mlfinlab.online_data_structures.time_bars
Advances in Financial Machine Learning, Marcos Lopez de Prado Chapter 2: Financial Data Structures: Time Bars
Module for implementation of online time bars data structures. This module allows for sequential input of ticks to form time bars.
Module Contents
Classes
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Class which implements time bars compression. |
- class TimeBarGenerator(threshold: int = 86400, tick_fields_mapping: dict = None, aggressor_side_mapping: dict = None, exchange: str = None, contract: str = None)
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Bases:
mlfinlab.online_data_structures.base_bars.BarGeneratorClass which implements time bars compression.
- __metaclass__
- process_tick(tick: dict) bool
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Process one tick. :param tick: (dict) tick to process. {‘timestamp’: pd.Timestamp, ‘price’: float, ‘volume’: float, ‘aggressor_side’(optional): int} :return: (bool) Flag indicating that a new bar was formed.
- set_threshold(threshold: float)
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Set new threshold for bar calculations. :param threshold: (float) threshold to set.
- apply_tick_rule(price: float) Tuple[int, float]
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Applies the tick rule as defined on page 29 of Advances in Financial Machine Learning. :param price: (float) Price at time t. :return: (Tuple[int, float]) The signed tick and tick difference.