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Enrich test cases

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This commit is contained in:
Huoran Li
2022-07-15 14:47:37 +08:00
parent 3294e4dc87
commit a44fbf5854
3 changed files with 165 additions and 86 deletions
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31
qlib/rl/order_execution/simulator_qlib.py
View File

@@ -98,7 +98,7 @@ class StateMaintainer:
self.history_steps = pd.DataFrame(columns=metric_keys).set_index("datetime")
self.metrics = None
def update(self, inner_executor: BaseExecutor, inner_strategy: DecomposedStrategy) -> None:
def update(self, inner_executor: BaseExecutor, inner_strategy: DecomposedStrategy, done: bool) -> None:
execute_order = inner_strategy.execute_order
execute_result = inner_strategy.execute_result
exec_vol = np.array([e[0].deal_amount for e in execute_result])
@@ -117,7 +117,7 @@ class StateMaintainer:
market_volume = np.array([exchange.get_volume(execute_order.stock_id, t, t) for t in minutes])
datetime_list = _get_ticks_slice(
self._tick_index, execute_result[0][0].start_time, execute_result[-1][0].start_time, include_end=True
self._tick_index, execute_result[0][0].start_time, execute_result[-1][0].start_time, include_end=True,
)
else:
market_price = np.array([])
@@ -157,6 +157,16 @@ class StateMaintainer:
],
)
if done:
self.metrics = self._metrics_collect(
self._order,
self._tick_index[0], # start time
self.history_exec["market_volume"],
self.history_exec["market_price"],
self.history_steps["amount"].sum(),
self.history_exec["deal_amount"],
)
def _metrics_collect(
self,
order: Order,
@@ -248,13 +258,19 @@ class QlibSimulator(Simulator[Order, SAOEState, float]):
exchange = self._inner_executor.trade_exchange
self._ticks_index = pd.DatetimeIndex([e[1] for e in list(exchange.quote_df.index)])
self._ticks_for_order = _get_ticks_slice(self._ticks_index, self._order.start_time, self._order.end_time)
self._ticks_for_order = _get_ticks_slice(
self._ticks_index,
self._order.start_time,
self._order.end_time,
include_end=True,
)
twap_price = exchange.get_deal_price(
self.twap_price = exchange.get_deal_price(
order.stock_id,
pd.Timestamp(self._ticks_for_order[0]),
pd.Timestamp(self._ticks_for_order[1]),
pd.Timestamp(self._ticks_for_order[-1]),
direction=order.direction,
method="mean",
)
top_strategy = SingleOrderStrategy(common_infra, order, self._trade_range, instrument)
@@ -270,7 +286,7 @@ class QlibSimulator(Simulator[Order, SAOEState, float]):
self._maintainer = StateMaintainer(
order=self._order,
tick_index=self._ticks_index,
twap_price=twap_price,
twap_price=self.twap_price,
)
def _iter_strategy(self, action: float = None) -> DecomposedStrategy:
@@ -281,6 +297,8 @@ class QlibSimulator(Simulator[Order, SAOEState, float]):
return strategy
def step(self, action: float) -> None:
assert not self._done, "Simulator has already done!"
try:
self._iter_strategy(action=action)
except StopIteration:
@@ -289,6 +307,7 @@ class QlibSimulator(Simulator[Order, SAOEState, float]):
self._maintainer.update(
inner_executor=self._inner_executor,
inner_strategy=self._inner_strategy,
done=self._done,
)
def get_state(self) -> SAOEState:

