Multi-Timeframe Zero-Lag Trend Signals Trading Strategy: ZLEMA-Based Dynamic Entry-Exit System

Overview
The Multi-Timeframe Zero-Lag Trend Signals Trading Strategy is a quantitative trading system based on the Zero-Lag Exponential Moving Average (ZLEMA), designed to reduce the lag inherent in traditional moving averages and provide faster, more accurate trend identification signals. This strategy combines volatility channels to identify trend changes and integrates multiple flexible exit mechanisms, including risk-reward ratio exits, profit target exits, ATR-based stop-loss and take-profit, dynamic trailing stops, and EMA crossover exits. Particularly suitable for medium to long-term trading, the strategy can be configured for long-only or bidirectional trading and offers zero-line re-entry options, greatly enhancing the adaptability and risk management capabilities of the trading system.

Strategy Principles
The core principle of this strategy is based on the Zero-Lag Exponential Moving Average (ZLEMA), a technical indicator that improves the responsiveness of moving averages by eliminating or reducing price data lag. The specific implementation steps are as follows:

Zero-Lag Calculation: The strategy first calculates ZLEMA using the formula zlema = ta.ema(src + (src - src[lag]), length), where lag is derived based on half the length, effectively reducing the lag present in traditional EMAs.

Trend Identification Mechanism:

Volatility channels (similar to Bollinger Bands) are added around the ZLEMA, with channel width determined by the highest ATR value multiplied by a factor
When price crosses above the upper band, the trend turns upward (1)
When price crosses below the lower band, the trend turns downward (-1)
The system also provides confirmation functionality through 5 consecutive bars of consistent ZLEMA direction, implemented via the zlemaUpTrend and zlemaDownTrend variables

Diversified Entry Conditions:

Basic long entry: price crosses above the upper band and is within the date range
Advanced long entry: basic conditions plus trend confirmation with ZLEMA rising for 5 consecutive bars
Short entry: price crosses below the lower band and is within the date range (optional feature)
ZLEMA zero-line re-entry: price briefly pulls back and then returns above ZLEMA, while still in an uptrend

Comprehensive Dynamic Exit System:

Risk-reward ratio profit target: calculates target price based on entry price and stop-loss position at a specific risk-reward ratio
ATR-based stop-loss and take-profit: dynamically calculates stop-loss and take-profit positions using ATR multipliers
ATR trailing stop: automatically raises stop-loss position as price moves favorably
Break-even stop-loss: moves stop-loss to entry price when profit reaches a specific risk-reward ratio
Trend reversal exit: automatically exits when trend indicator reverses
EMA exit: exits when price crosses a specific EMA

Strategy Advantages
The Multi-Timeframe Zero-Lag Trend Signals Trading Strategy offers significant advantages:

Reduced Signal Lag: Through ZLEMA technology, the lag of traditional moving averages is reduced, making trend identification more timely and enabling earlier capture of trend starting points.
Comprehensive Risk Management System: Integrates multi-level risk control mechanisms, from fixed stop-losses, ATR dynamic stop-losses, and trailing stops to break-even stop-losses, providing comprehensive protection for different market environments.
Flexible Trading Direction Options: Can be configured as either a long-only strategy or a bidirectional trading strategy, adapting to different market preferences and regulatory environments.
Re-entry Mechanism: Through the ZLEMA zero-line re-entry function, allows re-entry after short-term pullbacks in strong trends, maximizing trend profits.
Diversified Exit Strategies: Provides multiple exit solutions for different market conditions, either locking in profits through profit targets or letting profits run through trailing stops.
Visual Assistance: Through visualization elements such as trend shading, stop-loss lines, take-profit lines, and trend indicators, intuitively displays trading signals and risk management positions.
Detailed Performance Statistics: Integrates trade statistics tables showing key indicators such as win rate, net profit, and maximum drawdown, facilitating strategy evaluation and optimization.

Strategy Risks
Despite its well-designed nature, there are several potential risks that need attention:

Parameter Sensitivity: Core parameters such as ZLEMA length and ATR multipliers significantly impact strategy performance; improper settings may lead to too many or too few signals.
False Signals in Choppy Markets: In oscillating markets without clear trends, frequent false signals may occur, leading to consecutive losses.
Trend Reversal Risk: Although the strategy includes multiple exit mechanisms, in severe trend reversals, it may still suffer significant losses before exiting.
Overfitting Risk: The combination of multiple parameters may lead to overfitting historical data, resulting in poor performance in future market environments.
Infrequent Signals with Longer Periods: When using longer ZLEMA lengths, the strategy may generate fewer trading signals, affecting capital utilization efficiency.
Stop-Loss Width Challenges: ATR-based stops may be too wide in highly volatile markets, leading to excessive single-trade losses; in low-volatility markets, they may be too narrow, triggering frequent exits.

