.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/trade_ledger.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_gallery_trade_ledger.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_gallery_trade_ledger.py:


Trade Ledger and Position Analytics
===================================

Every ``BacktestResult`` includes a trade ledger.  Each row records costs,
holding time, exit classification, maximum adverse excursion (MAE), and maximum
favorable excursion (MFE), while the ledger provides portfolio-level position
analytics such as expectancy and streaks.

.. GENERATED FROM PYTHON SOURCE LINES 12-14

Create a short deterministic market and a single long signal.  Its compact
price path makes the resulting holding time, MAE, and MFE easy to audit.

.. GENERATED FROM PYTHON SOURCE LINES 14-71

.. code-block:: Python


    from datetime import datetime, timedelta

    import numpy as np

    from TradeTide import (
        Market,
        Portfolio,
        PositionCollection,
        capital_management,
        exit_strategy,
    )
    from TradeTide.execution import ExecutionCosts
    from TradeTide.performance import BacktestResult

    market = Market()
    start = datetime(2024, 1, 1, 9)
    market.add_market_data(
        start, 1.2002, 1.2004, 1.2000, 1.2002, 1.2000, 1.2002, 1.1998, 1.2000
    )
    market.add_market_data(
        start + timedelta(minutes=1),
        1.2004,
        1.2008,
        1.2002,
        1.2006,
        1.2002,
        1.2006,
        1.2000,
        1.2004,
    )
    market.add_market_data(
        start + timedelta(minutes=2),
        1.2006,
        1.2008,
        1.2004,
        1.2006,
        1.2004,
        1.2006,
        1.2002,
        1.2004,
    )

    positions = PositionCollection(market, np.array([1, 0, 0]))
    positions.open_positions(exit_strategy.Static(stop_loss=2, take_profit=2))
    positions.propagate_positions()

    portfolio = Portfolio(positions)
    portfolio.simulate(
        capital_management.FixedLot(
            capital=10_000,
            fixed_lot_size=100,
            max_capital_at_risk=1_000,
            max_concurrent_positions=1,
        )
    )








.. GENERATED FROM PYTHON SOURCE LINES 72-74

Add optional execution costs and inspect the ledger.  ``to_dataframe`` is
convenient for notebooks and CSV/HTML reporting workflows.

.. GENERATED FROM PYTHON SOURCE LINES 74-82

.. code-block:: Python


    result = BacktestResult.from_portfolio(
        portfolio,
        ExecutionCosts(commission_per_lot=0.001, slippage_pips=0.0),
    )

    print(result.ledger.to_dataframe())
    print(result.ledger.analytics)




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

       trade_id  ...  maximum_favorable_excursion
    0         1  ...                         0.04

    [1 rows x 14 columns]
    <TradeTide.ledger.PositionAnalytics object at 0x7f7f4de3ec30>





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.005 seconds)


.. _sphx_glr_download_gallery_trade_ledger.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: trade_ledger.ipynb <trade_ledger.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: trade_ledger.py <trade_ledger.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: trade_ledger.zip <trade_ledger.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_