Building Formulaic Alphas¶
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:
Note
DIF means Differential value, which is 12-period EMA minus 26-period EMA.
`DEA`means a 9-period EMA of the DIF.
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.
>> from qlib.data.dataset.handler import QLibDataHandler
>> MACD_EXP = '(EMA($close, 12) - EMA($close, 26))/$close - EMA((EMA($close, 12) - EMA($close, 26))/$close, 9)/$close'
>> fields = [MACD_EXP] # MACD
>> names = ['MACD']
>> labels = ['$close'] # label
>> label_names = ['LABEL']
>> data_handler = QLibDataHandler(start_date='2010-01-01', end_date='2017-12-31', fields=fields, names=names, labels=labels, label_names=label_names)
>> TRAINER_CONFIG = {
.. "train_start_date": "2007-01-01",
.. "train_end_date": "2014-12-31",
.. "validate_start_date": "2015-01-01",
.. "validate_end_date": "2016-12-31",
.. "test_start_date": "2017-01-01",
.. "test_end_date": "2020-08-01",
.. }
>> feature_train, label_train, feature_validate, label_validate, feature_test, label_test = data_handler.get_split_data(**TRAINER_CONFIG)
>> print(feature_train, label_train)
MACD
instrument datetime
SH600000 2010-01-04 -0.008625
2010-01-05 -0.007234
2010-01-06 -0.007693
2010-01-07 -0.009633
2010-01-08 -0.009891
... ...
SZ300251 2014-12-25 0.043072
2014-12-26 0.041345
2014-12-29 0.042733
2014-12-30 0.042066
2014-12-31 0.036299
[322025 rows x 1 columns]
LABEL
instrument datetime
SH600000 2010-01-04 4.260015
2010-01-05 4.292182
2010-01-06 4.207747
2010-01-07 4.113258
2010-01-08 4.159496
... ...
SZ300251 2014-12-25 4.343212
2014-12-26 4.470587
2014-12-29 4.762474
2014-12-30 4.369748
2014-12-31 4.182222
[322025 rows x 1 columns]
Reference¶
To learn more about Data Handler
, please refer to Data Handler
To learn more about Data API
, please refer to Data API