| |
| |
|
|
| import sys |
| from pathlib import Path |
| from typing import Tuple |
|
|
| import pandas as pd |
| import pytest |
|
|
| from qlib.backtest.decision import Order, OrderDir |
| from qlib.backtest.executor import SimulatorExecutor |
| from qlib.rl.order_execution import CategoricalActionInterpreter |
| from qlib.rl.order_execution.simulator_qlib import SingleAssetOrderExecution |
|
|
| TOTAL_POSITION = 2100.0 |
|
|
| python_version_request = pytest.mark.skipif(sys.version_info < (3, 8), reason="requires python3.8 or higher") |
|
|
|
|
| def is_close(a: float, b: float, epsilon: float = 1e-4) -> bool: |
| return abs(a - b) <= epsilon |
|
|
|
|
| def get_order() -> Order: |
| return 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"), |
| ) |
|
|
|
|
| def get_configs(order: Order) -> Tuple[dict, dict]: |
| executor_config = { |
| "class": "NestedExecutor", |
| "module_path": "qlib.backtest.executor", |
| "kwargs": { |
| "time_per_step": "1day", |
| "inner_strategy": {"class": "ProxySAOEStrategy", "module_path": "qlib.rl.order_execution.strategy"}, |
| "track_data": True, |
| "inner_executor": { |
| "class": "NestedExecutor", |
| "module_path": "qlib.backtest.executor", |
| "kwargs": { |
| "time_per_step": "30min", |
| "inner_strategy": { |
| "class": "TWAPStrategy", |
| "module_path": "qlib.contrib.strategy.rule_strategy", |
| }, |
| "inner_executor": { |
| "class": "SimulatorExecutor", |
| "module_path": "qlib.backtest.executor", |
| "kwargs": { |
| "time_per_step": "1min", |
| "verbose": False, |
| "trade_type": SimulatorExecutor.TT_SERIAL, |
| "generate_report": False, |
| "track_data": True, |
| }, |
| }, |
| "track_data": True, |
| }, |
| }, |
| "start_time": pd.Timestamp(order.start_time.date()), |
| "end_time": pd.Timestamp(order.start_time.date()), |
| }, |
| } |
|
|
| exchange_config = { |
| "freq": "1min", |
| "codes": [order.stock_id], |
| "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, |
| } |
|
|
| return executor_config, exchange_config |
|
|
|
|
| def get_simulator(order: Order) -> SingleAssetOrderExecution: |
| DATA_ROOT_DIR = Path(__file__).parent.parent / ".data" / "rl" / "qlib_simulator" |
|
|
| |
| qlib_config = { |
| "provider_uri_day": DATA_ROOT_DIR / "qlib_1d", |
| "provider_uri_1min": DATA_ROOT_DIR / "qlib_1min", |
| "feature_root_dir": DATA_ROOT_DIR / "qlib_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", |
| ], |
| } |
| |
|
|
| executor_config, exchange_config = get_configs(order) |
|
|
| return SingleAssetOrderExecution( |
| order=order, |
| qlib_config=qlib_config, |
| executor_config=executor_config, |
| exchange_config=exchange_config, |
| ) |
|
|
|
|
| @python_version_request |
| def test_simulator_first_step(): |
| order = get_order() |
| simulator = get_simulator(order) |
| state = simulator.get_state() |
| assert state.cur_time == pd.Timestamp("2019-03-04 09:30:00") |
| assert state.position == TOTAL_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") |
|
|
| 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 is_close(state.history_exec["ffr"].iloc[0], AMOUNT / TOTAL_POSITION / 30) |
|
|
| 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] == AMOUNT / TOTAL_POSITION |
| 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, |
| ) |
|
|
|
|
| @python_version_request |
| def test_simulator_stop_twap() -> None: |
| order = get_order() |
| 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 is_close(state.metrics["market_price"], state.backtest_data.get_deal_price().mean()) |
| assert is_close(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) |
|
|
| assert simulator.done() |
|
|
|
|
| @python_version_request |
| def test_interpreter() -> None: |
| NUM_EXECUTION = 3 |
| order = get_order() |
| simulator = get_simulator(order) |
| interpreter_action = CategoricalActionInterpreter(values=NUM_EXECUTION) |
|
|
| NUM_STEPS = 7 |
| state = simulator.get_state() |
| position_history = [] |
| for i in range(NUM_STEPS): |
| simulator.step(interpreter_action(state, 1)) |
| state = simulator.get_state() |
| position_history.append(state.position) |
|
|
| assert position_history[-1] == max(TOTAL_POSITION - TOTAL_POSITION / NUM_EXECUTION * (i + 1), 0.0) |
|
|