Methods to mitigate these risks include: rigorous parameter backtesting and forward validation, incorporating market state indicators to avoid trading in choppy markets, implementing strict money management rules, and periodically re-optimizing strategy parameters to adapt to market changes.

Strategy Optimization Directions
This strategy has multiple optimization opportunities to further enhance performance:

Dynamic Parameter Adaptation: Develop adaptive mechanisms to automatically adjust ZLEMA length and ATR multipliers based on market volatility, improving strategy adaptability across different market environments.
Market State Filtering: Introduce market state indicators (such as ADX, volatility indicators) to trade only under favorable market conditions, avoiding frequent trading in inefficient, choppy markets.
Multi-Timeframe Confirmation: Incorporate trend direction from higher timeframes, entering only when aligned with the larger trend direction to improve success rates.
Volume Confirmation: Integrate volume indicators as auxiliary confirmation, for example, confirming trend change signals only when accompanied by increased trading volume.
Machine Learning Optimization: Use machine learning algorithms to find optimal parameter combinations and entry timing, particularly training models to predict which signals are more likely to succeed.
Seasonality and Time Filters: Add trading session and calendar filters to avoid inefficient or high-risk trading periods.
Correlated Asset Analysis: Introduce correlation analysis of related assets, enhancing signal credibility when multiple assets confirm the same direction.

These optimization directions can not only improve the strategy's stability and profitability but also reduce risk, making it more suitable for different market environments and individual risk preferences.

Summary
The Multi-Timeframe Zero-Lag Trend Signals Trading Strategy is a comprehensive and flexible quantitative trading system that achieves fast and accurate trend identification through Zero-Lag Exponential Moving Average (ZLEMA) technology and volatility channels, while protecting capital safety through multi-level dynamic risk management mechanisms. This strategy can capture entry opportunities in the early stages of trends and maximize returns through re-entry mechanisms as trends develop, while providing multiple exit strategies adapted to different market environments.

The main advantages of the strategy lie in reducing signal lag, providing a comprehensive risk management system, and offering flexible trading configuration options. However, users need to be aware of potential risks such as parameter sensitivity, false signals in choppy markets, and overfitting. Through market state filtering, multi-timeframe confirmation, and dynamic parameter adaptation, strategy performance can be further enhanced.

As a technical indicator-based quantitative trading system, this strategy is particularly suitable for medium to long-term trend trading across various financial markets. However, any strategy needs to be customized according to individual trading goals, risk tolerance, and market preferences, and applied to actual trading in conjunction with strict money management principles.

Strategy source code

//@version=6
// Quant Trading Pro www.quanttradingpro.com
// #1 Strategy Optimizer on the chrome extension store Quant Trading Strategy Optimizer


strategy(title="Quant Trading Zero Lag Trend Signals (MTF) Strategy", shorttitle="QT0️⃣Zero Lag Signals Strategy", overlay=true, 
     commission_type=strategy.commission.percent, 
     commission_value=0.1, 
     slippage=3, 
     default_qty_type=strategy.percent_of_equity, 
     default_qty_value=100, 
     initial_capital=1000, 
     margin_long=0, 
     margin_short=0)

// === INPUT PARAMETERS ===

// 📌 1️⃣ Main Calculations
length = input.int(70, title="Length", minval=70, maxval=7000)
mult   = input.float(1.2, "Band Multiplier", group="Main Calculations")

// === 📊 Trade Data Toggles ===
showFloatingTable = input.bool(true, "Show Floating Stats Table?", group="Trade Data")
showTradeLog      = input.bool(false, "Show Trade Log Labels on Chart?", group="Trade Data")
enableCSVExport = input.bool(false, "Enable CSV Export", group="Trade Data")

// 📌 ZLEMA Trend Confirmation for Entries
useZlemaTrendConfirm = input.bool(false, "Use ZLEMA Trend Confirmation for entry?", group="Entry Conditions")
reEnterOnLongTrend = input.bool(false, "Re-Enter on Long Trend continuation", group="Entry Conditions")

// 📌 2️⃣ Short Trades
allowShortTrades = input.bool(false, "Allow Short Trades?", group="Short Trades")

