liuyu/qlib
1
0
Fork 0
mirror of https://github.com/microsoft/qlib.git synced 2026-07-03 11:00:57 +08:00
Code Activity

add doc

Browse Source
This commit is contained in:
wangwenxi.handsome
2021-07-16 09:17:29 +00:00
parent 65b44349cd
commit 110141ddac
1 changed files with 59 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

65
qlib/backtest/exchange.py
View File

@@ -532,15 +532,24 @@ class BaseQuote:
self.logger = get_module_logger("online operator", level=logging.INFO)
def _update_limit(self, limit_threshold):
"""add limitation information to data based on limit_threshold
"""
raise NotImplementedError(f"Please implement the `_update_limit` method")
def get_trade_w_adj_price(self):
"""return whether use the trade price with adjusted weight
"""
raise NotImplementedError(f"Please implement the `get_trade_w_adj_price` method")
def get_all_stock(self):
"""return all stock codes
"""
raise NotImplementedError(f"Please implement the `get_all_stock` method")
def get_data(self, stock_id, start_time, end_time, fields, method):
def get_data(self, stock_id, start_time, end_time, fields=None, method=None):
"""get the specific fields of stock data during start time and end_time,
and apply method to the data, please refer to resam_ts_data
"""
raise NotImplementedError(f"Please implement the `get_data` method")
LT_TP_EXP = "(exp)" # Tuple[str, str]
@@ -549,6 +558,8 @@ class BaseQuote:
@staticmethod
def _get_limit_type(limit_threshold):
"""get limit type
"""
if isinstance(limit_threshold, Tuple):
return BaseQuote.LT_TP_EXP
elif isinstance(limit_threshold, float):
@@ -560,6 +571,8 @@ class BaseQuote:
class PandasQuote(BaseQuote):
"""
"""
def __init__(
self,
@@ -567,12 +580,52 @@ class PandasQuote(BaseQuote):
end_time,
freq,
codes,
all_fields,
limit_threshold,
buy_price,
sell_price,
extra_quote
all_fields: List[str],
limit_threshold: Union[Tuple[str, str], float, None],
buy_price: str,
sell_price: str,
extra_quote: pd.DataFrame,
):
"""init stock data based on pandas
Parameters
----------
start_time : pd.Timestamp|str
closed start time for backtest
end_time : pd.Timestamp|str
closed end time for backtest
freq : str
frequency of data
codes : [type]
all stock code
all_fields : List[str]
all subscribe fields in qlib
limit_threshold : Union[Tuple[str, str], float, None]
1) `None`: no limitation
2) float, 0.1 for example, default None
3) Tuple[str, str]: (<the expression for buying stock limitation>,
<the expression for sell stock limitation>)
`False` value indicates the stock is tradable
`True` value indicates the stock is limited and not tradable
buy_price : str
the data field for buying stock
sell_price : str
the data field for selling stock
extra_quote : pd.DataFrame
columns: like ['$vwap', '$close', '$volume', '$factor', 'limit_sell', 'limit_buy'].
The limit indicates that the etf is tradable on a specific day.
Necessary fields:
$close is for calculating the total value at end of each day.
Optional fields:
$volume is only necessary when we limit the trade amount or caculate PA(vwap) indicator
$vwap is only necessary when we use the $vwap price as the deal price
$factor is for rounding to the trading unit
limit_sell will be set to False by default(False indicates we can sell this
target on this day).
limit_buy will be set to False by default(False indicates we can buy this
target on this day).
index: MultipleIndex(instrument, pd.Datetime)
"""
super().__init__()