From 64d807a2445576c5127e02d7e70f24e106b79b31 Mon Sep 17 00:00:00 2001 From: sal Date: Sun, 29 Oct 2023 15:05:35 -0500 Subject: [PATCH] updated --- appveyor.yml | 2 +- docs/_modules/pyqstrat/evaluator.html | 9 +- docs/_modules/pyqstrat/pq_types.html | 40 +- docs/_modules/pyqstrat/pq_utils.html | 21 +- docs/_modules/pyqstrat/strategy.html | 25 +- docs/_modules/pyqstrat/strategy_builder.html | 22 +- .../pyqstrat/strategy_components.html | 331 +++++++++++---- docs/genindex.html | 112 +++-- docs/modules.html | 58 ++- docs/objects.inv | Bin 3254 -> 3401 bytes docs/pyqstrat.html | 394 ++++++++++++++---- docs/searchindex.js | 2 +- 12 files changed, 771 insertions(+), 245 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index e0a7687..ece5436 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -53,7 +53,7 @@ for: - mypy --ignore-missing-imports pyqstrat/ - flake8 --ignore W291,W293,W503,E402,E701,E275,E741 --max-line-length=160 pyqstrat/ # run notebooks and exit on first error - - find pyqstrat/notebooks -name '*.ipynb' | xargs -n1 sh -c 'ipython $0 || exit 255' + - find pyqstrat/notebooks -name '*.ipynb' | xargs -n1 sh -c 'ipython --no-automagic $0 || exit 255' - matrix: diff --git a/docs/_modules/pyqstrat/evaluator.html b/docs/_modules/pyqstrat/evaluator.html index b98eeae..26c9c76 100644 --- a/docs/_modules/pyqstrat/evaluator.html +++ b/docs/_modules/pyqstrat/evaluator.html @@ -701,7 +701,7 @@

Source code for pyqstrat.evaluator

 
 

 [docs]
-def plot_return_metrics(metrics: dict[str, Any], title='', height=1000, width=0, show_points=True, show=True) -> go.Figure:
+def plot_return_metrics(metrics: dict[str, Any], title='', height=1000, width=0, show_points=False, show=True) -> go.Figure:
     '''
     Plot equity, rolling drawdowns and and a boxplot of annual returns given the output of compute_return_metrics.
     
@@ -758,6 +758,8 @@ 
Source code for pyqstrat.evaluator
     fig.add_trace(go.Box(x=all_rets, boxmean=True, marker_color='blue', line_color='blue', name='All'), row=3, col=1)
     if show_points:
         fig.update_traces(boxpoints='all', jitter=0.1, row=3, col=1)
+    else:
+        fig.update_traces(boxpoints=False, row=3, col=1)
 
     fig.update_yaxes(title_text="Equity", type="log", row=1, col=1)
     fig.update_yaxes(title_text="Drawdown", row=2, col=1)
@@ -780,8 +782,9 @@ 
Source code for pyqstrat.evaluator
     
     ev = compute_return_metrics(timestamps, rets, starting_equity)
     display_return_metrics(ev.metrics())
-    plot_return_metrics(ev.metrics())
-    
+    plot_return_metrics(ev.metrics(), show_points=False)
+    plot_return_metrics(ev.metrics(), show_points=True)
+
     assert_(round(ev.metric('sharpe'), 6) == 2.932954)
     assert_(round(ev.metric('sortino'), 6) == 5.690878)
     assert_(ev.metric('annual_returns')[0] == [2018])
diff --git a/docs/_modules/pyqstrat/pq_types.html b/docs/_modules/pyqstrat/pq_types.html
index 6f4ee64..05cb78f 100644
--- a/docs/_modules/pyqstrat/pq_types.html
+++ b/docs/_modules/pyqstrat/pq_types.html
@@ -77,6 +77,13 @@ 
Source code for pyqstrat.pq_types
         return ContractGroup._instances[name]

 
     
+

+[docs]
+    @staticmethod
+    def get_default() -> ContractGroup:
+        return DEFAULT_CG

+
+    
 

 [docs]
     @staticmethod
@@ -107,8 +114,14 @@ 
Source code for pyqstrat.pq_types
 [docs]
     @staticmethod
     def clear_cache() -> None:
-        ContractGroup.contracts = {}
-        ContractGroup.contracts = {}

+        ContractGroup._instances = {}

+
+        
+

+[docs]
+    def clear(self) -> None:
+        '''Remove all contracts'''
+        self.contracts.clear()

 
         
     def __repr__(self) -> str:
@@ -198,6 +211,22 @@ 
Source code for pyqstrat.pq_types
         return Contract._instances.get(name)

 
     
+

+[docs]
+    @staticmethod
+    def get_or_create(symbol: str, 
+                      contract_group: ContractGroup | None = None, 
+                      expiry: np.datetime64 | None = None, 
+                      multiplier: float = 1., 
+                      components: list[tuple[Contract, float]] | None = None,
+                      properties: SimpleNamespace | None = None) -> Contract:
+        if symbol in Contract._instances:
+            contract = Contract._instances.get(symbol)
+        else:
+            contract = Contract.create(symbol, contract_group, expiry, multiplier, components, properties)
+        return contract  # type: ignore

+
+    
 

 [docs]
     @staticmethod
@@ -387,8 +416,11 @@ 
Source code for pyqstrat.pq_types
 @dataclass(kw_only=True)
 class MarketOrder(Order):
     def __post_init__(self):
-        if not np.isfinite(self.qty) or math.isclose(self.qty, 0):
-            raise ValueError(f'order qty must be finite and nonzero: {self.qty}')
+        try:
+            if not np.isfinite(self.qty) or math.isclose(self.qty, 0):
+                raise ValueError(f'order qty must be finite and nonzero: {self.qty}')
+        except Exception as ex:
+            _logger.info(ex)
             
     def __repr__(self):
         timestamp = pd.Timestamp(self.timestamp).to_pydatetime()
diff --git a/docs/_modules/pyqstrat/pq_utils.html b/docs/_modules/pyqstrat/pq_utils.html
index eb12251..881f981 100644
--- a/docs/_modules/pyqstrat/pq_utils.html
+++ b/docs/_modules/pyqstrat/pq_utils.html
@@ -573,7 +573,7 @@ 
Source code for pyqstrat.pq_utils
     for period in ['D', 'M', 'm', 's']:
         ret = try_frequency(timestamps, period, threshold)
         if math.isfinite(ret): return ret
-    assert_(False, f'could not infer frequency from timestamps: {timestamps}')
+    assert_(False, f'could not infer frequency from timestamps: {timestamps[:100]} ...')
     return math.nan  # will never execute but keeps mypy happy

 
 
@@ -777,7 +777,6 @@ 
Source code for pyqstrat.pq_utils
                         formatter: logging.Formatter | None = None) -> None:
     if formatter is None: formatter = logging.Formatter(fmt=LOG_FORMAT, datefmt=DATE_FORMAT)
     stream_handler = logging.StreamHandler(sys.stdout)
-    # stream_handler = logging.StreamHandler()
     stream_handler.setFormatter(formatter)
     stream_handler.setLevel(log_level)
     logger.addHandler(stream_handler)
@@ -786,7 +785,6 @@ 
Source code for pyqstrat.pq_utils
 

 [docs]
 def get_main_logger() -> logging.Logger:
-    # sys.stderr = sys.stdout
     main_logger = logging.getLogger('pq')
     if len(main_logger.handlers): return main_logger
     _add_stream_handler(main_logger)
@@ -813,7 +811,16 @@ 
Source code for pyqstrat.pq_utils
     Whether we are running in an ipython (or Jupyter) environment
     '''
     import builtins
-    return '__IPYTHON__' in vars(builtins)

+    if ('__IPYTHON__' in vars(builtins)): return True
+    return False

+
+
+
+

+[docs]
+def in_debug() -> bool:
+    if 'PQ_DEBUG_MODE' in os.environ: return True
+    return False

 
 
 
@@ -832,7 +839,11 @@ 
Source code for pyqstrat.pq_utils
     using the python optimization switch
     '''
     if msg is None: msg = ''
-    if not condition: raise PQException(msg)