// 📌 Performance Settings
useProfitTarget  = input.bool(false, "Use Profit Target?", group="Performance Settings")
profitTargetRR   = input.float(2.0, "Profit Target (Risk-Reward Ratio)", group="Performance Settings")


// 📌 4️⃣ Dynamic TP/SL (Each Setting with Its Parameters Directly Below)
useATRStopTP    = input.bool(false, "Use ATR-Based Stop-Loss & Take-Profit?", group="Dynamic TP/SL")
atrLength       = input.int(14, "ATR Length", group="Dynamic TP/SL")
atrMultiplier   = input.float(1.5, "Stop-Loss ATR Multiplier", group="Dynamic TP/SL")
profitATRMultiplier = input.float(2.5, "Profit Target ATR Multiplier", group="Dynamic TP/SL")

useTrailingStop = input.bool(false, "Use ATR Trailing Stop?", group="Dynamic TP/SL")
trailStopMultiplier = input.float(1.5, "Trailing Stop ATR Multiplier", group="Dynamic TP/SL")

useBreakEven    = input.bool(false, "Use Break-Even Stop-Loss?", group="Dynamic TP/SL")
breakEvenRR     = input.float(1.5, "Move SL to Break-Even After RR", group="Dynamic TP/SL")

useTrendExit    = input.bool(false, "Use Trend-Based Take Profit (EMA Exit)?", group="Dynamic TP/SL")
emaExitLength   = input.int(9, "EMA Exit Length", group="Dynamic TP/SL")

// 📌 Debug Options
showZlemaDebug = input.bool(false, "Show ZLEMA Trend Debug?", group="Debug")




// ============================================================
// === 1️⃣ CALCULATIONS (Indicators, Trend, ATR, Stop/TP) ===
// ============================================================
src        = close
lag        = math.floor((length - 1) / 2)
zlema      = ta.ema(src + (src - src[lag]), length)
volatility = ta.highest(ta.atr(length), length * 3) * mult

var trend  = 0
if ta.crossover(close, zlema + volatility)
    trend := 1
if ta.crossunder(close, zlema - volatility)
    trend := -1

atrValue = ta.atr(atrLength)
emaExit  = ta.ema(close, emaExitLength)

var float stopLossLongLevel = na
var float profitTargetLongLevel = na
var float stopLossShortLevel = na
var float profitTargetShortLevel = na

var int lastEntryBarIndex = na
var float lastEntryPrice = na

// ✅ Corrected ZLEMA DownTrend Logic: Ensure ZLEMA has decreased for 5 consecutive bars
// ✅ ZLEMA Increasing for 5 Bars → Bullish Trend (Green Triangle Up at the Bottom)
zlemaUpTrend = zlema > zlema[1] and zlema[1] > zlema[2] and zlema[2] > zlema[3] and zlema[3] > zlema[4]

// ✅ ZLEMA Decreasing for 5 Bars → Bearish Trend (Red Triangle Down at the Top)
zlemaDownTrend = zlema < zlema[1] and zlema[1] < zlema[2] and zlema[2] < zlema[3] and zlema[3] < zlema[4]

if ta.crossover(trend, 0) // Long Entry
    stopLossLongLevel := useATRStopTP ? close - (atrValue * atrMultiplier) : zlema - volatility
    profitTargetLongLevel := useProfitTarget ? (close + ((close - stopLossLongLevel) * profitTargetRR)) : na

if ta.crossunder(trend, 0) // Short Entry
    stopLossShortLevel := useATRStopTP ? close + (atrValue * atrMultiplier) : zlema + volatility
    profitTargetShortLevel := useProfitTarget ? (close - ((stopLossShortLevel - close) * profitTargetRR)) : na

// ATR-Based Stop-Loss Levels for Trade Exits
var float atrStopLossLong = na
var float atrStopLossShort = na

if useATRStopTP
    if strategy.position_size > 0  // Long Position
        atrStopLossLong := na(atrStopLossLong) or strategy.position_size[1] == 0 ? close - (atrValue * atrMultiplier) : math.max(nz(atrStopLossLong[1]), close - (atrValue * atrMultiplier))  // Prevents SL from decreasing

    if strategy.position_size < 0  // Short Position
        atrStopLossShort := na(atrStopLossShort) or strategy.position_size[1] == 0 ? close + (atrValue * atrMultiplier) : math.min(nz(atrStopLossShort[1]), close + (atrValue * atrMultiplier))  // Prevents SL from increasing

