add position test

qlib/backtest/__init__.py

@@ -104,19 +104,28 @@ def create_account_instance(
 
     Parameters
     ----------
-    start_time :
+    start_time
         start time of the benchmark
-    end_time :
+    end_time
         end time of the benchmark
     benchmark : str
         the benchmark for reporting
-    account : Union[float, int, {"cash": float, "stock1": {"amount": int, "price"(optional): float}, "stock2": {"amount": int}}]
+    account :   Union[
+                    float,
+                    {
+                        "cash": float,
+                        "stock1": Union[
+                                        int,    # it is equal to {"amount": int}
+                                        {"amount": int, "price"(optional): float},
+                                  ]
+                    },
+                ]
         information for describing how to creating the account
-        For `float` or `int`:
+        For `float`:
             Using Account with only initial cash
         For `dict`:
             key "cash" means initial cash.
-            key "stock1" means the first stock information with amount and price(optional).
+            key "stock1" means the information of first stock with amount and price(optional).
             ...
     """
     if isinstance(account, (int, float)):

qlib/backtest/account.py

@@ -80,9 +80,15 @@ class Account:
         ----------
         init_cash : float, optional
             initial cash, by default 1e9
-        position_dict : Dict[stock_id, {"amount": int, "price"(optional): float}], optional
-            initial stocks with amount and price,
-            if there is no price key in the dict of stocks, it will be filled by latest close price from qlib.
+        position_dict : Dict[
+                            stock_id,
+                            Union[
+                                int,  # it is equal to {"amount": int}
+                                {"amount": int, "price"(optional): float},
+                            ]
+                        ]
+            initial stocks with parameters amount and price,
+            if there is no price key in the dict of stocks, it will be filled by _fill_stock_value.
             by default {}.
         """
 
@@ -122,6 +128,8 @@ class Account:
             self.report = Report(freq, benchmark_config)
             self.positions = {}
             # fill stock value
+            # The frequency of account may not align with the trading frequency.
+            # This may result in obscure bugs when data quality is low.
             self.current.fill_stock_value(self.benchmark_config["start_time"], self.freq)
 
         # trading related metrics(e.g. high-frequency trading)
@@ -186,7 +194,8 @@ class Account:
         # The cost will be substracted from the cash at last. So the trading logic can ignore the cost calculation
         if order.direction == Order.SELL:
             # sell stock
-            self._update_state_from_order(order, trade_val, cost, trade_price)
+            if getattr(self, "accum_info") is not None:
+                self._update_state_from_order(order, trade_val, cost, trade_price)
             # update current position
             # for may sell all of stock_id
             self.current.update_order(order, trade_val, cost, trade_price)
@@ -194,7 +203,8 @@ class Account:
             # buy stock
             # deal order, then update state
             self.current.update_order(order, trade_val, cost, trade_price)
-            self._update_state_from_order(order, trade_val, cost, trade_price)
+            if getattr(self, "accum_info") is not None:
+                self._update_state_from_order(order, trade_val, cost, trade_price)
 
     def update_bar_count(self):
         """at the end of the trading bar, update holding bar, count of stock"""
@@ -311,7 +321,6 @@ class Account:
         self.update_current(trade_start_time, trade_end_time, trade_exchange)
         if self.is_port_metr_enabled():
             # report is portfolio related analysis
-            print(trade_start_time, trade_end_time)
             self.update_report(trade_start_time, trade_end_time)
 
         # TODO: will skip empty decisions make it faster?  `outer_trade_decision.empty():`

qlib/backtest/exchange.py

@@ -713,12 +713,11 @@ class Exchange:
                 f"Order clipped due to volume limitation: {order}, {[(vol, rule) for vol, rule in zip(vol_limit_num, vol_limit)]}"
             )
 
-    def _cal_trade_amount_by_cash_limit(self, now_trade_amount, trade_price, order, position):
+    def _get_max_amount_by_cash_limit(self, trade_price, order, position):
         """return the real order amount after cash limit.
 
