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Dynamic Signal Line Trend Following and Volatility Filtering Strategy

Author: ChaoZhang, Date: 2024-11-29 17:02:33
Tags: DSLATRRSIZLEMASMAEMA

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Overview

This strategy is a comprehensive trading system that combines Dynamic Signal Lines (DSL), volatility, and momentum indicators. It effectively identifies market trends through dynamic thresholds and adaptive volatility bands, while using momentum indicators for signal filtering to achieve precise trade timing. The system incorporates a complete risk management mechanism, including dynamic stop-loss and profit targets based on risk-reward ratios.

Strategy Principles

The core logic is built on three main components:

First, the Dynamic Signal Line system calculates dynamic upper and lower channel lines based on moving averages. These channel lines automatically adjust their position based on recent market highs and lows, achieving adaptive trend tracking. The system also incorporates ATR-based dynamic volatility bands to confirm trend strength and set stop-loss positions.

Second, the momentum analysis system uses an RSI indicator optimized with Zero-Lag Exponential Moving Average (ZLEMA). By applying the dynamic signal line concept to RSI, the system can more accurately identify overbought and oversold regions and generate momentum breakthrough signals.

Third, the signal integration mechanism. Trade signals must simultaneously satisfy both trend confirmation and momentum breakthrough conditions to trigger. Long entry requires price breakthrough above the upper band and maintenance above the channel, while RSI breaks through the lower dynamic signal line. Short signals require the opposite conditions to be met simultaneously.

Strategy Advantages

  1. Strong Adaptability: Dynamic signal lines and volatility bands automatically adjust to market conditions, enabling the strategy to adapt to different market environments.
  2. False Signal Filtering: By requiring dual confirmation of trend and momentum, significantly reduces the probability of false signals.
  3. Comprehensive Risk Management: Integrates ATR-based dynamic stop-loss and profit targets based on risk-reward ratios, achieving systematic risk control.
  4. Flexible Customization: Strategy parameters can be optimized for different markets and time periods.

Strategy Risks

  1. Trend Reversal Risk: During severe market reversals, dynamic signal line adjustments may not be timely enough, leading to larger drawdowns.
  2. Range-Bound Market Risk: In range-bound markets, frequent breakouts may result in multiple stop-losses.
  3. Parameter Sensitivity: Strategy performance is sensitive to parameter settings, improper parameters may affect strategy effectiveness.

Strategy Optimization Directions

  1. Market Environment Recognition: Add market environment classification mechanism to use different parameter settings in different market states.
  2. Dynamic Parameter Optimization: Introduce adaptive parameter adjustment mechanism to automatically optimize signal line and volatility band parameters based on market volatility.
  3. Multiple Timeframe Analysis: Integrate signals from multiple timeframes to improve trading decision reliability.
  4. Volatility Adaptation: Adjust stop-loss ranges and risk-reward ratios during high volatility periods to improve risk-adjusted returns.

Conclusion

This strategy achieves effective market trend capture through innovative combination of dynamic signal lines and momentum indicators. The comprehensive risk management mechanism and signal filtering system give it strong practical application value. Through continuous optimization and parameter adjustment, the strategy can maintain stable performance in different market environments. While certain risk points exist, they are controllable through reasonable parameter settings and risk control measures.


/*backtest
start: 2024-10-01 00:00:00
end: 2024-10-31 23:59:59
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Scriptâ„¢ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © DailyPanda

//@version=5
strategy("DSL Strategy [DailyPanda]",
     initial_capital = 2000,
     commission_value=0.00,
     slippage=3,
     overlay = true)

//--------------------------------------------------------------------------------------------------------------------
// USER INPUTS
//--------------------------------------------------------------------------------------------------------------------

// DSL Indicator Inputs CP
int   len         = input.int(34, "Length", group="CP")      // Length for calculating DSL
int   offset      = input.int(30, "Offset", group="CP")      // Offset for threshold levels
float width       = input.float(1, "Bands Width", step = 0.1, maxval = 2, minval = 0.5, group="CP") // Width for ATR-based bands
float risk_reward = input.float(1.5, "Risk Reward", group="Risk Mgmt") // Risk Reward ratio

// Colors for upper and lower trends
color upper_col = input.color(color.lime, "+", inline = "col")
color lower_col = input.color(color.orange, "-", inline = "col")

// DSL-BELUGA
len_beluga  = input.int(10, "Beluga Length", group="BELUGA")
dsl_mode_inp = input.string("Fast", "DSL Lines Mode", options=["Fast", "Slow"], group="BELUGA")
dsl_mode    = dsl_mode_inp == "Fast" ? 2 : 1