// ATR-Based Take-Profit Levels
var float atrTakeProfitLong = na
var float atrTakeProfitShort = na

if useATRStopTP
    if strategy.position_size > 0  // Long Position
        atrTakeProfitLong := strategy.position_avg_price + (atrValue * profitATRMultiplier)  // Dynamic TP Based on ATR

    if strategy.position_size < 0  // Short Position
        atrTakeProfitShort := strategy.position_avg_price - (atrValue * profitATRMultiplier)  // Dynamic TP Based on ATR


// ATR Trailing Stop Levels for Trade Exits and Visualization
var float trailStopLongLine = na
var float trailStopShortLine = na

if useTrailingStop
    if strategy.position_size > 0  // Long Position
        trailStopLongLine := na(trailStopLongLine) or strategy.position_size[1] == 0 ? close - (atrValue * trailStopMultiplier) : 
                               math.max(nz(trailStopLongLine[1]), close - (atrValue * trailStopMultiplier))

    if strategy.position_size < 0  // Short Position
        trailStopShortLine := na(trailStopShortLine) or strategy.position_size[1] == 0 ? close + (atrValue * trailStopMultiplier) : 
                               math.min(nz(trailStopShortLine[1]), close + (atrValue * trailStopMultiplier))

// ============================================================
// === 2️⃣ ENTRY & EXIT LOGIC (Conditions for Trading) ===
// ============================================================


// ✅ Entry Conditions for Long Trades
longCondition = ta.crossover(trend, 0) and close > zlema + volatility 
canEnterLong = strategy.position_size == 0 or strategy.position_size[1] < 0  // Allows long entry right after short exit

if useZlemaTrendConfirm
    longCondition := longCondition and zlemaUpTrend  // Ensure ZLEMA Uptrend is true for long entries

// 🔥 Enforce that `longCondition` CANNOT be true if `zlemaUpTrend` is false
if useZlemaTrendConfirm and not zlemaUpTrend
    longCondition := false

// ✅ Entry Conditions for Short Trades
shortCondition = allowShortTrades and ta.crossunder(trend, 0) and close < zlema - volatility
canEnterShort = strategy.position_size == 0 or strategy.position_size[1] > 0  // Allows short entry right after long exit

if useZlemaTrendConfirm
    shortCondition := shortCondition and zlemaDownTrend  // Ensure ZLEMA Downtrend is true for short entries

// ✅ Long Re-Entry Condition: ZLEMA is green, position is flat, price closed below and now above ZLEMA
reEntryLongCondition = reEnterOnLongTrend and
     trend == 1 and
     trend[1] == 1 and  // ✅ Previous bar must also be in bullish trend (prevents triggering on trend change)
     strategy.position_size == 0 and
     close[1] < zlema[1] and
     close > zlema 


// ✅ Debugging: Display `longCondition` and `zlemaUpTrend` values only if the checkbox is checked
if showZlemaDebug and ta.crossover(trend, 0)
    label.new(x=bar_index, y=low, 
              text="LongCondition: " + str.tostring(longCondition) + 
                   "\nZLEMA UpTrend: " + str.tostring(zlemaUpTrend),
              color=color.white, textcolor=color.black, size=size.small, style=label.style_label_down)



// ============================================================
// === 3️⃣ TRADE EXECUTIONS (Entries, ATR SL/TP, Trailing Stop, Trend Exit) ===
// ============================================================

// 📌 Entry Conditions
if (canEnterLong and longCondition) or reEntryLongCondition
    lastEntryBarIndex := bar_index
    lastEntryPrice := close

    // 🛠️ Reset all SL/TP levels on Long Entry or Re-Entry
    if reEntryLongCondition
        // Trend-Based SL/TP
        stopLossLongLevel := useATRStopTP ? na : zlema - volatility
        profitTargetLongLevel := useProfitTarget and not useATRStopTP ? (close + ((close - stopLossLongLevel) * profitTargetRR)) : na

        // ATR-Based SL/TP
        atrStopLossLong := useATRStopTP ? close - (atrValue * atrMultiplier) : na
        atrTakeProfitLong := useATRStopTP ? close + (atrValue * profitATRMultiplier) : na

        // Trailing Stop
        trailStopLongLine := useTrailingStop ? close - (atrValue * trailStopMultiplier) : na

    strategy.entry(id="Long", direction=strategy.long, comment=reEntryLongCondition ? "Re-Entry Long" : "Bullish Trend Change")


if canEnterShort and shortCondition
    lastEntryBarIndex := bar_index
    lastEntryPrice := close
    strategy.entry(id="Short", direction=strategy.short, comment="Bearish Trend Change")