+    if not condition:
+        if in_debug():
+            import pdb
+            pdb.set_trace()
+        raise PQException(msg)

 
 
 
diff --git a/docs/_modules/pyqstrat/strategy.html b/docs/_modules/pyqstrat/strategy.html
index a538bd6..788073f 100644
--- a/docs/_modules/pyqstrat/strategy.html
+++ b/docs/_modules/pyqstrat/strategy.html
@@ -103,6 +103,8 @@ 
Source code for pyqstrat.strategy
                  pnl_calc_time: int = 16 * 60 + 1,
                  trade_lag: int = 0,
                  run_final_calc: bool = True, 
+                 log_trades: bool = True,
+                 log_orders: bool = False,
                  strategy_context: StrategyContextType | None = None) -> None:
         '''
         Args:
@@ -120,6 +122,8 @@ 
Source code for pyqstrat.strategy
             strategy_context: A storage class where you can store key / value pairs relevant to this strategy.
                 For example, you may have a pre-computed table of correlations that you use in the indicator or trade rule functions.  
                 If not set, the __init__ function will create an empty member strategy_context object that you can access.
+            log_trades: If set, we log orders as they are created
+            log_orders: If set, we log trades as they are created
         '''
         self.name = 'main'  # Set by portfolio when running multiple strategies
         increasing_ts: bool = bool(np.all(np.diff(timestamps.astype(int)) > 0))
@@ -134,6 +138,8 @@ 
Source code for pyqstrat.strategy
         assert_(trade_lag >= 0, f'trade_lag cannot be negative: {trade_lag}')
         self.trade_lag = trade_lag
         self.run_final_calc = run_final_calc
+        self.log_trades = log_trades
+        self.log_orders = log_orders
         self.indicators: dict[str, IndicatorType] = {}
         self.signals: dict[str, SignalType] = {}
         self.signal_values: dict[str, SimpleNamespace] = defaultdict(types.SimpleNamespace)
@@ -470,6 +476,12 @@ 
Source code for pyqstrat.strategy
         
         for j, (rule_function, contract_group, params) in enumerate(rules):
             orders = self._get_orders(i, rule_function, contract_group, params)
+            if self.log_orders and len(orders) > 0:
+                if len(orders) > 1:
+                    _logger.info('ORDERS:' + ''.join([f'\n {order}' for order in orders]))
+                else:
+                    _logger.info(f'ORDER: {orders[0]}')
+                    
             self._orders += orders
             self._current_orders += orders
             # _logger.info(f'current_orders: {self._current_orders}')
@@ -507,9 +519,9 @@ 
Source code for pyqstrat.strategy
             if position_filter is not None:
                 curr_pos = self.account.position(contract_group, self.timestamps[idx])
                 if position_filter == 'zero' and not math.isclose(curr_pos, 0): return []
-                if position_filter == 'nonzero' and math.isclose(curr_pos, 0): return []
-                if position_filter == 'positive' and (curr_pos < 0 or math.isclose(curr_pos, 0)): return []
-                if position_filter == 'negative' and (curr_pos > 0 or math.isclose(curr_pos, 0)): return []
+                elif position_filter == 'nonzero' and math.isclose(curr_pos, 0): return []
+                elif position_filter == 'positive' and (curr_pos < 0 or math.isclose(curr_pos, 0)): return []
+                elif position_filter == 'negative' and (curr_pos > 0 or math.isclose(curr_pos, 0)): return []
                 
             orders = rule_function(contract_group, idx, self.timestamps, indicator_values, signal_values, self.account,
                                    self._current_orders, self.strategy_context)
@@ -551,6 +563,13 @@ 
Source code for pyqstrat.strategy
                                              self.indicator_values, 
                                              self.signal_values, 
                                              self.strategy_context)
+                
+                if self.log_trades and len(trades) > 0:
+                    if len(trades) > 1:
+                        _logger.info('TRADES:' + ''.join([f'\n {trade}' for trade in trades]))
+                    else:
+                        _logger.info(f'TRADE: {trades[0]}')
+
                 if len(trades): self.account.add_trades(trades)
                 self._trades += trades
             except Exception as e:
diff --git a/docs/_modules/pyqstrat/strategy_builder.html b/docs/_modules/pyqstrat/strategy_builder.html
index d2aec62..c4ecc35 100644
--- a/docs/_modules/pyqstrat/strategy_builder.html
+++ b/docs/_modules/pyqstrat/strategy_builder.html
@@ -105,6 +105,8 @@ 
Source code for pyqstrat.strategy_builder
     signals: list[tuple[str, SignalType, Sequence[ContractGroup] | None, Sequence[str] | None, Sequence[str] | None]]
     rules: list[tuple[str, RuleType, str, Sequence[Any] | None, str | None]]
     market_sims: list[MarketSimulatorType]
+    log_trades: bool
+    log_orders: bool
     
 

 [docs]
@@ -121,7 +123,9 @@ 
Source code for pyqstrat.strategy_builder
         self.indicators = []
         self.signals = []
         self.rules = []
-        self.market_sims = []

+        self.market_sims = []
+        self.log_trades = True
+        self.log_orders = False

 
         
 

@@ -155,6 +159,18 @@ 
Source code for pyqstrat.strategy_builder
         self.strategy_context = context

 
         
+

+[docs]
+    def set_log_trades(self, log_trades: bool) -> None:
+        self.log_trades = log_trades

+
+        
+

+[docs]
+    def set_log_orders(self, log_orders: bool) -> None:
+        self.log_orders = log_orders

+
+        
 

 [docs]
     def add_contract(self, symbol: str) -> Contract:
@@ -266,7 +282,9 @@ 
Source code for pyqstrat.strategy_builder
                          self.starting_equity, 
                          self.pnl_calc_time, 
                          self.trade_lag, 
-                         True, 
+                         True,
+                         self.log_trades,
+                         self.log_orders,
                          self.strategy_context)
         
         assert_(self.rules is not None and len(self.rules) > 0, 'rules cannot be empty or None')
diff --git a/docs/_modules/pyqstrat/strategy_components.html b/docs/_modules/pyqstrat/strategy_components.html
index d89307d..a8282c6 100644
--- a/docs/_modules/pyqstrat/strategy_components.html
+++ b/docs/_modules/pyqstrat/strategy_components.html
@@ -115,15 +115,62 @@ 
Source code for pyqstrat.strategy_components
[docs]
 def get_contract_price_from_array_dict(price_dict: dict[str, tuple[np.ndarray, np.ndarray]], 
                                        contract: Contract, 
-                                       timestamp: np.datetime64) -> float:
+                                       timestamp: np.datetime64,
+                                       allow_previous: bool) -> float:
     tup: tuple[np.ndarray, np.ndarray] | None = price_dict.get(contract.symbol)
     assert_(tup is not None, f'{contract.symbol} not found in price_dict')
-    _timestamps: np.ndarray = tup[0]  # type: ignore
-    idx = np_indexof_sorted(_timestamps, timestamp)
+    _timestamps, _prices = tup  # type: ignore
+    idx: int
+    if allow_previous:
+        idx = int(np.searchsorted(_timestamps, timestamp, side='right')) - 1
+    else:
+        idx = np_indexof_sorted(_timestamps, timestamp)
     if idx == -1: return math.nan
-    return tup[1][idx]  # type: ignore

+#     if idx >= len(_prices):
+#         import pdb
+#         pdb.set_trace()
+    return _prices[idx]  # type: ignore

+
+
+
+

+[docs]
+@dataclass
+class PriceFuncArrays:
+    '''
+    A function object with a signature of PriceFunctionType. Takes three ndarrays
+    of symbols, timestamps and prices
+    '''
+    price_dict: dict[str, tuple[np.ndarray, np.ndarray]]
+    allow_previous: bool
+        
+

+[docs]
+    def __init__(self, symbols: np.ndarray, timestamps: np.ndarray, prices: np.ndarray, allow_previous: bool = False) -> None:
+        assert_(len(timestamps) == len(symbols) and len(prices) == len(symbols),
+                f'arrays have different sizes: {len(timestamps)} {len(symbols)} {len(prices)}')
+        price_dict: dict[str, tuple[np.ndarray, np.ndarray]] = {}
+        for symbol in np.unique(symbols):
+            mask = (symbols == symbol)
+            price_dict[symbol] = (timestamps[mask], prices[mask])        
+        self.price_dict = price_dict
+        self.allow_previous = allow_previous