69
qlib/rl/order_execution/tests/common.py Normal file
View File

@@ -0,0 +1,69 @@
from pathlib import Path
from qlib.backtest.decision import Order
from qlib.backtest.executor import NestedExecutor, SimulatorExecutor
from qlib.backtest.utils import CommonInfrastructure
from qlib.config import QlibConfig
from qlib.contrib.strategy import TWAPStrategy
from qlib.rl.order_execution.simulator_qlib import ExchangeConfig, QlibSimulator
# fmt: off
qlib_config = QlibConfig(
{
"provider_uri_day": Path("C:/workspace/NeuTrader/data_sample/cn/qlib_amc_1d"),
"provider_uri_1min": Path("C:/workspace/NeuTrader/data_sample/cn/qlib_amc_1min"),
"feature_root_dir": Path("C:/workspace/NeuTrader/data_sample/cn/qlib_amc_handler_stock"),
"feature_columns_today": [
"$open", "$high", "$low", "$close", "$vwap", "$bid", "$ask", "$volume",
"$bidV", "$bidV1", "$bidV3", "$bidV5", "$askV", "$askV1", "$askV3", "$askV5",
],
"feature_columns_yesterday": [
"$open_1", "$high_1", "$low_1", "$close_1", "$vwap_1", "$bid_1", "$ask_1", "$volume_1",
"$bidV_1", "$bidV1_1", "$bidV3_1", "$bidV5_1", "$askV_1", "$askV1_1", "$askV3_1", "$askV5_1",
],
}
)
# fmt: on
exchange_config = ExchangeConfig(
limit_threshold=("$ask == 0", "$bid == 0"),
deal_price=("If($ask == 0, $bid, $ask)", "If($bid == 0, $ask, $bid)"),
volume_threshold={
"all": ("cum", "0.2 * DayCumsum($volume, '9:30', '14:29')"),
"buy": ("current", "$askV1"),
"sell": ("current", "$bidV1"),
},
open_cost=0.0005,
close_cost=0.0015,
min_cost=5.0,
trade_unit=None,
cash_limit=None,
generate_report=False,
)
def _inner_executor_fn(time_per_step: str, common_infra: CommonInfrastructure) -> NestedExecutor:
return NestedExecutor(
time_per_step=time_per_step,
inner_strategy=TWAPStrategy(),
inner_executor=SimulatorExecutor(
time_per_step="1min",
verbose=False,
trade_type=SimulatorExecutor.TT_SERIAL,
generate_report=False,
common_infra=common_infra,
track_data=True,
),
common_infra=common_infra,
track_data=True,
)
def get_simulator(order: Order) -> QlibSimulator:
return QlibSimulator(
order=order,
time_per_step="30min",
qlib_config=qlib_config,
inner_executor_fn=_inner_executor_fn,
exchange_config=exchange_config,
)