// 📌 ATR-Based Stop-Loss Exits (Ensures SL Always Triggers Correctly)
if useATRStopTP and strategy.position_size > 0
    if low <= atrStopLossLong
        strategy.close("Long", comment="ATR SL Hit - Long")

if useATRStopTP and strategy.position_size < 0
    if high >= atrStopLossShort
        strategy.close("Short", comment="ATR SL Hit - Short")

// 📌 ATR-Based Stop-Loss & Take-Profit Exits (Ensures TP Always Executes)
if useATRStopTP and strategy.position_size > 0 and high >= atrTakeProfitLong
    strategy.close("Long", comment="ATR TP Hit - Long")

if useATRStopTP and strategy.position_size < 0 and low <= atrTakeProfitShort
    strategy.close("Short", comment="ATR TP Hit - Short")


// 📌 Profit Target Exits (Ensures TP Always Executes Independently)
if useProfitTarget and strategy.position_size > 0 and high >= profitTargetLongLevel
    strategy.close("Long", comment="Profit Target Hit - Long")

if useProfitTarget and strategy.position_size < 0 and low <= profitTargetShortLevel
    strategy.close("Short", comment="Profit Target Hit - Short")

// 📌 Stop-Loss for Profit Target Trades (Ensures Stop-Loss Works with TP)
if useProfitTarget and strategy.position_size > 0 and low <= stopLossLongLevel
    strategy.close("Long", comment="Stop-Loss Hit - Long")

if useProfitTarget and strategy.position_size < 0 and high >= stopLossShortLevel
    strategy.close("Short", comment="Stop-Loss Hit - Short")

// 📌 ATR Trailing Stop Loss (Ensures It Works Alongside Other Exits)
if useTrailingStop and strategy.position_size > 0 and low <= trailStopLongLine
    strategy.close("Long", comment="Trailing Stop Hit - Long")

if useTrailingStop and strategy.position_size < 0 and high >= trailStopShortLine
    strategy.close("Short", comment="Trailing Stop Hit - Short")

// 📌 Trend-Based Exit (Closes Position When Trend Reverses)
if strategy.position_size > 0 and ta.crossunder(trend, 0)
    strategy.close("Long", comment="Trend Change to Bearish")

if strategy.position_size < 0 and ta.crossover(trend, 0)
    strategy.close("Short", comment="Trend Change to Bullish")

// 📌 Break-Even Stop-Loss (Adjusts Stop to Entry Price at Set Risk-Reward Ratio)
if useBreakEven and strategy.position_size > 0 and high >= strategy.position_avg_price + (strategy.position_avg_price - atrStopLossLong) * breakEvenRR
    atrStopLossLong := strategy.position_avg_price

if useBreakEven and strategy.position_size < 0 and low <= strategy.position_avg_price - (atrStopLossShort - strategy.position_avg_price) * breakEvenRR
    atrStopLossShort := strategy.position_avg_price

// 📌 EMA Exit (Closes Position if Price Crosses EMA)
if useTrendExit and strategy.position_size > 0 and low < emaExit
    strategy.close("Long", comment="Exit on EMA")

if useTrendExit and strategy.position_size < 0 and high > emaExit
    strategy.close("Short", comment="Exit on EMA")



// ============================================================
// === 4️⃣ VISUALIZATIONS (Trend Shading, Stop-Loss, TP, ATR TS) ===
// ============================================================

// 🟢🔴 Restore Bullish/Bearish Trend Shading
zlemaColor = trend == 1 ? color.new(#00ffbb, 70) : color.new(#ff1100, 70)
m = plot(series=zlema, title="Zero Lag Basis", linewidth=2, color=zlemaColor)

upper = plot(zlema + volatility, style=plot.style_linebr, color=color.new(#ff1100, 90), title="Upper Deviation Band")
lower = plot(zlema - volatility, style=plot.style_linebr, color=color.new(#00ffbb, 90), title="Lower Deviation Band")

fill(plot1=m, plot2=upper, color=(trend == -1 ? color.new(#ff1100, 80) : na), title="Bearish Fill")
fill(plot1=m, plot2=lower, color=(trend == 1 ? color.new(#00ffbb, 80) : na), title="Bullish Fill")

// ✅ Plot a lime green TriangleUp at the bottom when ZLEMA has been going UP for 5 bars
plotshape(series=zlemaUpTrend ? low - ta.atr(5) * 0.5 : na, 
          location=location.bottom, style=shape.triangleup, 
          color=color.lime, title="ZLEMA Uptrend Detected")

