report.rst

Analysis: Evaluation & Results Analysis

Introduction

Analysis is designed to show the graphical reports of Intraday Trading , which helps users to evaluate and analyse investment portfolios visually. The following are some graphics to view:

• analysis_position

  • report_graph
  • score_ic_graph
  • cumulative_return_graph
  • risk_analysis_graph
  • rank_label_graph

• analysis_model

  • model_performance_graph

All of the accumulated profit metrics(e.g. return, max drawdown) in Qlib are calculated by summation. This avoids the metrics or the plots being skewed exponentially over time.

Graphical Reports

Users can run the following code to get all supported reports.

>> import qlib.contrib.report as qcr
>> print(qcr.GRAPH_NAME_LIST)
['analysis_position.report_graph', 'analysis_position.score_ic_graph', 'analysis_position.cumulative_return_graph', 'analysis_position.risk_analysis_graph', 'analysis_position.rank_label_graph', 'analysis_model.model_performance_graph']

Note

For more details, please refer to the function document: similar to help(qcr.analysis_position.report_graph)

Usage & Example

Usage of analysis_position.report

API

.. automodule:: qlib.contrib.report.analysis_position.report
    :members:

Graphical Result

Note

• Axis X: Trading day

• Axis Y:

  • cum bench

    Cumulative returns series of benchmark

  • cum return wo cost

    Cumulative returns series of portfolio without cost

  • cum return w cost

    Cumulative returns series of portfolio with cost

  • return wo mdd

    Maximum drawdown series of cumulative return without cost

  • return w cost mdd:

    Maximum drawdown series of cumulative return with cost

  • cum ex return wo cost

    The CAR (cumulative abnormal return) series of the portfolio compared to the benchmark without cost.

  • cum ex return w cost

    The CAR (cumulative abnormal return) series of the portfolio compared to the benchmark with cost.

  • turnover

    Turnover rate series

  • cum ex return wo cost mdd

    Drawdown series of CAR (cumulative abnormal return) without cost

  • cum ex return w cost mdd

    Drawdown series of CAR (cumulative abnormal return) with cost

• The shaded part above: Maximum drawdown corresponding to cum return wo cost
• The shaded part below: Maximum drawdown corresponding to cum ex return wo cost

Usage of analysis_position.score_ic

API

.. automodule:: qlib.contrib.report.analysis_position.score_ic
    :members:

Graphical Result

Note

• Axis X: Trading day

• Axis Y:

  • ic

    The Pearson correlation coefficient series between label and prediction score. In the above example, the label is formulated as Ref($close, -2)/Ref($close, -1)-1. Please refer to Data Feature for more details.

  • rank_ic

    The Spearman's rank correlation coefficient series between label and prediction score.

Usage of analysis_position.risk_analysis

API

.. automodule:: qlib.contrib.report.analysis_position.risk_analysis
    :members:

Graphical Result

Note

• general graphics

  • std

    • excess_return_without_cost

      The Standard Deviation of CAR (cumulative abnormal return) without cost.

    • excess_return_with_cost

      The Standard Deviation of CAR (cumulative abnormal return) with cost.

  • annualized_return

    • excess_return_without_cost

      The Annualized Rate of CAR (cumulative abnormal return) without cost.

    • excess_return_with_cost

      The Annualized Rate of CAR (cumulative abnormal return) with cost.

  • information_ratio

    • excess_return_without_cost

      The Information Ratio without cost.

    • excess_return_with_cost

      The Information Ratio with cost.

    To know more about Information Ratio, please refer to Information Ratio – IR.

  • max_drawdown

    • excess_return_without_cost

      The Maximum Drawdown of CAR (cumulative abnormal return) without cost.

    • excess_return_with_cost

      The Maximum Drawdown of CAR (cumulative abnormal return) with cost.

Note

• annualized_return/max_drawdown/information_ratio/std graphics

  • Axis X: Trading days grouped by month

  • Axis Y:

    • annualized_return graphics

      • excess_return_without_cost_annualized_return

        The Annualized Rate series of monthly CAR (cumulative abnormal return) without cost.

      • excess_return_with_cost_annualized_return

        The Annualized Rate series of monthly CAR (cumulative abnormal return) with cost.

    • max_drawdown graphics

      • excess_return_without_cost_max_drawdown

        The Maximum Drawdown series of monthly CAR (cumulative abnormal return) without cost.

      • excess_return_with_cost_max_drawdown

        The Maximum Drawdown series of monthly CAR (cumulative abnormal return) with cost.

    • information_ratio graphics

      • excess_return_without_cost_information_ratio

        The Information Ratio series of monthly CAR (cumulative abnormal return) without cost.

      • excess_return_with_cost_information_ratio

        The Information Ratio series of monthly CAR (cumulative abnormal return) with cost.

    • std graphics

      • excess_return_without_cost_max_drawdown

        The Standard Deviation series of monthly CAR (cumulative abnormal return) without cost.

      • excess_return_with_cost_max_drawdown

        The Standard Deviation series of monthly CAR (cumulative abnormal return) with cost.

Usage of analysis_model.analysis_model_performance

API

.. automodule:: qlib.contrib.report.analysis_model.analysis_model_performance
    :members:

Graphical Results

Note

• cumulative return graphics

  • Group1:

    The Cumulative Return series of stocks group with (ranking ratio of label <= 20%)

  • Group2:

    The Cumulative Return series of stocks group with (20% < ranking ratio of label <= 40%)

  • Group3:

    The Cumulative Return series of stocks group with (40% < ranking ratio of label <= 60%)

  • Group4:

    The Cumulative Return series of stocks group with (60% < ranking ratio of label <= 80%)

  • Group5:

    The Cumulative Return series of stocks group with (80% < ranking ratio of label)

  • long-short:

    The Difference series between Cumulative Return of Group1 and of Group5

  • long-average

    The Difference series between Cumulative Return of Group1 and average Cumulative Return for all stocks.

  The ranking ratio can be formulated as follows.

  ranking\ ratio = \frac{Ascending\ Ranking\ of\ label}{Number\ of\ Stocks\ in\ the\ Portfolio}
  

Note

• long-short/long-average

  The distribution of long-short/long-average returns on each trading day

Note

• Information Coefficient

  • The Pearson correlation coefficient series between labels and prediction scores of stocks in portfolio.
  • The graphics reports can be used to evaluate the prediction scores.

Note

• Monthly IC

  Monthly average of the Information Coefficient

Note

• IC

  The distribution of the Information Coefficient on each trading day.

• IC Normal Dist. Q-Q

  The Quantile-Quantile Plot is used for the normal distribution of Information Coefficient on each trading day.

Note

• Auto Correlation

  • The Pearson correlation coefficient series between the latest prediction scores and the prediction scores lag days ago of stocks in portfolio on each trading day.
  • The graphics reports can be used to estimate the turnover rate.