         Parameters
         ----------
-        now_trade_amount : float
         trade_price : float
         order : Order
         position : Position
@@ -729,27 +728,24 @@ class Exchange:
             the real order amount after cash limit.
         """
         cash = position.get_cash()
-        trade_val = now_trade_amount * trade_price
-        if order.direction == Order.SELL:
-            if cash < trade_val * self.close_cost:
-                # The money is not enough
-                self.logger.debug(f"Order clipped due to cash limitation: {order}")
-                return self.round_amount_by_trade_unit(cash / self.close_cost, order.factor)
-        elif order.direction == Order.BUY:
-            if cash < trade_val * (1 + self.open_cost):
-                # The money is not enough
-                self.logger.debug(f"Order clipped due to cash limitation: {order}")
-                return self.round_amount_by_trade_unit(cash / (1 + self.open_cost) / trade_price, order.factor)
+        max_trade_amount = 0
+        if cash >= self.min_cost:
+            if order.direction == Order.SELL:
+                max_trade_amount = cash / self.close_cost / trade_price
+            elif order.direction == Order.BUY:
+                critical_amount = self.min_cost / (self.open_cost * trade_price)
+                critical_price = critical_amount * trade_price + self.min_cost
+                if cash >= critical_price:
+                    max_trade_amount = cash / (1 + self.open_cost) / trade_price
+                else:
+                    max_trade_amount = (cash - self.min_cost) / trade_price
+        return max_trade_amount
 
-        # The money is enough
-        return self.round_amount_by_trade_unit(now_trade_amount, order.factor)
-
-    def _cal_trade_amount_by_stock_limit(self, now_trade_amount, order, position):
+    def _get_max_amount_by_stock_limit(self, order, position):
         """return the real order amount after stock amount limit.
 
         Parameters
         ----------
-        now_trade_amount : float
         order : Order
         position : Position
 
@@ -760,15 +756,9 @@ class Exchange:
         """
         if order.direction == Order.SELL:
             current_amount = position.get_stock_amount(order.stock_id) if position.check_stock(order.stock_id) else 0
-            if np.isclose(now_trade_amount, current_amount):
-                # when selling last stock. The amount don't need rounding
-                return now_trade_amount
-            elif now_trade_amount > current_amount:
-                return self.round_amount_by_trade_unit(current_amount, order.factor)
-            else:
-                return self.round_amount_by_trade_unit(now_trade_amount, order.factor)
+            return current_amount
         elif order.direction == Order.BUY:
-            return self.round_amount_by_trade_unit(now_trade_amount, order.factor)
+            return np.inf
 
     def _calc_trade_info_by_order(self, order, position: Position, dealt_order_amount):
         """
@@ -779,18 +769,33 @@ class Exchange:
         :param order:
         :param position: Position
         :param dealt_order_amount: the dealt order amount dict with the format of {stock_id: float}
-        :return: trade_val, trade_cost
+        :return: trade_price, trade_val, trade_cost
         """
 