// Colors for DSL-BELUGA
color color_up = #8BD8BD
color color_dn = #436cd3

i_lossPct = input.int(defval=100, title="% max day DD", minval=1, maxval=100, step=1, group="Risk Management")
i_goal = input.bool(title="Enable Daily Goal", defval=false, group="Risk Management")
i_goalPct = input.int(defval=4, title="% Daily Goal", minval=1, step=1, group="Risk Management")


//############################## RISK MANAGEMENT ##############################
// Set maximum intraday loss to our lossPct input
// strategy.risk.max_intraday_loss(i_lossPct, strategy.percent_of_equity)
//strategy.risk.max_intraday_loss(value=1200, type=strategy.cash)

// Store equity value from the beginning of the day
eqFromDayStart = ta.valuewhen(ta.change(dayofweek) > 0, strategy.equity, 0)
// Calculate change of the current equity from the beginning of the current day
eqChgPct = 100 * ((strategy.equity - eqFromDayStart - strategy.openprofit) / (strategy.equity-strategy.openprofit))
f_stopGain = eqChgPct >= i_goalPct and i_goal ? true : false


//--------------------------------------------------------------------------------------------------------------------
// INDICATOR CALCULATIONS
//--------------------------------------------------------------------------------------------------------------------

// Function to calculate DSL lines based on price
dsl_price(float price, int len) =>
    // Initialize DSL lines
    float dsl_up = na
    float dsl_dn = na
    float sma    = ta.sma(price, len)

    // Dynamic upper and lower thresholds calculated with offset
    float threshold_up = ta.highest(len)[offset] 
    float threshold_dn = ta.lowest(len)[offset] 

    // Calculate the DSL upper and lower lines based on price compared to the thresholds
    dsl_up := price > threshold_up ? sma : nz(dsl_up[1]) 
    dsl_dn := price < threshold_dn ? sma : nz(dsl_dn[1])

    // Return both DSL lines
    [dsl_up, dsl_dn]

// Function to calculate DSL bands based on ATR and width multiplier
dsl_bands(float dsl_up, float dsl_dn) =>
    float atr = ta.atr(200) * width // ATR-based calculation for bands
    float upper = dsl_up - atr       // Upper DSL band
    float lower = dsl_dn + atr       // Lower DSL band

    [upper, lower]

// Get DSL values based on the closing price
[dsl_up, dsl_dn] = dsl_price(close, len)

// Calculate the bands around the DSL lines
[dsl_up1, dsl_dn1] = dsl_bands(dsl_up, dsl_dn)


//--------------------------------------------------------------------------------------------------------------------
// DSL-BELUGA INDICATOR CALCULATIONS
//--------------------------------------------------------------------------------------------------------------------

// Calculate RSI with a period of 10
float RSI = ta.rsi(close, 10)

// Zero-Lag Exponential Moving Average function
zlema(src, length) =>
    int   lag      = math.floor((length - 1) / 2)
    float ema_data = 2 * src - src[lag]
    float ema2     = ta.ema(ema_data, length)
    ema2

// Discontinued Signal Lines function
dsl_lines(src, length)=>
    float up  = 0.
    float dn  = 0.
    up := (src > ta.sma(src, length)) ? nz(up[1]) + dsl_mode / length * (src - nz(up[1])) : nz(up[1])  
    dn := (src < ta.sma(src, length)) ? nz(dn[1]) + dsl_mode / length * (src - nz(dn[1])) : nz(dn[1])
    [up, dn]

// Calculate DSL lines for RSI
[lvlu, lvld] = dsl_lines(RSI, len_beluga)

// Calculate DSL oscillator using ZLEMA of the average of upper and lower DSL Lines
float dsl_osc = zlema((lvlu + lvld) / 2, 10)

// Calculate DSL Lines for the oscillator
[level_up, level_dn] = dsl_lines(dsl_osc, 10)

// Detect crossovers for signal generation
bool up_signal = ta.crossover(dsl_osc, level_dn) and dsl_osc < 55
bool dn_signal = ta.crossunder(dsl_osc, level_up) and dsl_osc > 50

//--------------------------------------------------------------------------------------------------------------------
// VISUALIZATION
//--------------------------------------------------------------------------------------------------------------------

// Plot the DSL lines on the chart
plot_dsl_up = plot(dsl_up, color=color.new(upper_col, 80), linewidth=1, title="DSL Up")
plot_dsl_dn = plot(dsl_dn, color=color.new(lower_col, 80), linewidth=1, title="DSL Down")