151
qlib/rl/order_execution/tests/test_simulator_qlib.py
View File

@@ -1,98 +1,89 @@
from pathlib import Path
import pandas as pd
from qlib.backtest.decision import Order, OrderDir
from qlib.backtest.executor import NestedExecutor, SimulatorExecutor
from qlib.backtest.utils import CommonInfrastructure
from qlib.config import QlibConfig
from qlib.contrib.strategy import TWAPStrategy
from qlib.rl.order_execution import CategoricalActionInterpreter
from qlib.rl.order_execution.simulator_qlib import ExchangeConfig, QlibSimulator
# fmt: off
qlib_config = QlibConfig(
{
"provider_uri_day": Path("C:/workspace/NeuTrader/data_sample/cn/qlib_amc_1d"),
"provider_uri_1min": Path("C:/workspace/NeuTrader/data_sample/cn/qlib_amc_1min"),
"feature_root_dir": Path("C:/workspace/NeuTrader/data_sample/cn/qlib_amc_handler_stock"),
"feature_columns_today": [
"$open", "$high", "$low", "$close", "$vwap", "$bid", "$ask", "$volume",
"$bidV", "$bidV1", "$bidV3", "$bidV5", "$askV", "$askV1", "$askV3", "$askV5",
],
"feature_columns_yesterday": [
"$open_1", "$high_1", "$low_1", "$close_1", "$vwap_1", "$bid_1", "$ask_1", "$volume_1",
"$bidV_1", "$bidV1_1", "$bidV3_1", "$bidV5_1", "$askV_1", "$askV1_1", "$askV3_1", "$askV5_1",
],
}
)
# fmt: on
exchange_config = ExchangeConfig(
limit_threshold=("$ask == 0", "$bid == 0"),
deal_price=("If($ask == 0, $bid, $ask)", "If($bid == 0, $ask, $bid)"),
volume_threshold={
"all": ("cum", "0.2 * DayCumsum($volume, '9:45', '14:44')"),
"buy": ("current", "$askV1"),
"sell": ("current", "$bidV1"),
},
open_cost=0.0005,
close_cost=0.0015,
min_cost=5.0,
trade_unit=None,
cash_limit=None,
generate_report=False,
)
from qlib.rl.order_execution.tests.common import get_simulator
def _inner_executor_fn(time_per_step: str, common_infra: CommonInfrastructure) -> NestedExecutor:
return NestedExecutor(
time_per_step=time_per_step,
inner_strategy=TWAPStrategy(),
inner_executor=SimulatorExecutor(
time_per_step="1min",
verbose=False,
trade_type=SimulatorExecutor.TT_SERIAL,
generate_report=False,
common_infra=common_infra,
track_data=True,
),
common_infra=common_infra,
track_data=True,
)
def is_close(a: float, b: float, epsilon: float = 1e-4) -> bool:
return abs(a - b) <= epsilon
def test():
def test_simulator_first_step():
TOTAL_POSITION = 2100.0
order = Order(
stock_id="SH600000",
amount=1078.644160270691,
direction=OrderDir(1),
start_time=pd.Timestamp("2019-03-04 09:45:00"),
end_time=pd.Timestamp("2019-03-04 14:44:00"),
amount=TOTAL_POSITION,
direction=OrderDir.BUY,
start_time=pd.Timestamp("2019-03-04 09:30:00"),
end_time=pd.Timestamp("2019-03-04 14:29:00"),
)
simulator = QlibSimulator(
order=order,
time_per_step="30min",
qlib_config=qlib_config,
inner_executor_fn=_inner_executor_fn,
exchange_config=exchange_config,
)
interpreter_action = CategoricalActionInterpreter(values=4)
simulator = get_simulator(order)
state = simulator.get_state()
print(state.position)
for i in range(10):
print(f"Step {i}")
simulator.step(interpreter_action(state, 1))
assert state.cur_time == pd.Timestamp('2019-03-04 09:30:00')
assert state.position == TOTAL_POSITION
state = simulator.get_state()
print(state.position)
AMOUNT = 300.0
simulator.step(AMOUNT)
state = simulator.get_state()
assert state.cur_time == pd.Timestamp('2019-03-04 10:00:00')
assert state.position == TOTAL_POSITION - AMOUNT
assert len(state.history_exec) == 30
assert state.history_exec.index[0] == pd.Timestamp('2019-03-04 09:30:00')
if simulator.done():
break
assert is_close(state.history_exec["market_volume"].iloc[0], 109382.382812)
assert is_close(state.history_exec["market_price"].iloc[0], 149.566483)
assert (state.history_exec["amount"] == AMOUNT / 30).all()
assert (state.history_exec["deal_amount"] == AMOUNT / 30).all()
assert is_close(state.history_exec["trade_price"].iloc[0], 149.566483)
assert is_close(state.history_exec["trade_value"].iloc[0], 1495.664825)
assert is_close(state.history_exec["position"].iloc[0], TOTAL_POSITION - AMOUNT / 30)
# assert state.history_exec["ffr"].iloc[0] == 1 / 60 # FIXME
assert is_close(state.history_steps["market_volume"].iloc[0], 1254848.5756835938)
assert state.history_steps["amount"].iloc[0] == AMOUNT
assert state.history_steps["deal_amount"].iloc[0] == AMOUNT
assert state.history_steps["ffr"].iloc[0] == 1.0
assert is_close(
state.history_steps["pa"].iloc[0] * (1.0 if order.direction == OrderDir.SELL else -1.0),
(state.history_steps["trade_price"].iloc[0] / simulator.twap_price - 1) * 10000,
)
def test_simulator_stop_twap() -> None:
TOTAL_POSITION = 2100.0
order = Order(
stock_id="SH600000",
amount=TOTAL_POSITION,
direction=OrderDir.BUY,
start_time=pd.Timestamp("2019-03-04 09:30:00"),
end_time=pd.Timestamp("2019-03-04 14:29:00"),
)
simulator = get_simulator(order)
NUM_STEPS = 7
for i in range(NUM_STEPS):
simulator.step(TOTAL_POSITION / NUM_STEPS)
HISTORY_STEP_LENGTH = 30 * NUM_STEPS
state = simulator.get_state()
assert len(state.history_exec) == HISTORY_STEP_LENGTH
assert (state.history_exec["deal_amount"] == TOTAL_POSITION / HISTORY_STEP_LENGTH).all()
assert is_close(state.history_steps["position"].iloc[0], TOTAL_POSITION * (NUM_STEPS - 1) / NUM_STEPS)
assert is_close(state.history_steps["position"].iloc[-1], 0.0)
assert is_close(state.position, 0.0)
assert is_close(state.metrics["ffr"], 1.0)
# assert abs(state.metrics["market_price"] - state.backtest_data.get_deal_price().mean()) < 1e-4
# assert np.isclose(state.metrics["market_volume"], state.backtest_data.get_volume().sum())
assert is_close(state.metrics["trade_price"], state.metrics["market_price"])
assert is_close(state.metrics["pa"], 0.0)
if __name__ == "__main__":
test()
test_simulator_first_step()
test_simulator_stop_twap()