         trade_price = self.get_deal_price(order.stock_id, order.start_time, order.end_time, direction=order.direction)
         order.factor = self.get_factor(order.stock_id, order.start_time, order.end_time)
+        # get all limits amount
+        # cash limit
+        cash_max_amount = self._get_max_amount_by_cash_limit(trade_price, order, position)
+        # held stock limit
+        stock_max_amount = self._get_max_amount_by_stock_limit(order, position)
+
         if order.direction == Order.SELL:
             # sell
             if position is not None:
-                now_trade_amount = order.amount
-                now_trade_amount = self._cal_trade_amount_by_stock_limit(now_trade_amount, order, position)
-                now_trade_amount = self._cal_trade_amount_by_cash_limit(now_trade_amount, trade_price, order, position)
-                order.deal_amount = now_trade_amount
+                if np.isclose(order.amount, stock_max_amount):
+                    # when selling last stock. The amount don't need rounding
+                    if stock_max_amount <= cash_max_amount:
+                        order.deal_amount = stock_max_amount
+                    else:
+                        order.deal_amount = self.round_amount_by_trade_unit(cash_max_amount, order.factor)
+                else:
+                    now_trade_amount = min(order.amount, stock_max_amount)
+                    if now_trade_amount > cash_max_amount:
+                        self.logger.debug(f"Order clipped due to cash limitation: {order}")
+                    order.deal_amount = self.round_amount_by_trade_unit(
+                        min(now_trade_amount, cash_max_amount), order.factor
+                    )
             else:
                 # TODO: We don't know current position.
                 #  We choose to sell all
@@ -802,9 +807,9 @@ class Exchange:
         elif order.direction == Order.BUY:
             # buy
             if position is not None:
-                now_trade_amount = order.amount
-                now_trade_amount = self._cal_trade_amount_by_cash_limit(now_trade_amount, trade_price, order, position)
-                order.deal_amount = now_trade_amount
+                if order.amount > cash_max_amount:
+                    self.logger.debug(f"Order clipped due to cash limitation: {order}")
+                order.deal_amount = self.round_amount_by_trade_unit(min(order.amount, cash_max_amount), order.factor)
             else:
                 # Unknown amount of money. Just round the amount
                 order.deal_amount = self.round_amount_by_trade_unit(order.amount, order.factor)

qlib/backtest/position.py

@@ -246,7 +246,13 @@ class Position(BasePosition):
             the start time of backtest. It's for filling the initial value of stocks.
         cash : float, optional
             initial cash in account, by default 0
-        position_dict : Dict[stock_id, {"amount": int, "price"(optional): float}], optional
+        position_dict : Dict[
+                            stock_id,
+                            Union[
+                                int,  # it is equal to {"amount": int}
+                                {"amount": int, "price"(optional): float},
+                            ]
+                        ]
             initial stocks with parameters amount and price,
             if there is no price key in the dict of stocks, it will be filled by _fill_stock_value.
             by default {}.
@@ -256,8 +262,10 @@ class Position(BasePosition):
         # NOTE: The position dict must be copied!!!
         # Otherwise the initial value
         self.init_cash = cash
-        self.init_stock_info = position_dict.copy()
-        self.position = self.init_stock_info.copy()
+        self.position = position_dict.copy()
+        for stock in self.position:
+            if isinstance(self.position[stock], int):
+                self.position[stock] = {"amount": self.position[stock]}
         self.position["cash"] = cash
 
         # If the stock price information is missing, the account value will not be calculated temporarily
@@ -277,7 +285,9 @@ class Position(BasePosition):
             the days to get the latest close price, by default 30.
         """
         stock_list = []
-        for stock in self.init_stock_info:
+        for stock in self.position:
+            if not isinstance(self.position[stock], dict):
+                continue
             if ("price" not in self.position[stock]) or (self.position[stock]["price"] is None):
                 stock_list.append(stock)
 
@@ -298,8 +308,7 @@ class Position(BasePosition):
             raise ValueError(f"{lack_stock} doesn't have close price in qlib in the latest {last_days} days")
 
         for stock in stock_list:
-            self.init_stock_info[stock]["price"] = price_dict[stock]
-        self.position.update(self.init_stock_info)
+            self.position[stock]["price"] = price_dict[stock]
         self.position["now_account_value"] = self.calculate_value()
 
     def _init_stock(self, stock_id, amount, price=None):

tests/backtest/test_file_strategy.py

@@ -27,6 +27,8 @@ class FileStrTest(TestAutoData):
             ["20200102", self.TEST_INST, "1000", "sell"],
             ["20200103", self.TEST_INST, "1000", "buy"],
             ["20200106", self.TEST_INST, "1000", "sell"],
+            ["20200106", self.TEST_INST, "1000", "buy"],
+            ["20200106", self.TEST_INST, "949.7773413058803", "sell"],
         ]
         return pd.DataFrame(orders, columns=headers).set_index(["datetime", "instrument"])
 