+
+        
+

+[docs]
+    def __call__(self, contract: Contract, timestamps: np.ndarray, i: int, context: StrategyContextType) -> float:
+        price: float = 0.
+        timestamp = timestamps[i]
+        if contract.is_basket():
+            for _contract, ratio in contract.components:
+                price += get_contract_price_from_array_dict(self.price_dict, _contract, timestamp, self.allow_previous) * ratio
+        else:
+            price = get_contract_price_from_array_dict(self.price_dict, contract, timestamp, self.allow_previous)
+        return price

+

+
 
-    
 
 

 [docs]
@@ -132,6 +179,11 @@ 
Source code for pyqstrat.strategy_components
    '''
     A function object with a signature of PriceFunctionType and takes a dictionary of 
         contract name -> tuple of sorted timestamps and prices
+    
+    Args:
+        price_dict: a dict with key=contract nane and value a tuple of timestamp and price arrays
+        allow_previous: if set and we don't find an exact match for the timestamp, use the 
+            previous timestamp. Useful if you have a dict with keys containing dates instead of timestamps
         
     >>> timestamps = np.arange(np.datetime64('2023-01-01'), np.datetime64('2023-01-04'))
     >>> price_dict = {'AAPL': (timestamps, [8, 9, 10]), 'IBM': (timestamps, [20, 21, 22])}
@@ -144,11 +196,13 @@ 
Source code for pyqstrat.strategy_components
    >>> assert(pricefunc(basket, timestamps, 1, None) == -12)
     '''
     price_dict: dict[str, tuple[np.ndarray, np.ndarray]]
+    allow_previous: bool
         
 

 [docs]
-    def __init__(self, price_dict: dict[str, tuple[np.ndarray, np.ndarray]]) -> None:
-        self.price_dict = price_dict

+    def __init__(self, price_dict: dict[str, tuple[np.ndarray, np.ndarray]], allow_previous: bool = False) -> None:
+        self.price_dict = price_dict
+        self.allow_previous = allow_previous

 
         
 

@@ -158,9 +212,9 @@ 
Source code for pyqstrat.strategy_components
timestamp = timestamps[i]
         if contract.is_basket():
             for _contract, ratio in contract.components:
-                price += get_contract_price_from_array_dict(self.price_dict, _contract, timestamp) * ratio
+                price += get_contract_price_from_array_dict(self.price_dict, _contract, timestamp, self.allow_previous) * ratio
         else:
-            price = get_contract_price_from_array_dict(self.price_dict, contract, timestamp)
+            price = get_contract_price_from_array_dict(self.price_dict, contract, timestamp, self.allow_previous)
         return price

 

 
@@ -227,32 +281,38 @@ 
Source code for pyqstrat.strategy_components
    >>> timestamp = np.datetime64('2023-01-03 14:35')
     >>> price_func = PriceFuncDict({put_symbol: {timestamp: 4.8}, call_symbol: {timestamp: 3.5}})
     >>> order = MarketOrder(contract=basket, timestamp=timestamp, qty=10, reason_code='TEST')
-    >>> sim = SimpleMarketSimulator(price_func=price_func, slippage_per_trade=0)
+    >>> sim = SimpleMarketSimulator(price_func=price_func, slippage_pct=0)
     >>> out = sim([order], 0, np.array([timestamp]), {}, {}, SimpleNamespace())
     >>> assert(len(out) == 1)
     >>> assert(math.isclose(out[0].price, -1.3))
     >>> assert(out[0].qty == 10)    
     '''
     price_func: PriceFunctionType
-    slippage: float
+    slippage_pct: float
     commission: float
+    price_rounding: int
+    post_trade_func: Callable[[Trade, StrategyContextType], None] | None
         
 

 [docs]
     def __init__(self,
                  price_func: PriceFunctionType,
-                 slippage_per_trade: float = 0.,
-                 commission_per_trade: float = 0) -> None:
+                 slippage_pct: float = 0.,
+                 commission: float = 0,
+                 price_rounding: int = 3,
+                 post_trade_func: Callable[[Trade, StrategyContextType], None] | None = None) -> None:
         '''
         Args:
             price_func: A function that we use to get the price to execute at
-            slippage_per_trade: Slippage in local currency. Meant to simulate the difference
-            between bid/ask mid and execution price 
-            commission_per_trade: Fee paid to broker per trade
+            slippage_pct: Slippage per dollar transacted. 
+                Meant to simulate the difference between bid/ask mid and execution price 
+            commission: Fee paid to broker per trade
         '''
-        self.price_func: PriceFunctionType = price_func
-        self.slippage: float = slippage_per_trade
-        self.commission: float = commission_per_trade

+        self.price_func = price_func
+        self.slippage_pct = slippage_pct
+        self.commission = commission
+        self.price_rounding = price_rounding
+        self.post_trade_func = post_trade_func

 
     
 

@@ -261,13 +321,12 @@ 
Source code for pyqstrat.strategy_components
orders: Sequence[Order],
                  i: int, 
                  timestamps: np.ndarray, 
-                 indicators: dict[ContractGroup, SimpleNamespace],
-                 signals: dict[ContractGroup, SimpleNamespace],
+                 indicators: dict[str, SimpleNamespace],
+                 signals: dict[str, SimpleNamespace],
                  strategy_context: SimpleNamespace) -> list[Trade]:
-        '''TODO: code for limit orders and stop orders'''
+        '''TODO: code for stop orders'''
         trades = []
         timestamp = timestamps[i]
-        # _logger.info(f'got: {orders}')
         for order in orders:
             if not isinstance(order, MarketOrder) and not isinstance(order, LimitOrder): continue
             contract = order.contract
@@ -280,9 +339,10 @@ 
Source code for pyqstrat.strategy_components
if np.isnan(raw_price):
                         break
             if np.isnan(raw_price): continue
-            slippage = self.slippage * order.qty
+            slippage = self.slippage_pct * raw_price
             if order.qty < 0: slippage = -slippage
             price = raw_price + slippage
+            price = round(price, self.price_rounding)
             if isinstance(order, LimitOrder) and np.isfinite(order.limit_price):
                 if ((abs(order.qty > 0) and order.limit_price > price) 
                         or (abs(order.qty < 0) and order.limit_price < price)):
@@ -290,9 +350,10 @@ 
Source code for pyqstrat.strategy_components
commission = self.commission * order.qty
             if order.qty < 0: commission = -commission
             trade = Trade(order.contract, order, timestamp, order.qty, price, self.commission)
-            _logger.info(f'TRADE: {timestamp.astype("M8[m]")} {trade}')
             order.fill()
             trades.append(trade)
+            if self.post_trade_func is not None:
+                self.post_trade_func(trade, strategy_context)
         return trades

 

 
@@ -309,6 +370,7 @@ 
Source code for pyqstrat.strategy_components
        reason_code: Reason for entering the order, used for display
         equity_percent: Percentage of equity used to size order
         long: Whether We want to go long or short
+        allocate_risk: If set, we divide the max risk by number of trades. Otherwise each trade will be alloated max risk 
         limit_increment: If not nan, we add or subtract this number from current market price (if selling or buying respectively)
             and create a limit order. If nan, we create market orders
         price_func: The function we use to get intraday prices
@@ -318,6 +380,7 @@ 
Source code for pyqstrat.strategy_components
price_func: PriceFunctionType
     equity_percent: float = 0.1  # use 10% of equity by default
     long: bool = True
+    allocate_risk: bool = False
     limit_increment: float = math.nan
         
 

