How to get the profit factor of TradingView Pine Script strategies?

How to get the profit factor of TradingView Pine Script strategies?

TL;DR
Profit factor is gross profit ÷ gross loss. Guard against zero loss, then use the ratio to plot performance, throttle sizing, or trigger alerts when results slip below one.

At a Glance

Difficulty	Intermediate
Time to implement	10-15 min
Category	Performance Metrics

Quick Actions

• Open in AI Editor
• Browse PineScript Examples
• Connect to Live Trading

Quick Start

//@version=5
strategy("Profit factor monitor", overlay=false)

profitFactor() =>
    grossLoss = strategy.grossloss
    grossLoss == 0 ? na : strategy.grossprofit / grossLoss

plot(profitFactor(), "PF", color=color.new(color.blue, 0))

Heads-up. Until the strategy books its first losing trade `strategy.grossloss` equals zero, so return `na` (or a large placeholder) to avoid divide-by-zero errors.

Why It Matters

Profit factor summarises edge at a glance: values above 1.0 mean winners outweigh losers, below 1.0 flags a system giving back gains. Tracking it inside Pine lets you throttle order size, pause trading after drawdowns, or surface the ratio in dashboards without exporting results manually.

What You’ll Learn

• Build a reusable helper that guards against zero loss.
• Detect profit-factor shifts with comparisons and crossovers.
• Plot the ratio, annotate results, and conditionally size trades.
• Wrap up with a sample strategy that reports the metric on chart.

Quick Reference

Call	Purpose
strategy.grossprofit	Total gains from closed trades.
strategy.grossloss	Total losses (positive number).
strategy.closedtrades	Useful for confirming the strategy has traded before evaluating PF.
plot(series, ...)	Visualises the profit factor history.
label.new()	Displays a summary at the end of the backtest.

Implementation Blueprint

1. Create a profit factor helper
   Hide the divide-by-zero guard inside a function so the rest of the script stays tidy.

   profitFactor() =>
       grossLoss = strategy.grossloss
       grossLoss == 0 ? na : strategy.grossprofit / grossLoss

2. React to thresholds
   Compare the helper output against critical levels to control risk.

   pf = profitFactor()
   stall = not na(pf) and pf < 1.0
   if stall
       strategy.risk.max_intraday_filled_orders(0)

3. Report the metric clearly
   Plot the ratio and summarise it in a label or table on the last bar.

   plot(pf, "Profit factor", color=color.new(color.teal, 0))
   if barstate.islastconfirmedhistory and not na(pf)
       label.new(bar_index + 2, close,
           "PF: " + str.tostring(pf, "0.000"),
           style=label.style_label_left,
           textcolor=color.white,
           bgcolor=color.new(color.teal, 65))

Example Playbook

//@version=5
strategy("Bollinger band swings with PF monitor", overlay=true, default_qty_type=strategy.fixed, default_qty_value=1)

length    = input.int(20, "BB length", minval=1)
mult      = input.float(2.0, "Std dev multiplier", step=0.1)
minPF     = input.float(1.2, "Pause trading below PF", step=0.1)

basis = ta.sma(close, length)
upper = basis + mult * ta.stdev(close, length)
lower = basis - mult * ta.stdev(close, length)

plot(basis, "Basis", color=color.new(color.gray, 0))
plot(upper, "Upper", color=color.new(color.green, 0))
plot(lower, "Lower", color=color.new(color.red, 0))

pf() =>
    loss = strategy.grossloss
    loss == 0 ? na : strategy.grossprofit / loss

currentPF = pf()

longSignal  = ta.crossover(close, upper)
shortSignal = ta.crossunder(close, lower)

if longSignal and (na(currentPF) or currentPF >= minPF)
    strategy.entry("Long", strategy.long)
if shortSignal and (na(currentPF) or currentPF >= minPF)
    strategy.entry("Short", strategy.short)

if not na(currentPF)
    plot(currentPF, "Profit factor", color=color.new(color.orange, 0), linewidth=2, display=display.bottom)

if barstate.islastconfirmedhistory and not na(currentPF)
    summary = "Gross profit: " + str.tostring(strategy.grossprofit, "##,###.00") +
              "\nGross loss: " + str.tostring(strategy.grossloss, "##,###.00") +
              "\nProfit factor: " + str.tostring(currentPF, "0.000")
    shade = currentPF >= 1.0 ? color.new(color.green, 60) : color.new(color.red, 60)
    label.new(bar_index + 2, basis,
        summary,
        style=label.style_label_left,
        textcolor=color.white,
        bgcolor=shade)

Why this works.

• The helper centralises error handling, so all comparisons read cleanly.
• Guarding entries when PF drops below `minPF` pauses trading during drawdowns.
• The summary label makes it easy to screenshot results or share backtests without opening the Strategy Tester panel.

Pro Tips & Pitfalls

• Profit factor only reflects closed trades. During open drawdowns it may still look healthy—combine it with equity curve checks for a fuller picture.
• Because strategy.grossloss is positive, dividing by it is safe once a losing trade exists; you do not need math.abs.
• Compare PF against different thresholds to gate pyramiding or tighten stops when edge weakens.
• Resetting the strategy (removing/re-adding) clears the history—handy for segmenting sessions.

Troubleshooting & FAQ

My helper keeps returning na

The strategy has not booked any losing trades yet. Leave chart running or seed a losing trade so strategy.grossloss becomes non-zero.

Profit factor spikes to extremes mid-test

Large ratios occur when losses are tiny relative to wins. Consider minimum-loss guards or pair PF with additional stats (e.g., win rate) before trusting it in isolation.

Can I calculate PF per symbol or timeframe?

Yes—store cumulative profits/losses in arrays keyed by symbol/time-frame, or run the strategy separately per chart. Pine’s built-in metrics are global to the script instance.

Key Takeaways

• Profit factor equals total wins divided by total losses; guard against zero loss before dividing.
• Wrap the math in a helper so charts, alerts, and position sizing can reuse the value cleanly.
• Visualise and label the metric to understand when the system is thriving or failing.
• Combine PF with other controls to automate drawdown responses without babysitting the Strategy Tester.

---

Keep Going

• Open AI Editor to apply the pattern with guided assistance
• Browse Strategy Examples for ready-to-run templates
• Connect to Live Trading when you are ready to automate

Adapted from tradingcode.net, optimised for Algo Trade Analytics users.