зеркало из https://github.com/microsoft/qlib.git
Correct errors and typos in doc strings (#1338)
* add missing parameters to doc string in order_generate * fix some typos in doc strings * reformat base on code style standard * Update qlib/backtest/__init__.py * Update examples/run_all_model.py * Update examples/run_all_model.py Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
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@ -253,7 +253,7 @@ class ModelRunner:
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default "" indicates that
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qlib_uri : str
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the uri to install qlib with pip
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it could be url on the we or local path (NOTE: the local path must be a absolute path)
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it could be URI on the remote or local path (NOTE: the local path must be an absolute path)
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exp_folder_name: str
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the name of the experiment folder
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wait_before_rm_env : bool
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@ -244,7 +244,7 @@ def backtest(
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benchmark: str
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the benchmark for reporting.
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account : Union[float, int, Position]
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information for describing how to creating the account
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information for describing how to create the account
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For `float` or `int`:
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Using Account with only initial cash
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For `Position`:
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@ -236,7 +236,7 @@ class Account:
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if not self.current_position.skip_update():
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stock_list = self.current_position.get_stock_list()
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for code in stock_list:
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# if suspend, no new price to be updated, profit is 0
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# if suspended, no new price to be updated, profit is 0
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if trade_exchange.check_stock_suspended(code, trade_start_time, trade_end_time):
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continue
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bar_close = cast(float, trade_exchange.get_close(code, trade_start_time, trade_end_time))
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@ -33,10 +33,14 @@ class OrderGenerator:
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:type target_weight_position: dict
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:param risk_degree:
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:type risk_degree: float
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:param pred_date: the date the score is predicted
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:type pred_date: pd.Timestamp
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:param trade_date: the date the stock is traded
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:type trade_date: pd.Timestamp
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:param pred_start_time:
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:type pred_start_time: pd.Timestamp
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:param pred_end_time:
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:type pred_end_time: pd.Timestamp
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:param trade_start_time:
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:type trade_start_time: pd.Timestamp
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:param trade_end_time:
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:type trade_end_time: pd.Timestamp
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:rtype: list
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"""
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@ -72,10 +76,14 @@ class OrderGenWInteract(OrderGenerator):
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:type target_weight_position: dict
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:param risk_degree:
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:type risk_degree: float
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:param pred_date:
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:type pred_date: pd.Timestamp
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:param trade_date:
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:type trade_date: pd.Timestamp
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:param pred_start_time:
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:type pred_start_time: pd.Timestamp
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:param pred_end_time:
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:type pred_end_time: pd.Timestamp
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:param trade_start_time:
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:type trade_start_time: pd.Timestamp
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:param trade_end_time:
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:type trade_end_time: pd.Timestamp
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:rtype: list
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"""
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@ -147,9 +155,12 @@ class OrderGenWOInteract(OrderGenerator):
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) -> list:
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"""generate_order_list_from_target_weight_position
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generate order list directly not using the information (e.g. whether can be traded, the accurate trade price) at trade date.
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In target weight position, generating order list need to know the price of objective stock in trade date, but we cannot get that
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value when do not interact with exchange, so we check the %close price at pred_date or price recorded in current position.
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generate order list directly not using the information (e.g. whether can be traded, the accurate trade price)
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at trade date.
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In target weight position, generating order list need to know the price of objective stock in trade date,
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but we cannot get that
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value when do not interact with exchange, so we check the %close price at pred_date or price recorded
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in current position.
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:param current:
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:type current: Position
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@ -159,10 +170,14 @@ class OrderGenWOInteract(OrderGenerator):
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:type target_weight_position: dict
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:param risk_degree:
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:type risk_degree: float
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:param pred_date:
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:type pred_date: pd.Timestamp
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:param trade_date:
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:type trade_date: pd.Timestamp
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:param pred_start_time:
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:type pred_start_time: pd.Timestamp
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:param pred_end_time:
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:type pred_end_time: pd.Timestamp
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:param trade_start_time:
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:type trade_start_time: pd.Timestamp
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:param trade_end_time:
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:type trade_end_time: pd.Timestamp
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:rtype: list of generated orders
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"""
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@ -185,7 +200,8 @@ class OrderGenWOInteract(OrderGenerator):
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* target_weight_position[stock_id]
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/ trade_exchange.get_close(stock_id, start_time=pred_start_time, end_time=pred_end_time)
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)
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# TODO: Qlib use None to represent trading suspension. So last close price can't be the estimated trading price.
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# TODO: Qlib use None to represent trading suspension.
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# So last close price can't be the estimated trading price.
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# Maybe a close price with forward fill will be a better solution.
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elif stock_id in current_stock:
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amount_dict[stock_id] = (
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