@@ -343,7 +406,8 @@ 
Source code for pyqstrat.strategy_components
curr_equity = account.equity(timestamp)
             risk_amount = self.equity_percent * curr_equity
             order_qty = risk_amount / entry_price_est
-            order_qty /= len(contracts)  # divide up qty equally between all contracts
+            if self.allocate_risk:
+                order_qty /= len(contracts)  # divide up qty equally between all contracts
             if not self.long: order_qty *= -1
             order_qty = math.floor(order_qty) if order_qty > 0 else math.ceil(order_qty)
             if math.isclose(order_qty, 0.): return []
@@ -384,8 +448,8 @@ 
Source code for pyqstrat.strategy_components
        long: Whether we want to go long or short
         percent_of_equity: Order qty is calculated so that if the stop price is reached, we lose this amount
         stop_price_ind: Don't enter if estimated entry price is 
-            market price <= stop price + min_price_diff (for long orders) or the opposite for short orders
-        min_price_diff: See stop_price_ind
+            market price <= stop price + min_price_diff_pct * market_price (for long orders) or the opposite for short orders
+        min_price_diff_pct: See stop_price_ind
     '''
     reason_code: str
     vwap_minutes: int
@@ -393,7 +457,7 @@ 
Source code for pyqstrat.strategy_components
long: bool
     percent_of_equity: float
     stop_price_ind: str | None
-    min_price_diff: float
+    min_price_diff_pct: float
     single_entry_per_day: bool
         
 

@@ -405,7 +469,7 @@ 
Source code for pyqstrat.strategy_components
long: bool = True,
                  percent_of_equity: float = 0.1,
                  stop_price_ind: str | None = None,
-                 min_price_diff: float = 0,
+                 min_price_diff_pct: float = 0,
                  single_entry_per_day: bool = False) -> None:
         self.reason_code = reason_code
         self.price_func = price_func
@@ -413,7 +477,7 @@ 
Source code for pyqstrat.strategy_components
self.vwap_minutes = vwap_minutes
         self.percent_of_equity = percent_of_equity
         self.stop_price_ind = stop_price_ind
-        self.min_price_diff = min_price_diff
+        self.min_price_diff_pct = min_price_diff_pct
         self.single_entry_per_day = single_entry_per_day

 
         
@@ -446,8 +510,8 @@ 
Source code for pyqstrat.strategy_components
if self.stop_price_ind:
                 _stop_price_ind = getattr(indicator_values, self.stop_price_ind)
                 stop_price = _stop_price_ind[i]
-                if self.long and (entry_price_est - stop_price) < self.min_price_diff: return []
-                if not self.long and (stop_price - entry_price_est) < self.min_price_diff: return []
+                if self.long and (entry_price_est - stop_price) < self.min_price_diff_pct * entry_price_est: return []
+                if not self.long and (stop_price - entry_price_est) < self.min_price_diff_pct * entry_price_est: return []
             else:
                 stop_price = math.nan
 
@@ -606,11 +670,9 @@ 
Source code for pyqstrat.strategy_components
fill_fraction = (timestamp - order.timestamp) / (order.vwap_end_time - order.timestamp)
                 fill_fraction = min(fill_fraction, 1)
                 fill_qty = np.fix(order.qty * fill_fraction)
-                _logger.info(f'{timestamp} {order.timestamp} {order.vwap_end_time} {fill_fraction} qty: {fill_qty}')
             order.fill(fill_qty)
             order.cancel()
             trade = Trade(order.contract, order, timestamp, fill_qty, vwap)
-            _logger.info(f'Trade: {timestamp.astype("M8[m]")} {trade} {i}')
             trades.append(trade)
         return trades

 

@@ -618,7 +680,7 @@ 
Source code for pyqstrat.strategy_components
ContractFilterType = Callable[
-    [Contract, 
+    [ContractGroup, 
      int, 
      np.ndarray, 
      SimpleNamespace, 
@@ -626,13 +688,13 @@ 
Source code for pyqstrat.strategy_components
Account, 
      Sequence[Order],
      StrategyContextType],
-    list[str] | None]
+    list[str]]
 
 
-

-[docs]
+

+[docs]
 @dataclass
-class FiniteRiskEntryRule:
+class BracketOrderEntryRule:
     '''
     A rule that generates orders with stops
     
@@ -644,45 +706,77 @@ 
Source code for pyqstrat.strategy_components
            Used to calculate order qty so that if we get stopped out, we don't lose 
             more than this amount. Of course if price gaps up or down rather than moving smoothly,
             we may lose more.
-        stop_price_ind: An indicator containing the stop price so we exit the order when this is breached
+        stop_return_func: A function that gives us the distance between entry price and stop price
+        min_stop_return: We will not enter if the stop_return is closer than this percent to the stop.
+            Otherwise, we get very large trade sizes
+        max_position_size: An order should not result in a position that is greater than this percent
+            of the portfolio
         contract_filter: A function that takes similar arguments as a rule (with ContractGroup) replaced by 
             Contract but returns a list of contract names for each positive signal timestamp. For example, 
             for a strategy that trades 5000 stocks, you may want to construct a single signal and apply it 
             to different contracts at different times, rather than create 5000 signals that will call your rule
             5000 times every time the signal is true.
+            
+    >>> timestamps = np.arange(np.datetime64('2023-01-01'), np.datetime64('2023-01-05'))
+    >>> sig_values = np.full(len(timestamps), False) 
+    >>> aapl_prices = np.array([100.1, 100.2, 100.3, 100.4])
+    >>> ibm_prices = np.array([200.1, 200.2, 200.3, 200.4])
+    >>> aapl_stops = np.array([-0.5, -0.3, -0.2, -0.01])
+    >>> ibm_stops=  np.array([-0.5, -0.3, -0.2, -0.15])
+    >>> price_dict = {'AAPL': (timestamps, aapl_prices), 'IBM': (timestamps, ibm_prices)}
+    >>> stop_dict = {'AAPL': (timestamps, aapl_stops), 'IBM': (timestamps, ibm_stops)}
+    >>> price_func = PriceFuncArrayDict(price_dict)
+    >>> fr = BracketOrderEntryRule('TEST_ENTRY', price_func, long=False)
+    >>> default_cg = ContractGroup.get('DEFAULT')
+    >>> default_cg.clear_cache()
+    >>> default_cg.add_contract(Contract.get_or_create('AAPL'))
+    >>> default_cg.add_contract(Contract.get_or_create('IBM'))
+    >>> account = SimpleNamespace()
+    >>> account.equity = lambda x: 1e6
+    >>> orders = fr(default_cg, 1, timestamps, SimpleNamespace(), sig_values, account, [], SimpleNamespace())
+    >>> assert len(orders) == 2 and orders[0].qty == -998 and orders[1].qty == -499
+    >>> stop_return_func = PriceFuncArrayDict(stop_dict)
+    >>> fr = BracketOrderEntryRule('TEST_ENTRY', price_func, long=True, stop_return_func=stop_return_func, min_stop_return=-0.1)
+    >>> orders = fr(default_cg, 2, timestamps, SimpleNamespace(), sig_values, account, [], SimpleNamespace())
+    >>> assert len(orders) == 2 and orders[0].qty == 4985 and orders[1].qty == 2496
+    >>> orders = fr(default_cg, 3, timestamps, SimpleNamespace(), sig_values, account, [], SimpleNamespace())
+    >>> assert len(orders) == 1 and orders[0].qty == 3326
     '''
     reason_code: str
     price_func: PriceFunctionType
     long: bool
     percent_of_equity: float
-    stop_price_ind: str | None
-    min_price_diff: float
+    min_stop_returnt: float
+    max_position_size: float
     single_entry_per_day: bool
     contract_filter: ContractFilterType | None
-        
-

-[docs]
+    stop_return_func: PriceFunctionType | None
+
+

+[docs]
     def __init__(self, 
                  reason_code: str, 
                  price_func: PriceFunctionType,
                  long: bool = True,
                  percent_of_equity: float = 0.1,
-                 stop_price_ind: str | None = None,
-                 min_price_diff: float = 0,
+                 min_stop_return: float = 0,
+                 max_position_size: float = 0,
                  single_entry_per_day: bool = False,
-                 contract_filter: ContractFilterType | None = None) -> None:
+                 contract_filter: ContractFilterType | None = None,
+                 stop_return_func: PriceFunctionType | None = None) -> None:
         self.reason_code = reason_code
         self.price_func = price_func
         self.long = long
         self.percent_of_equity = percent_of_equity
-        self.stop_price_ind = stop_price_ind
-        self.min_price_diff = min_price_diff
+        self.stop_return_func = stop_return_func
+        self.min_stop_return = min_stop_return
+        self.max_position_size = max_position_size
         self.single_entry_per_day = single_entry_per_day
         self.contract_filter = contract_filter        

