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Building Formulaic Alphas

docs/advanced/alpha.rst

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.. _alpha:

========================= Building Formulaic Alphas

.. currentmodule:: qlib

Introduction

In quantitative trading practice, designing novel factors that can explain and predict future asset returns are of vital importance to the profitability of a strategy. Such factors are usually called alpha factors, or alphas in short.

A formulaic alpha, as the name suggests, is a kind of alpha that can be presented as a formula or a mathematical expression.

Building Formulaic Alphas in Qlib

In Qlib, users can easily build formulaic alphas.

Example

MACD, short for moving average convergence/divergence, is a formulaic alpha used in technical analysis of stock prices. It is designed to reveal changes in the strength, direction, momentum, and duration of a trend in a stock's price.

MACD can be presented as the following formula:

.. math::

MACD = 2\times (DIF-DEA)

.. note::

`DIF` means Differential value, which is 12-period EMA minus 26-period EMA.

.. math::

    DIF = \frac{EMA(CLOSE, 12) - EMA(CLOSE, 26)}{CLOSE}

`DEA` means a 9-period EMA of the DIF.

.. math::

    DEA = EMA(DIF, 9)

Users can use Data Handler to build formulaic alphas MACD in qlib:

.. note:: Users need to initialize Qlib with qlib.init first. Please refer to initialization <../start/initialization.html>_.

.. code-block:: python

>> from qlib.data.dataset.loader import QlibDataLoader
>> MACD_EXP = '2 * ((EMA($close, 12) - EMA($close, 26))/$close - EMA((EMA($close, 12) - EMA($close, 26))/$close, 9))'
>> fields = [MACD_EXP] # MACD
>> names = ['MACD']
>> labels = ['Ref($close, -2)/Ref($close, -1) - 1'] # label
>> label_names = ['LABEL']
>> data_loader_config = {
..     "feature": (fields, names),
..     "label": (labels, label_names)
.. }
>> data_loader = QlibDataLoader(config=data_loader_config)
>> df = data_loader.load(instruments='csi300', start_time='2010-01-01', end_time='2017-12-31')
>> print(df)
                        feature     label
                           MACD     LABEL
datetime   instrument
2010-01-04 SH600000    0.008781 -0.019672
           SH600004    0.006699 -0.014721
           SH600006    0.005714  0.002911
           SH600008    0.000798  0.009818
           SH600009    0.017015 -0.017758
...                         ...       ...
2017-12-29 SZ300124    0.015071 -0.005074
           SZ300136   -0.015466  0.056352
           SZ300144    0.013082  0.011853
           SZ300251   -0.001026  0.021739
           SZ300315   -0.007559  0.012455

Reference

To learn more about Data Loader, please refer to Data Loader <../component/data.html#data-loader>_

To learn more about Data API, please refer to Data API <../component/data.html>_