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Merge pull request #493 from bxdd/optimize_resam_data

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optimize performance of resam data in rule_strategy & exchange
This commit is contained in:
bxdd
2021-07-04 02:44:53 +08:00
committed by GitHub
parent ef7fe8aa75 ecf2f24d59
commit 9b74a19b14
6 changed files with 99 additions and 35 deletions
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21
qlib/contrib/strategy/rule_strategy.py
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@@ -7,7 +7,7 @@ from qlib.data.dataset.utils import convert_index_format
from qlib.utils import lazy_sort_index
from ...utils.resam import resam_ts_data
from ...utils.resam import resam_ts_data, ts_data_last
from ...data.data import D
from ...strategy.base import BaseStrategy
from ...backtest.order import BaseTradeDecision, Order, TradeDecisionWO
@@ -432,7 +432,7 @@ class SBBStrategyEMA(SBBStrategyBase):
if not signal_df.empty:
for stock_id, stock_val in signal_df.groupby(level="instrument"):
self.signal[stock_id] = stock_val
self.signal[stock_id] = stock_val["signal"].droplevel(level="instrument")
def reset_level_infra(self, level_infra):
"""
@@ -454,13 +454,16 @@ class SBBStrategyEMA(SBBStrategyBase):
return self.TREND_MID
else:
_sample_signal = resam_ts_data(
self.signal[stock_id]["signal"], pred_start_time, pred_end_time, method="last"
self.signal[stock_id],
pred_start_time,
pred_end_time,
method=ts_data_last,
)
# if EMA signal == 0 or None, return mid trend
if _sample_signal is None or _sample_signal.iloc[0] == 0:
if _sample_signal is None or np.isnan(_sample_signal) or _sample_signal == 0:
return self.TREND_MID
# if EMA signal > 0, return long trend
elif _sample_signal.iloc[0] > 0:
elif _sample_signal > 0:
return self.TREND_LONG
# if EMA signal < 0, return short trend
else:
@@ -523,7 +526,7 @@ class ACStrategy(BaseStrategy):
if not signal_df.empty:
for stock_id, stock_val in signal_df.groupby(level="instrument"):
self.signal[stock_id] = stock_val
self.signal[stock_id] = stock_val["volatility"].droplevel(level="instrument")
def reset_common_infra(self, common_infra):
"""
@@ -590,12 +593,12 @@ class ACStrategy(BaseStrategy):
# considering trade unit
sig_sam = (
resam_ts_data(self.signal[order.stock_id]["volatility"], pred_start_time, pred_end_time, method="last")
resam_ts_data(self.signal[order.stock_id], pred_start_time, pred_end_time, method=ts_data_last)
if order.stock_id in self.signal
else None
)
if sig_sam is None or sig_sam.iloc[0] is None:
if sig_sam is None or np.isnan(sig_sam):
# no signal, TWAP
_amount_trade_unit = self.trade_exchange.get_amount_of_trade_unit(order.factor)
if _amount_trade_unit is None:
@@ -612,7 +615,7 @@ class ACStrategy(BaseStrategy):
)
else:
# VA strategy
kappa_tild = self.lamb / self.eta * sig_sam.iloc[0] * sig_sam.iloc[0]
kappa_tild = self.lamb / self.eta * sig_sam * sig_sam
kappa = np.arccosh(kappa_tild / 2 + 1)
amount_ratio = (
np.sinh(kappa * (trade_len - trade_step)) - np.sinh(kappa * (trade_len - trade_step - 1))