 
 
-

-[docs]
+

+[docs]
     def __call__(self,
                  contract_group: ContractGroup,
                  i: int,
@@ -693,37 +787,58 @@ 
Source code for pyqstrat.strategy_components
current_orders: Sequence[Order],
                  strategy_context: StrategyContextType) -> list[Order]:
         timestamp = timestamps[i]
-        if self.single_entry_per_day:
-            date = timestamp.astype('M8[D]')
-            trades = account.get_trades_for_date(contract_group.name, date)
-            if len(trades): return []
-
-        contracts = contract_group.get_contracts()
+        date = timestamp.astype('M8[D]')
+
+        contracts: list[Contract] = []
+        if self.contract_filter is not None:
+            names = self.contract_filter(
+                contract_group, i, timestamps, indicator_values, signal_values, account, current_orders, strategy_context)
+            for name in names:
+                _contract = Contract.get(name)
+                if _contract is None: continue
+                contracts.append(_contract)
+        else:
+            contracts = contract_group.get_contracts()
+            
         orders: list[Order] = []
         for contract in contracts:
-            if self.contract_filter is not None:
-                relevant_contracts = self.contract_filter(
-                    contract, i, timestamps, indicator_values, signal_values, account, current_orders, strategy_context)
-                if relevant_contracts is None or contract.symbol not in relevant_contracts: continue
-
+            if self.single_entry_per_day:
+                trades = account.get_trades_for_date(contract_group.name, date)
+                if len(trades): continue
+            
             entry_price_est = self.price_func(contract, timestamps, i, strategy_context)  # type: ignore
-            if math.isnan(entry_price_est): return []
-
-            if self.stop_price_ind:
-                _stop_price_ind = getattr(indicator_values, self.stop_price_ind)
-                stop_price = _stop_price_ind[i]
-            else:
-                stop_price = 0.
-
-            if self.long and (entry_price_est - stop_price) < self.min_price_diff: return []
-            if not self.long and (stop_price - entry_price_est) < self.min_price_diff: return []
+            if math.isnan(entry_price_est): continue
+
+            stop_price = 0.
+            if self.stop_return_func is not None:           
+                stop_return = self.stop_return_func(contract, timestamps, i, strategy_context)  # type: ignore
+                assert_(stop_return < 0, f'stop_return must be negative: {stop_return} {timestamp} {contract.symbol}')
+                if stop_return > self.min_stop_return:
+                    _logger.info(f'entry price estimate: {entry_price_est} too close to stop price: {stop_price}'
+                                 f' min stop return: {self.min_stop_return}')
+                    continue
+                if not self.long: stop_return = -stop_return
+                stop_price = entry_price_est * (1 + stop_return)
+                if ((self.long and entry_price_est <= stop_price) or (not self.long and entry_price_est >= stop_price)):
+                    _logger.info(f'entry price estimate: {entry_price_est} exceeds stop price: {stop_price}')
+                    continue                                 
 
             curr_equity = account.equity(timestamp)
             risk_amount = self.percent_of_equity * curr_equity
-            order_qty = risk_amount / (entry_price_est - stop_price)
-            order_qty /= len(contracts)  # divide up equity equally
-            order_qty = math.floor(order_qty) if order_qty > 0 else math.ceil(order_qty)
-            if math.isclose(order_qty, 0.): return []
+            order_qty = risk_amount / abs(entry_price_est - stop_price)
+            
+            if self.max_position_size > 0:
+                max_qty = abs(self.max_position_size * curr_equity / entry_price_est)
+                orig_qty = order_qty
+                if max_qty < abs(orig_qty):
+                    order_qty = max_qty * np.sign(orig_qty)
+                    _logger.info(f'max postion size exceeded: {contract} timestamp: {timestamp} max_qty: {max_qty}'
+                                 f' orig_qty: {orig_qty} new qty: {order_qty} max_qty: {max_qty} pos size: {self.max_position_size}'
+                                 f' curr_equity: {curr_equity} entry_price_est: {entry_price_est}')
+                
+            order_qty = math.floor(order_qty)
+            if not self.long: order_qty = -order_qty
+            if math.isclose(order_qty, 0.): continue
             order = MarketOrder(contract=contract,  # type: ignore
                                 timestamp=timestamp, 
                                 qty=order_qty,
@@ -746,7 +861,6 @@ 
Source code for pyqstrat.strategy_components
        price_func: the function this rule uses to get market prices
         limit_increment: if not nan, we add or subtract this number from current market price (if selling or buying respectively)
             and create a limit order
-        log_orders: if set, we use the python logger to log each order as it is generated
     '''
     reason_code: str
     price_func: PriceFunctionType
@@ -757,14 +871,11 @@ 
Source code for pyqstrat.strategy_components
def __init__(self, 
                  reason_code: str, 
                  price_func: PriceFunctionType,
-                 limit_increment: float = math.nan,
-                 log_orders: bool = True) -> None:
+                 limit_increment: float = math.nan) -> None:
         self.reason_code = reason_code
         self.price_func = price_func
-        assert_(math.isnan(limit_increment) or limit_increment >= 0, 
-                f'limit_increment: {limit_increment} cannot be negative')
-        self.limit_increment = limit_increment
-        self.log_orders = log_orders

+        assert_(math.isnan(limit_increment) or limit_increment >= 0, f'limit_increment: {limit_increment} cannot be negative')
+        self.limit_increment = limit_increment

 
         
 

@@ -780,7 +891,6 @@ 
Source code for pyqstrat.strategy_components
strategy_context: StrategyContextType) -> list[Order]:
         timestamp = timestamps[i]
         positions = account.positions(contract_group, timestamp)
-        # assert len(positions) == 1, f'expected 1 positions, got: {positions}'
         orders: list[Order] = []
         for (contract, qty) in positions:
             if math.isfinite(self.limit_increment):
@@ -794,7 +904,54 @@ 
Source code for pyqstrat.strategy_components
continue
             order = MarketOrder(contract=contract, timestamp=timestamp, qty=-qty, reason_code=self.reason_code)
             orders.append(order)
-        if self.log_orders: _logger.info(f'ORDER: {timestamp} {order}')
+        return orders

+

+
+    
+
+

+[docs]
+@dataclass
+class StopReturnExitRule:
+    '''
+    A rule that exits any given positions if a stop is hit.
+    You should set entry_price in the strategy context in the market simulator when you enter a position
+    '''
+    reason_code: str
+    price_func: PriceFunctionType
+    stop_return_func: PriceFunctionType
+
+

+[docs]
+    def __call__(self,
+                 contract_group: ContractGroup,
+                 i: int,
+                 timestamps: np.ndarray,
+                 indicator_values: SimpleNamespace,
+                 signal_values: np.ndarray,
+                 account: Account,
+                 current_orders: Sequence[Order],
+                 context: StrategyContextType) -> list[Order]:
+        
+        timestamp = timestamps[i]
+        date = timestamp.astype('M8[D]')
+        entry_prices: dict[str, float] = context.entry_prices[date]
+        assert_(len(entry_prices) > 0, f'no symbols entered for: {date}')
+        positions = account.positions(contract_group, timestamp)
+
+        orders: list[Order] = []
+        for contract, qty in positions:
+            symbol = contract.symbol
+            stop_ret = self.stop_return_func(contract, timestamps, i, context)
+            assert_(stop_ret < 0, f'stop_return must be negative: {stop_ret} {timestamp} {symbol}')
+            entry_price = entry_prices[symbol]
+            if qty < 0: stop_ret = -stop_ret
+            stop_price = entry_price * (1 + stop_ret)
+            curr_price = self.price_func(contract, timestamps, i, context)
+            if math.isnan(curr_price): continue
+            if (qty > 0 and curr_price > stop_price) or (qty <= 0 and curr_price < stop_price): continue
+            order = MarketOrder(contract=contract, timestamp=timestamp, qty=-qty, reason_code=self.reason_code)
+            orders.append(order)
         return orders

