.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "api/gallery/market_microstructure/spreads/plot_03_lee_ready.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_api_gallery_market_microstructure_spreads_plot_03_lee_ready.py>`
        to download the full example code or to run this example in your browser via JupyterLite.

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

.. _sphx_glr_api_gallery_market_microstructure_spreads_plot_03_lee_ready.py:


Lee and Ready's trade classification
====================================

Trade records do not say who initiated a trade. Charles Lee and Mark
Ready (1991) signed trades above the midquote as buys and below it as
sells, used the tick test for trades at the midquote, and compared each
trade with the quote of *five seconds earlier*: on the NYSE the quote
revision a trade caused was often time-stamped before the trade itself,
so the contemporaneous quote had already moved toward the trade price.

.. GENERATED FROM PYTHON SOURCE LINES 14-21

.. code-block:: Python

    import matplotlib.pyplot as plt
    import numpy as np

    from financialkit.market_microstructure import align_quotes, lee_ready, quote_rule, tick_test

    rng = np.random.default_rng(2)








.. GENERATED FROM PYTHON SOURCE LINES 22-30

A market with early-stamped quote updates
-----------------------------------------

Trades arrive every 15 seconds on average, 15% of them at the midquote.
Each one moves the midquote by 4 cents in its direction, plus noise,
and the new quote is recorded two seconds *before* the trade that
caused it. Without the delay, the quote rule compares trades with a
quote that has already moved past them.

.. GENERATED FROM PYTHON SOURCE LINES 30-52

.. code-block:: Python


    n, half = 3000, 0.05
    t = np.cumsum(3.0 + rng.exponential(12.0, n))
    side = rng.choice([-1.0, 1.0], n)
    step = 0.04 * side + 0.02 * rng.standard_normal(n)
    mid_before = 20 + np.concatenate([[0.0], np.cumsum(step)[:-1]])
    at_mid = rng.random(n) < 0.15
    price = np.where(at_mid, mid_before, mid_before + side * rng.uniform(0.3, 1.0, n) * half)
    mid_after = mid_before + step
    quote_t = np.concatenate([[0.0], t - 2.0])
    quote_mid = np.concatenate([[mid_before[0]], mid_after])

    results = {}
    for delay in (0.0, 5.0):
        b, a = align_quotes(t, quote_t, quote_mid - half, quote_mid + half, delay=delay)
        results[f"quote rule, {delay:g}s"] = quote_rule(price, b, a)
        results[f"Lee-Ready, {delay:g}s"] = lee_ready(price, b, a)
    results["tick test"] = tick_test(price)

    for name, est in results.items():
        print(f"{name:17s} correct {np.mean(est == side):.1%}")





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

 .. code-block:: none

    quote rule, 0s    correct 29.9%
    Lee-Ready, 0s     correct 29.9%
    quote rule, 5s    correct 85.6%
    Lee-Ready, 5s     correct 91.5%
    tick test         correct 81.0%




.. GENERATED FROM PYTHON SOURCE LINES 53-55

Accuracy by rule
----------------

.. GENERATED FROM PYTHON SOURCE LINES 55-63

.. code-block:: Python


    fig, ax = plt.subplots(figsize=(7, 3.5))
    ax.barh(list(results), [np.mean(e == side) for e in results.values()], color=["C0", "C2", "C0", "C2", "C1"])
    ax.set_xlim(0.4, 1.0)
    ax.set_xlabel("fraction of trades correctly signed")
    fig.tight_layout()

    plt.show()



.. image-sg:: /api/gallery/market_microstructure/spreads/images/sphx_glr_plot_03_lee_ready_001.png
   :alt: plot 03 lee ready
   :srcset: /api/gallery/market_microstructure/spreads/images/sphx_glr_plot_03_lee_ready_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.028 seconds)


.. _sphx_glr_download_api_gallery_market_microstructure_spreads_plot_03_lee_ready.py:

.. only:: html

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

    .. container:: lite-badge

      .. image:: images/jupyterlite_badge_logo.svg
        :target: ../../../../lite/lab/index.html?path=api/gallery/market_microstructure/spreads/plot_03_lee_ready.ipynb
        :alt: Launch JupyterLite
        :width: 150 px

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

      :download:`Download Jupyter notebook: plot_03_lee_ready.ipynb <plot_03_lee_ready.ipynb>`

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

      :download:`Download Python source code: plot_03_lee_ready.py <plot_03_lee_ready.py>`

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

      :download:`Download zipped: plot_03_lee_ready.zip <plot_03_lee_ready.zip>`


.. only:: html

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

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