// Plot the DSL bands
plot_dsl_up1 = plot(dsl_up1, color=color.new(upper_col, 80), linewidth=1, title="DSL Upper Band")
plot_dsl_dn1 = plot(dsl_dn1, color=color.new(lower_col, 80), linewidth=1, title="DSL Lower Band")

// Fill the space between the DSL lines and bands with color
fill(plot_dsl_up, plot_dsl_up1, color=color.new(upper_col, 80))
fill(plot_dsl_dn, plot_dsl_dn1, color=color.new(lower_col, 80))

// Plot signals on the chart
plotshape(up_signal, title="Buy Signal", style=shape.triangleup, location=location.belowbar, size=size.tiny, text="Enter")
plotshape(dn_signal, title="Sell Signal", style=shape.triangledown, location=location.abovebar, size=size.tiny, text="Exit")

// Color the background on signal occurrences
bgcolor(up_signal ? color.new(color_up, 90) : na, title="Up Signal Background", editable = false)
bgcolor(dn_signal ? color.new(color_dn, 90) : na, title="Down Signal Background", editable = false)

//--------------------------------------------------------------------------------------------------------------------
// STRATEGY CONDITIONS AND EXECUTION
//--------------------------------------------------------------------------------------------------------------------

// Variables to hold stop loss and take profit prices
var float long_stop_loss_price  = na
var float long_take_profit_price = na
var float short_stop_loss_price = na
var float short_take_profit_price = na
float pos_size = math.abs(strategy.position_size)

// Long Entry Conditions
bool long_condition1 = not na(dsl_up1) and not na(dsl_dn) and dsl_up1 > dsl_dn
bool long_condition2 = open > dsl_up and close > dsl_up and open[1] > dsl_up and close[1] > dsl_up and open[2] > dsl_up and close[2] > dsl_up
bool long_condition3 = up_signal and pos_size == 0
bool long_condition  = long_condition1 and long_condition2 and long_condition3 and (not f_stopGain)

// Short Entry Conditions
bool short_condition1 = not na(dsl_dn1) and not na(dsl_up) and dsl_dn < dsl_up1
bool short_condition2 = open < dsl_dn1 and close < dsl_dn1 and open[1] < dsl_dn1 and close[1] < dsl_dn1 and open[2] < dsl_dn1 and close[2] < dsl_dn1
bool short_condition3 = dn_signal and pos_size == 0
bool short_condition  = short_condition1 and short_condition2 and short_condition3 and (not f_stopGain)

// Long Trade Execution
if (long_condition and not na(dsl_up1))
    long_stop_loss_price := dsl_up1
    float risk = close - long_stop_loss_price
    if (risk > 0)
        long_take_profit_price := close + risk * risk_reward
        strategy.entry("Long", strategy.long)
        strategy.exit("Exit Long", from_entry="Long", stop=long_stop_loss_price, limit=long_take_profit_price)
else if (strategy.position_size <= 0)
    // Reset when not in a long position
    long_stop_loss_price  := na
    long_take_profit_price := na

// Short Trade Execution
if (short_condition and not na(dsl_dn1))
    short_stop_loss_price := dsl_dn1
    float risk = short_stop_loss_price - close
    if (risk > 0)
        short_take_profit_price := close - risk * risk_reward
        strategy.entry("Short", strategy.short)
        strategy.exit("Exit Short", from_entry="Short", stop=short_stop_loss_price, limit=short_take_profit_price)
else if (strategy.position_size >= 0)
    // Reset when not in a short position
    short_stop_loss_price := na
    short_take_profit_price := na

//--------------------------------------------------------------------------------------------------------------------
// PLOTTING STOP LOSS AND TAKE PROFIT LEVELS
//--------------------------------------------------------------------------------------------------------------------

// Plot the stop loss and take profit levels only when in a position
float plot_long_stop_loss   = strategy.position_size > 0 ? long_stop_loss_price : na
float plot_long_take_profit = strategy.position_size > 0 ? long_take_profit_price : na

float plot_short_stop_loss   = strategy.position_size < 0 ? short_stop_loss_price : na
float plot_short_take_profit = strategy.position_size < 0 ? short_take_profit_price : na

plot(plot_long_stop_loss, title="Long Stop Loss", color=color.red, linewidth=2, style=plot.style_linebr, editable=false)
plot(plot_long_take_profit, title="Long Take Profit", color=color.green, linewidth=2, style=plot.style_linebr, editable=false)

plot(plot_short_stop_loss, title="Short Stop Loss", color=color.red, linewidth=2, style=plot.style_linebr, editable=false)
plot(plot_short_take_profit, title="Short Take Profit", color=color.green, linewidth=2, style=plot.style_linebr, editable=false)


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