price * (1 + stop_loss_pct)
    take_profit_level = avg_price * (1 - take_profit_pct)
    [stop_loss_level, take_profit_level]

// Buy entry order with label
if (long_condition and strategy.opentrades == 0)
    strategy.entry("Buy", strategy.long)
    pattern = isHammer() ? "Hammer" : isDoji() ? "Doji" : isPinBar() ? "Pin Bar" : ""
    label.new(x=bar_index, y=low, text=pattern, color=color.green, textcolor=color.black, size=size.small)

// Sell entry order with label
if (short_condition and strategy.opentrades == 0)
    strategy.entry("Sell", strategy.short)
    pattern = isShootingStar() ? "Shooting Star" : isDoji() ? "Doji" : isPinBar() ? "Pin Bar" : ""
    label.new(x=bar_index, y=high, text=pattern, color=color.red, textcolor=color.black, size=size.small)

// Stop Loss and Take Profit management for open positions
if (strategy.opentrades > 0)
    if (strategy.position_size > 0)  // Long position
        avg_price_long = strategy.position_avg_price  // Average price of long position
        [long_stop_level, long_take_profit_level] = calculate_levels(strategy.position_size, avg_price_long, stop_loss_pct, take_profit_pct)
        strategy.exit("Exit Long", from_entry="Buy", stop=long_stop_level, limit=long_take_profit_level)
    if (strategy.position_size < 0)  // Short position
        avg_price_short = strategy.position_avg_price  // Average price of short position
        [short_stop_level, short_take_profit_level] = calculate_levels_short(strategy.position_size, avg_price_short, stop_loss_pct, take_profit_pct)
        strategy.exit("Exit Short", from_entry="Sell", stop=short_stop_level, limit=short_take_profit_level)

// Visualization of Support and Resistance Levels
plot(support, title="Support", color=color.green, linewidth=2)
plot(resistance, title="Resistance", color=color.red, linewidth=2)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-12-04. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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