backtrader.analyzers.tradeanalyzer module

Trade Analyzer Module - Detailed trade statistics.

This module provides the TradeAnalyzer for calculating comprehensive trade statistics including win/loss ratios, streaks, and PnL metrics.

Classes:

TradeAnalyzer: Analyzer that calculates detailed trade statistics.

Example

>>> cerebro = bt.Cerebro()
>>> cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name='ta')
>>> results = cerebro.run()
>>> print(results[0].analyzers.ta.get_analysis())

class backtrader.analyzers.tradeanalyzer.TradeAnalyzer

Bases: Analyzer

Provides statistics on closed trades (keeps also the count of open ones)

• Total Open/Closed Trades

• Streak Won/Lost Current/Longest

• ProfitAndLoss Total/Average

• Won/Lost Count/ Total PNL/ Average PNL / Max PNL

• Long/Short Count/ Total PNL / Average PNL / Max PNL

  • Won/Lost Count/ Total PNL/ Average PNL / Max PNL

• Length (bars in the market)

  • Total/Average/Max/Min

  • Won/Lost Total/Average/Max/Min

  • Long/Short Total/Average/Max/Min

    • Won/Lost Total/Average/Max/Min

Note

The analyzer uses an autodict for the fields, which means that if no trades are executed, no statistics will be generated.

In that case, there will be a single field/subfield in the dictionary returned by get_analysis, namely:

• Dictname[‘total’][‘total’] which will have a value of 0 (the field is also reachable with dot notation dictname.total.total

rets = None

create_analysis()

Create the analysis result data structure.

Initializes the AutoOrderedDict with a total counter set to zero.

stop()

Finalize the analysis when backtest ends.

Closes the results dictionary to prevent further modifications.

notify_trade(trade)

Process trade notifications to build detailed statistics.

Updates all trade statistics including win/loss counts, streaks, PnL metrics, and trade duration for both long and short positions.

Parameters:

trade – The trade object with status and PnL information.