// ✅ Plot a red TriangleDown at the top when ZLEMA has been going DOWN for 5 bars
plotshape(series=zlemaDownTrend ? high + ta.atr(5) * 0.5 : na, 
          location=location.top, style=shape.triangledown, 
          color=color.red, title="ZLEMA Downtrend Detected")

// 🔴 Default Stop-Loss Lines (Red) - Only Show If ATR SL/TP Is Not Used
plot(series=(not useATRStopTP and strategy.position_size > 0) ? stopLossLongLevel : na, 
     style=plot.style_linebr, color=color.red, linewidth=2, title="Trend Stop-Loss - Long")

plot(series=(not useATRStopTP and strategy.position_size < 0) ? stopLossShortLevel : na, 
     style=plot.style_linebr, color=color.red, linewidth=2, title="Trend Stop-Loss - Short")

// 🟠 ATR Trailing Stop Loss Line (Thin Orange Line) - Only Draw When Checkbox is Checked
plot(series=(useTrailingStop and strategy.position_size > 0) ? trailStopLongLine : na, 
     style=plot.style_linebr, color=color.new(color.orange, 70), linewidth=1, title="ATR Trailing Stop - Long")

plot(series=(useTrailingStop and strategy.position_size < 0) ? trailStopShortLine : na, 
     style=plot.style_linebr, color=color.new(color.orange, 70), linewidth=1, title="ATR Trailing Stop - Short")

// ✅ ATR-Based Stop-Loss Visualization (Ensures Line Stays Until Trade Closes)
plot(series=(useATRStopTP and strategy.position_size > 0) ? atrStopLossLong : na, 
     style=plot.style_linebr, color=color.new(color.red, 50), linewidth=2, title="ATR-Based Stop-Loss - Long")

plot(series=(useATRStopTP and strategy.position_size < 0) ? atrStopLossShort : na, 
     style=plot.style_linebr, color=color.new(color.red, 50), linewidth=2, title="ATR-Based Stop-Loss - Short")

// ✅ ATR-Based Take-Profit Visualization (Ensures Line Stays Until Trade Closes)
plot(series=(useATRStopTP and strategy.position_size > 0) ? atrTakeProfitLong : na, 
     style=plot.style_linebr, color=color.new(color.green, 50), linewidth=2, title="ATR-Based Take-Profit - Long")

plot(series=(useATRStopTP and strategy.position_size < 0) ? atrTakeProfitShort : na, 
     style=plot.style_linebr, color=color.new(color.green, 50), linewidth=2, title="ATR-Based Take-Profit - Short")

// ✅ Standard Profit Target Visualization (Only Active if ATR SL/TP is NOT Used)
plot(series=(useProfitTarget and not useATRStopTP and strategy.position_size > 0) ? profitTargetLongLevel : na, 
     style=plot.style_linebr, color=color.green, linewidth=2, title="Profit Target - Long")

plot(series=(useProfitTarget and not useATRStopTP and strategy.position_size < 0) ? profitTargetShortLevel : na, 
     style=plot.style_linebr, color=color.green, linewidth=2, title="Profit Target - Short")

// === 📋 FLOATING TABLE: STRATEGY PERFORMANCE & SETTINGS ===

// === Track first and last trade times ===
var int firstTradeTime = na
var int lastTradeTime = na

if strategy.opentrades > 0 and na(firstTradeTime)
    firstTradeTime := time

if strategy.closedtrades > 0
    lastTradeTime := time

// === Format trade date strings safely ===
firstDateStr = "N/A"
lastDateStr  = "N/A"

if not na(firstTradeTime)
    firstDateStr := str.tostring(month(firstTradeTime)) + "/" + str.tostring(dayofmonth(firstTradeTime)) + "/" + str.tostring(year(firstTradeTime) % 100)

if not na(lastTradeTime)
    lastDateStr := str.tostring(month(lastTradeTime)) + "/" + str.tostring(dayofmonth(lastTradeTime)) + "/" + str.tostring(year(lastTradeTime) % 100)

Strategy parameters

The original address: Multi-Timeframe Zero-Lag Trend Signals Trading Strategy: ZLEMA-Based Dynamic Entry-Exit System

FMZQuant @fmzquant

Multi-Timeframe Zero-Lag Trend Signals Trading Strategy: ZLEMA-Based Dynamic Entry-Exit System

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