 

 
diff --git a/docs/genindex.html b/docs/genindex.html
index ee2facc..6a89136 100644
--- a/docs/genindex.html
+++ b/docs/genindex.html
@@ -70,17 +70,21 @@ 
_

 
         
  • (pyqstrat.strategy_builder.StrategyBuilder method)
 
    • 
-        
  • (pyqstrat.strategy_components.ClosePositionExitRule method)
+        
  • (pyqstrat.strategy_components.BracketOrderEntryRule method)
 
    • 
-        
  • (pyqstrat.strategy_components.FiniteRiskEntryRule method)
+        
  • (pyqstrat.strategy_components.ClosePositionExitRule method)
 
    • 
         
  • (pyqstrat.strategy_components.PercentOfEquityTradingRule method)
 
    • 
         
  • (pyqstrat.strategy_components.PriceFuncArrayDict method)
+
    • 
+        
  • (pyqstrat.strategy_components.PriceFuncArrays method)
 
    • 
         
  • (pyqstrat.strategy_components.PriceFuncDict method)
 
    • 
         
  • (pyqstrat.strategy_components.SimpleMarketSimulator method)
+
    • 
+        
  • (pyqstrat.strategy_components.StopReturnExitRule method)
 
    • 
         
  • (pyqstrat.strategy_components.VectorIndicator method)
 
    • 
@@ -124,17 +128,21 @@ 
    _
    
 
         
  • (pyqstrat.strategy_builder.StrategyBuilder method)
 
    • 
-        
  • (pyqstrat.strategy_components.ClosePositionExitRule method)
+        
  • (pyqstrat.strategy_components.BracketOrderEntryRule method)
 
    • 
-        
  • (pyqstrat.strategy_components.FiniteRiskEntryRule method)
+        
  • (pyqstrat.strategy_components.ClosePositionExitRule method)
 
    • 
         
  • (pyqstrat.strategy_components.PercentOfEquityTradingRule method)
 
    • 
         
  • (pyqstrat.strategy_components.PriceFuncArrayDict method)
+
    • 
+        
  • (pyqstrat.strategy_components.PriceFuncArrays method)
 
    • 
         
  • (pyqstrat.strategy_components.PriceFuncDict method)
 
    • 
         
  • (pyqstrat.strategy_components.SimpleMarketSimulator method)
+
    • 
+        
  • (pyqstrat.strategy_components.StopReturnExitRule method)
 
    • 
         
  • (pyqstrat.strategy_components.VectorIndicator method)
 
    • 
@@ -183,10 +191,10 @@ 
    A
    
         
  • (pyqstrat.strategy_builder.StrategyBuilder method)
 
    • 
       
-  
-  
+  
-  
+  
 
@@ -250,6 +268,8 @@ 
    C
    
       
  • CANCELLED (pyqstrat.pq_types.OrderStatus attribute)
 
    • 
       
  • cdf() (in module pyqstrat.pyqstrat_cpp)
+
    • 
+      
  • clear() (pyqstrat.pq_types.ContractGroup method)
 
    • 
       
  • clear_cache() (pyqstrat.pq_types.Contract static method)
 
@@ -329,7 +349,7 @@ 
    C
    
         
  • (pyqstrat.pq_types.RoundTripTrade attribute)
 
    • 
       
-      
  • contract_filter (pyqstrat.strategy_components.FiniteRiskEntryRule attribute)
+      
  • contract_filter (pyqstrat.strategy_components.BracketOrderEntryRule attribute)
 
    • 
       
  • contract_group (pyqstrat.pq_types.Contract attribute)
 
    • 
@@ -493,8 +513,6 @@ 
    F
    
 
   
   
   
      
@@ -550,6 +570,8 @@ 
      G
      
       
    • get_main_logger() (in module pyqstrat.pq_utils)
 
      • 
       
    • get_next_symbol() (pyqstrat.markets.EminiFuture static method)
+
      • 
+      
    • get_or_create() (pyqstrat.pq_types.Contract static method)
 
      • 
       
    • get_paths() (in module pyqstrat.pq_utils)
 
      • 
@@ -590,6 +612,8 @@ 
      I
      
 
-  
+  
+  
-  
      
   
       
    • LimitOrder (class in pyqstrat.pq_types)
 
      • 
-        		
-  
   
 
 
    • pyqstrat.strategy_components module
        
+
      • BracketOrderEntryRule
+
        • 
 
      • ClosePositionExitRule
 
        • 
-
      • FiniteRiskEntryRule
-
        • 
 
      • PercentOfEquityTradingRule
          
 
        • PercentOfEquityTradingRule.__call__()
          • 
 
        • PercentOfEquityTradingRule.__init__()
          • 
+
        • PercentOfEquityTradingRule.allocate_risk
          • 
 
        • PercentOfEquityTradingRule.equity_percent
          • 
 
        • PercentOfEquityTradingRule.limit_increment
          • 
 
        • PercentOfEquityTradingRule.long
          • 
@@ -466,9 +476,17 @@ 
          pyqstrat
 
        • PriceFuncArrayDict
 
          • 
+
        • PriceFuncArrays
+
          • 
 
        • PriceFuncDict
+
          • 
+
        • StopReturnExitRule
 
          • 
 
        • VWAPCloseRule
            
@@ -494,7 +522,7 @@ 
            pyqstrat
 
          • VWAPEntryRule.__call__()
            • 
 
          • VWAPEntryRule.__init__()
            • 
 
          • VWAPEntryRule.long
            • 
-
          • VWAPEntryRule.min_price_diff
            • 
+
          • VWAPEntryRule.min_price_diff_pct
            • 
 
          • VWAPEntryRule.percent_of_equity
            • 
 
          • VWAPEntryRule.price_func
            • 
 
          • VWAPEntryRule.reason_code
            • 
diff --git a/docs/objects.inv b/docs/objects.inv
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GIT binary patch
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diff --git a/docs/pyqstrat.html b/docs/pyqstrat.html
index a017e88..d676b5c 100644
--- a/docs/pyqstrat.html
+++ b/docs/pyqstrat.html
@@ -223,6 +223,16 @@ 
            Submodules
+
            
+pyqstrat.pq_utils.in_debug()[source]¶
            
+
            
+
            Return type:
            
+
            bool
            
+
            
+
            
+
            
+
 
            
 
            
 pyqstrat.pq_utils.in_ipython()[source]¶
            
@@ -838,6 +848,16 @@ 
            Submodules
+
            
+static get_or_create(symbol, contract_group=None, expiry=None, multiplier=1.0, components=None, properties=None)[source]¶
            
+
            
+
            Return type:
            
+
            Contract
            
+
            
+
            
+
            
+
 
            
 
            
 is_basket()[source]¶
            
@@ -876,6 +896,17 @@ 
            Submodulesadd_contract(contract)[source]¶
 
            
 
+
            
+
            
+clear()[source]¶
            
+
            Remove all contracts
            
+
            
+
            Return type:
            
+
            None
            
+
            
+
            
+
            
+
 
            
 
            
 static clear_cache()[source]¶
            
@@ -938,6 +969,16 @@ 
            Submodules
+
            
+static get_default()[source]¶
            
+
            
+
            Return type:
            
+
            ContractGroup
            
+
            
+
            
+
            
+
 
            
 
            
 name: str¶
            
@@ -2019,11 +2060,11 @@ 
            Submodules
            pyqstrat.strategy module¶
            
 
            
 
            
-class pyqstrat.strategy.Strategy(timestamps, contract_groups, price_function, starting_equity=1000000.0, pnl_calc_time=961, trade_lag=0, run_final_calc=True, strategy_context=None)[source]¶
            
+class pyqstrat.strategy.Strategy(timestamps, contract_groups, price_function, starting_equity=1000000.0, pnl_calc_time=961, trade_lag=0, run_final_calc=True, log_trades=True, log_orders=False, strategy_context=None)[source]¶
 
            Bases: object
            
 
            
 
            
-__init__(timestamps, contract_groups, price_function, starting_equity=1000000.0, pnl_calc_time=961, trade_lag=0, run_final_calc=True, strategy_context=None)[source]¶
            
+__init__(timestamps, contract_groups, price_function, starting_equity=1000000.0, pnl_calc_time=961, trade_lag=0, run_final_calc=True, log_trades=True, log_orders=False, strategy_context=None)[source]¶
 
            
 
            Parameters:
            
 
            
 
            
 
            
@@ -3192,7 +3235,7 @@ 
            Submodules
 
            
-pyqstrat.evaluator.plot_return_metrics(metrics, title='', height=1000, width=0, show_points=True, show=True)[source]¶
            
+pyqstrat.evaluator.plot_return_metrics(metrics, title='', height=1000, width=0, show_points=False, show=True)[source]¶
 
            Plot equity, rolling drawdowns and and a boxplot of annual returns given the output of compute_return_metrics.
            
