tensortrade.stochastic.processes.ornstein_uhlenbeck module¶
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tensortrade.stochastic.processes.ornstein_uhlenbeck.
ornstein
(base_price: int = 1, base_volume: int = 1, start_date: str = '2010-01-01', start_date_format: str = '%Y-%m-%d', times_to_generate: int = 1000, time_frame: str = '1h', params: Optional[tensortrade.stochastic.utils.parameters.ModelParameters] = None) → pandas.core.frame.DataFrame[source]¶ Generates price data from the OU process.
Parameters: - base_price (int, default 1) – The base price to use for price generation.
- base_volume (int, default 1) – The base volume to use for volume generation.
- start_date (str, default '2010-01-01') – The start date of the generated data
- start_date_format (str, default '%Y-%m-%d') – The format for the start date of the generated data.
- times_to_generate (int, default 1000) – The number of bars to make.
- time_frame (str, default '1h') – The time frame.
- params (ModelParameters, optional) – The model parameters.
Returns: pd.DataFrame – The generated data frame containing the OHLCV bars.
References
[1] https://en.wikipedia.org/wiki/Ornstein%E2%80%93Uhlenbeck_process
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tensortrade.stochastic.processes.ornstein_uhlenbeck.
ornstein_uhlenbeck_levels
(params: tensortrade.stochastic.utils.parameters.ModelParameters) → numpy.array[source]¶ Constructs the rate levels of a mean-reverting Ornstein-Uhlenbeck process.
Parameters: params (ModelParameters) – The parameters for the stochastic model. Returns: np.array – The interest rate levels for the Ornstein Uhlenbeck process