From c71b645777947ddc56a3cf9d738c3140f0998b73 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 5 Feb 2021 10:32:27 +0800
Subject: [PATCH] Update docs about record-temp

---
 docs/component/recorder.rst  | 46 ++++++++++++++++++++++++++++++++++++
 examples/workflow_by_code.py |  3 ++-
 2 files changed, 48 insertions(+), 1 deletion(-)

diff --git a/docs/component/recorder.rst b/docs/component/recorder.rst
index 5e01140cf..3882161bc 100644
--- a/docs/component/recorder.rst
+++ b/docs/component/recorder.rst
@@ -94,6 +94,52 @@ The ``RecordTemp`` class is a class that enables generate experiment results suc
 
 - ``SignalRecord``: This class generates the `prediction` results of the model.
 - ``SigAnaRecord``: This class generates the `IC`, `ICIR`, `Rank IC` and `Rank ICIR` of the model.
+
+Here is a simple example of what is done in ``SigAnaRecord``, which users can refer to if they want to calculate IC, Rank IC, Long-Short Return with their own prediction and label.
+
+.. code-block:: Python
+
+    from qlib.contrib.eva.alpha import calc_ic, calc_long_short_return
+
+    ic, ric = calc_ic(pred.iloc[:, 0], label.iloc[:, 0])
+    long_short_r, long_avg_r = calc_long_short_return(pred.iloc[:, 0], label.iloc[:, 0])
+
 - ``PortAnaRecord``: This class generates the results of `backtest`. The detailed information about `backtest` as well as the available `strategy`, users can refer to `Strategy <../component/strategy.html>`_ and `Backtest <../component/backtest.html>`_.
 
+Here is a simple exampke of what is done in ``PortAnaRecord``, which users can refer to if they want to do backtest based on their own prediction and label.
+
+.. code-block:: Python
+
+    from qlib.contrib.strategy.strategy import TopkDropoutStrategy
+    from qlib.contrib.evaluate import (
+        backtest as normal_backtest,
+        risk_analysis,
+    )
+
+    # backtest
+    STRATEGY_CONFIG = {
+        "topk": 50,
+        "n_drop": 5,
+    }
+    BACKTEST_CONFIG = {
+        "verbose": False,
+        "limit_threshold": 0.095,
+        "account": 100000000,
+        "benchmark": BENCHMARK,
+        "deal_price": "close",
+        "open_cost": 0.0005,
+        "close_cost": 0.0015,
+        "min_cost": 5,
+    }
+    
+    strategy = TopkDropoutStrategy(**STRATEGY_CONFIG)
+    report_normal, positions_normal = normal_backtest(pred_score, strategy=strategy, **BACKTEST_CONFIG)
+
+    # analysis
+    analysis = dict()
+    analysis["excess_return_without_cost"] = risk_analysis(report_normal["return"] - report_normal["bench"])
+    analysis["excess_return_with_cost"] = risk_analysis(report_normal["return"] - report_normal["bench"] - report_normal["cost"])
+    analysis_df = pd.concat(analysis)  # type: pd.DataFrame
+    print(analysis_df)
+
 For more information about the APIs, please refer to `Record Template API <../reference/api.html#module-qlib.workflow.record_temp>`_.
diff --git a/examples/workflow_by_code.py b/examples/workflow_by_code.py
index 8cad566da..4ef5d9b16 100644
--- a/examples/workflow_by_code.py
+++ b/examples/workflow_by_code.py
@@ -118,6 +118,7 @@ if __name__ == "__main__":
         sr = SignalRecord(model, dataset, recorder)
         sr.generate()
 
-        # backtest
+        # backtest. If users want to use backtest based on their own prediction,
+        # please refer to https://qlib.readthedocs.io/en/latest/component/recorder.html#record-template.
         par = PortAnaRecord(recorder, port_analysis_config)
         par.generate()