@@ -62,7 +64,7 @@ class FileStrTest(TestAutoData):
                 "close_cost": 0.0015,
                 "min_cost": 5,
                 "codes": codes,
-                "trade_unit": None,
+                "trade_unit": 100,
             },
             # "pos_type": "InfPosition"  # Position with infinitive position
         }

tests/backtest/test_init_position.py

@@ -0,0 +1,119 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+import unittest
+import qlib
+from qlib.backtest import backtest, order
+from qlib.tests import TestAutoData
+from qlib.backtest.order import TradeDecisionWO, TradeRangeByTime
+import pandas as pd
+from pathlib import Path
+
+
+class FileStrTest(TestAutoData):
+
+    TEST_INST = "SH600519"
+
+    def init_qlib(self):
+        provider_uri_day = "/nfs_data1/stock_data/huaxia_1d_qlib"
+        provider_uri_1min = "/nfs_data1/stock_data/huaxia_1min_qlib"
+        provider_uri_map = {"1min": provider_uri_1min, "day": provider_uri_day}
+
+        client_config = {
+            "calendar_provider": {
+                "class": "LocalCalendarProvider",
+                "module_path": "qlib.data.data",
+                "kwargs": {
+                    "backend": {
+                        "class": "FileCalendarStorage",
+                        "module_path": "qlib.data.storage.file_storage",
+                        "kwargs": {"provider_uri_map": provider_uri_map},
+                    }
+                },
+            },
+            "feature_provider": {
+                "class": "LocalFeatureProvider",
+                "module_path": "qlib.data.data",
+                "kwargs": {
+                    "backend": {
+                        "class": "FileFeatureStorage",
+                        "module_path": "qlib.data.storage.file_storage",
+                        "kwargs": {"provider_uri_map": provider_uri_map},
+                    }
+                },
+            },
+        }
+        qlib.init(provider_uri=provider_uri_day, **client_config, expression_cache=None, dataset_cache=None)
+
+    def test_file_str(self):
+        freq = "1min"
+        inst = ["SH600000", "SH600011"]
+        start_time = "2020-01-01"
+        end_time = "2020-01-15 15:00"
+
+        strategy_config = {
+            "class": "RandomOrderStrategy",
+            "module_path": "qlib.contrib.strategy.rule_strategy",
+            "kwargs": {
+                "trade_range": TradeRangeByTime("9:30", "15:00"),
+                "sample_ratio": 1.0,
+                "volume_ratio": 0.01,
+                "market": inst,
+            },
+        }
+        position_dict = {
+            "cash": 100000000,
+            "SH600000": {"amount": 100},
+            "SH600011": {"amount": 101},
+        }
+        backtest_config = {
+            "start_time": start_time,
+            "end_time": end_time,
+            "account": position_dict,
+            "benchmark": None,  # benchmark is not required here for trading
+            "exchange_kwargs": {
+                "freq": freq,
+                "limit_threshold": 0.095,
+                "deal_price": "close",
+                "open_cost": 0.0005,
+                "close_cost": 0.0015,
+                "min_cost": 5,
+                "codes": inst,
+            },
+            "pos_type": "Position",  # Position with infinitive position
+        }
+        executor_config = {
+            "class": "NestedExecutor",
+            "module_path": "qlib.backtest.executor",
+            "kwargs": {
+                "time_per_step": "day",
+                "inner_executor": {
+                    "class": "SimulatorExecutor",
+                    "module_path": "qlib.backtest.executor",
+                    "kwargs": {
+                        "time_per_step": freq,
+                        "generate_report": False,
+                        "verbose": False,
+                        # "verbose": True,
+                        "indicator_config": {
+                            "show_indicator": False,
+                        },
+                    },
+                },
+                "inner_strategy": {
+                    "class": "TWAPStrategy",
+                    "module_path": "qlib.contrib.strategy.rule_strategy",
+                },
+                "track_data": True,
+                "generate_report": True,
+                "indicator_config": {
+                    "show_indicator": True,
+                },
+            },
+        }
+        self.init_qlib()
+        backtest(executor=executor_config, strategy=strategy_config, **backtest_config)
+
+
+if __name__ == "__main__":
+    unittest.main()