 
            
 
            Parameters:
            
@@ -3792,6 +3835,16 @@ 
            Submodulesindicators: list[tuple[str, Callable[[ContractGroup, ndarray, SimpleNamespace, SimpleNamespace], ndarray], Optional[Sequence[ContractGroup]], Optional[Sequence[str]]]]¶
 
            
 
+
            
+
            
+log_orders: bool¶
            
+
            
+
+
            
+
            
+log_trades: bool¶
            
+
            
+
 
            
 
            
 market_sims: list[Callable[[Sequence[Order], int, ndarray, dict[str, SimpleNamespace], dict[str, SimpleNamespace], SimpleNamespace], list[Trade]]]¶
            
@@ -3812,6 +3865,26 @@ 
            Submodulesrules: list[tuple[str, Callable[[ContractGroup, int, ndarray, SimpleNamespace, ndarray, Account, Sequence[Order], SimpleNamespace], list[Order]], str, Optional[Sequence[Any]], Optional[str]]]¶
 
            
 
+
            
+
            
+set_log_orders(log_orders)[source]¶
            
+
            
+
            Return type:
            
+
            None
            
+
            
+
            
+
            
+
+
            
+
            
+set_log_trades(log_trades)[source]¶
            
+
            
+
            Return type:
            
+
            None
            
+
            
+
            
+
            
+
 
            
 
            
 set_pnl_calc_time(pnl_calc_time)[source]¶
            
@@ -3908,24 +3981,62 @@ 
            Submodules
 
            pyqstrat.strategy_components module¶
            
 
            
-
            
-class pyqstrat.strategy_components.ClosePositionExitRule(reason_code, price_func, limit_increment=nan, log_orders=True)[source]¶
            
+
            
+class pyqstrat.strategy_components.BracketOrderEntryRule(reason_code, price_func, long=True, percent_of_equity=0.1, min_stop_return=0, max_position_size=0, single_entry_per_day=False, contract_filter=None, stop_return_func=None)[source]¶
            
 
            Bases: object
            
-
            A rule to close out an open position
            
+
            A rule that generates orders with stops
            
 
            
 
            Parameters:
            
 
              
-
            • reason_code (str) – the reason for closing out used for display purposes
              • 
-
            • price_func (Callable[[Contract, ndarray, int, SimpleNamespace], float]) – the function this rule uses to get market prices
              • 
-
            • limit_increment (float) – if not nan, we add or subtract this number from current market price (if selling or buying respectively)
-and create a limit order
              • 
-
            • log_orders (bool) – if set, we use the python logger to log each order as it is generated
              • 
+
            • reason_code (str) – Reason for the orders created used for display
              • 
+
            • price_func (Callable[[Contract, ndarray, int, SimpleNamespace], float]) – A function that returns price given a contract and timestamp
              • 
+
            • long (bool) – whether we want to go long or short
              • 
+
            • percent_of_equity (float) – How much to risk per trade as a percentage of current equity.
+Used to calculate order qty so that if we get stopped out, we don’t lose
+more than this amount. Of course if price gaps up or down rather than moving smoothly,
+we may lose more.
              • 
+
            • stop_return_func (Optional[Callable[[Contract, ndarray, int, SimpleNamespace], float]]) – A function that gives us the distance between entry price and stop price
              • 
+
            • min_stop_return (float) – We will not enter if the stop_return is closer than this percent to the stop.
+Otherwise, we get very large trade sizes
              • 
+
            • max_position_size (float) – An order should not result in a position that is greater than this percent
+of the portfolio
              • 
+
            • contract_filter (Optional[Callable[[ContractGroup, int, ndarray, SimpleNamespace, ndarray, Account, Sequence[Order], SimpleNamespace], list[str]]]) – A function that takes similar arguments as a rule (with ContractGroup) replaced by
+Contract but returns a list of contract names for each positive signal timestamp. For example,
+for a strategy that trades 5000 stocks, you may want to construct a single signal and apply it
+to different contracts at different times, rather than create 5000 signals that will call your rule
+5000 times every time the signal is true.
              • 
 
            
 
            
 
            
+
            >>> timestamps = np.arange(np.datetime64('2023-01-01'), np.datetime64('2023-01-05'))
+>>> sig_values = np.full(len(timestamps), False)
+>>> aapl_prices = np.array([100.1, 100.2, 100.3, 100.4])
+>>> ibm_prices = np.array([200.1, 200.2, 200.3, 200.4])
+>>> aapl_stops = np.array([-0.5, -0.3, -0.2, -0.01])
+>>> ibm_stops=  np.array([-0.5, -0.3, -0.2, -0.15])
+>>> price_dict = {'AAPL': (timestamps, aapl_prices), 'IBM': (timestamps, ibm_prices)}
+>>> stop_dict = {'AAPL': (timestamps, aapl_stops), 'IBM': (timestamps, ibm_stops)}
+>>> price_func = PriceFuncArrayDict(price_dict)
+>>> fr = BracketOrderEntryRule('TEST_ENTRY', price_func, long=False)
+>>> default_cg = ContractGroup.get('DEFAULT')
+>>> default_cg.clear_cache()
+>>> default_cg.add_contract(Contract.get_or_create('AAPL'))
+>>> default_cg.add_contract(Contract.get_or_create('IBM'))
+>>> account = SimpleNamespace()
+>>> account.equity = lambda x: 1e6
+>>> orders = fr(default_cg, 1, timestamps, SimpleNamespace(), sig_values, account, [], SimpleNamespace())
+>>> assert len(orders) == 2 and orders[0].qty == -998 and orders[1].qty == -499
+>>> stop_return_func = PriceFuncArrayDict(stop_dict)
+>>> fr = BracketOrderEntryRule('TEST_ENTRY', price_func, long=True, stop_return_func=stop_return_func, min_stop_return=-0.1)
+>>> orders = fr(default_cg, 2, timestamps, SimpleNamespace(), sig_values, account, [], SimpleNamespace())
+>>> assert len(orders) == 2 and orders[0].qty == 4985 and orders[1].qty == 2496
+>>> orders = fr(default_cg, 3, timestamps, SimpleNamespace(), sig_values, account, [], SimpleNamespace())
+>>> assert len(orders) == 1 and orders[0].qty == 3326
+
            
+
            
 
            
-
            
-__call__(contract_group, i, timestamps, indicator_values, signal_values, account, current_orders, strategy_context)[source]¶
            
+
            
+__call__(contract_group, i, timestamps, indicator_values, signal_values, account, current_orders, strategy_context)[source]¶
            
 
            Call self as a function.
            
 
            
 
            Return type:
            
@@ -3935,54 +4046,75 @@ 
            Submodules
-
            
-__init__(reason_code, price_func, limit_increment=nan, log_orders=True)[source]¶
            
+
            
+__init__(reason_code, price_func, long=True, percent_of_equity=0.1, min_stop_return=0, max_position_size=0, single_entry_per_day=False, contract_filter=None, stop_return_func=None)[source]¶
            
 
            
 
 
            
-
            
-limit_increment: float¶
            
+
            
+contract_filter: Optional[Callable[[ContractGroup, int, ndarray, SimpleNamespace, ndarray, Account, Sequence[Order], SimpleNamespace], list[str]]]¶
            
 
            
 
 
            
-
            
-price_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
+
            
+long: bool¶
            
 
            
 
 
            
-
            
-reason_code: str¶
            
+
            
+max_position_size: float¶
            
+
            
+
+
            
+
            
+min_stop_returnt: float¶
            
+
            
+
+
            
+
            
+percent_of_equity: float¶
            
+
            
+
+
            
+
            
+price_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
+
            
+
+
            
+
            
+reason_code: str¶
            
+
            
+
+
            
+
            
+single_entry_per_day: bool¶
            
+
            
+
+
            
+
            
+stop_return_func: Optional[Callable[[Contract, ndarray, int, SimpleNamespace], float]]¶
            
 
            
 
 
            
 
 
            
-
            
-class pyqstrat.strategy_components.FiniteRiskEntryRule(reason_code, price_func, long=True, percent_of_equity=0.1, stop_price_ind=None, min_price_diff=0, single_entry_per_day=False, contract_filter=None)[source]¶
            
+
            
+class pyqstrat.strategy_components.ClosePositionExitRule(reason_code, price_func, limit_increment=nan)[source]¶
            
 
            Bases: object
            
-
            A rule that generates orders with stops
            
+
            A rule to close out an open position
            
 
            
 
            Parameters:
            
 
              
-
            • reason_code (str) – Reason for the orders created used for display
              • 
-
            • price_func (Callable[[Contract, ndarray, int, SimpleNamespace], float]) – A function that returns price given a contract and timestamp
              • 
-
            • long (bool) – whether we want to go long or short
              • 
-
            • percent_of_equity (float) – How much to risk per trade as a percentage of current equity.
-Used to calculate order qty so that if we get stopped out, we don’t lose
-more than this amount. Of course if price gaps up or down rather than moving smoothly,
-we may lose more.
              • 
-
            • stop_price_ind (Optional[str]) – An indicator containing the stop price so we exit the order when this is breached
              • 
-
            • contract_filter (Optional[Callable[[Contract, int, ndarray, SimpleNamespace, ndarray, Account, Sequence[Order], SimpleNamespace], Optional[list[str]]]]) – A function that takes similar arguments as a rule (with ContractGroup) replaced by
-Contract but returns a list of contract names for each positive signal timestamp. For example,
-for a strategy that trades 5000 stocks, you may want to construct a single signal and apply it
-to different contracts at different times, rather than create 5000 signals that will call your rule
-5000 times every time the signal is true.
              • 
+
            • reason_code (str) – the reason for closing out used for display purposes
              • 
+
            • price_func (Callable[[Contract, ndarray, int, SimpleNamespace], float]) – the function this rule uses to get market prices
              • 
+
            • limit_increment (float) – if not nan, we add or subtract this number from current market price (if selling or buying respectively)
+and create a limit order
              • 
 
            
 
            
 
            
 
            
-
            
-__call__(contract_group, i, timestamps, indicator_values, signal_values, account, current_orders, strategy_context)[source]¶
            
+
            
+__call__(contract_group, i, timestamps, indicator_values, signal_values, account, current_orders, strategy_context)[source]¶
            
 
            Call self as a function.
            
 
            
 
            Return type:
            
@@ -3992,55 +4124,30 @@ 
            Submodules
-
            
-__init__(reason_code, price_func, long=True, percent_of_equity=0.1, stop_price_ind=None, min_price_diff=0, single_entry_per_day=False, contract_filter=None)[source]¶
            
-
            
-
-
            
-
            
-contract_filter: Optional[Callable[[Contract, int, ndarray, SimpleNamespace, ndarray, Account, Sequence[Order], SimpleNamespace], Optional[list[str]]]]¶
            
-
            
-
-
            
-
            
-long: bool¶
            
-
            
-
-
            
-
            
-min_price_diff: float¶
            
-
            
-
-
            
-
            
-percent_of_equity: float¶
            
-
            
-
-
            
-
            
-price_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
+
            
+__init__(reason_code, price_func, limit_increment=nan)[source]¶
            
 
            
 
 
            
-
            
-reason_code: str¶
            
+
            
+limit_increment: float¶
            
 
            
 
 
            
-
            
-single_entry_per_day: bool¶
            
+
            
+price_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
 
            
 
 
            
-
            
-stop_price_ind: Optional[str]¶
            
+
            
+reason_code: str¶
            
 
            
 
 
            
 
 
            
 
            
-class pyqstrat.strategy_components.PercentOfEquityTradingRule(reason_code, price_func, equity_percent=0.1, long=True, limit_increment=nan)[source]¶
            
+class pyqstrat.strategy_components.PercentOfEquityTradingRule(reason_code, price_func, equity_percent=0.1, long=True, allocate_risk=False, limit_increment=nan)[source]¶
 
            Bases: object
            
 
            A rule that trades a percentage of equity.
            
 
            
@@ -4049,6 +4156,7 @@ 
            Submodulesstr) – Reason for entering the order, used for display
            
 
          • equity_percent (float) – Percentage of equity used to size order
            • 
 
          • long (bool) – Whether We want to go long or short
            • 
+
          • allocate_risk (bool) – If set, we divide the max risk by number of trades. Otherwise each trade will be alloated max risk
            • 
 
          • limit_increment (float) – If not nan, we add or subtract this number from current market price (if selling or buying respectively)
 and create a limit order. If nan, we create market orders
            • 
 
          • price_func (Callable[[Contract, ndarray, int, SimpleNamespace], float]) – The function we use to get intraday prices
            • 
@@ -4068,7 +4176,12 @@ 
            Submodules
 
            
-__init__(reason_code, price_func, equity_percent=0.1, long=True, limit_increment=nan)¶
            
+__init__(reason_code, price_func, equity_percent=0.1, long=True, allocate_risk=False, limit_increment=nan)¶
+
            
+
+
            
+
            
+allocate_risk: bool = False¶
            
 
            
 
 
            
@@ -4100,12 +4213,21 @@ 
            Submodules
 
            
-class pyqstrat.strategy_components.PriceFuncArrayDict(price_dict)[source]¶
            
+class pyqstrat.strategy_components.PriceFuncArrayDict(price_dict, allow_previous=False)[source]¶
 
            Bases: object
            
 
            
 
            A function object with a signature of PriceFunctionType and takes a dictionary of
            contract name -> tuple of sorted timestamps and prices
            
 
            
 
            
+
            
+
            Parameters:
            
+
              
+
            • price_dict (dict[str, tuple[ndarray, ndarray]]) – a dict with key=contract nane and value a tuple of timestamp and price arrays
              • 
+
            • allow_previous (bool) – if set and we don’t find an exact match for the timestamp, use the
+previous timestamp. Useful if you have a dict with keys containing dates instead of timestamps
              • 
+
            
+
            
+
            
 
            >>> timestamps = np.arange(np.datetime64('2023-01-01'), np.datetime64('2023-01-04'))
 >>> price_dict = {'AAPL': (timestamps, [8, 9, 10]), 'IBM': (timestamps, [20, 21, 22])}
 >>> pricefunc = PriceFuncArrayDict(price_dict)
@@ -4130,7 +4252,12 @@ 
            Submodules
 
            
-__init__(price_dict)[source]¶
            
+__init__(price_dict, allow_previous=False)[source]¶
+
            
+
+
            
+
            
+allow_previous: bool¶
            
 
            
 
 
            
@@ -4140,6 +4267,40 @@ 
            Submodules
+
            
+class pyqstrat.strategy_components.PriceFuncArrays(symbols, timestamps, prices, allow_previous=False)[source]¶
            
+
            Bases: object
            
+
            A function object with a signature of PriceFunctionType. Takes three ndarrays
+of symbols, timestamps and prices
            
+
            
+
            
+__call__(contract, timestamps, i, context)[source]¶
            
+
            Call self as a function.
            
+
            
+
            Return type:
            
+
            float
            
+
            
+
            
+
            
+
+
            
+
            
+__init__(symbols, timestamps, prices, allow_previous=False)[source]¶
            
+
            
+
+
            
+
            
+allow_previous: bool¶
            
+
            
+
+
            
+
            
+price_dict: dict[str, tuple[ndarray, ndarray]]¶
            
+
            
+
+
            
+
 
            
 
            
 class pyqstrat.strategy_components.PriceFuncDict(price_dict)[source]¶
            
@@ -4184,7 +4345,7 @@ 
            Submodules
 
            
-class pyqstrat.strategy_components.SimpleMarketSimulator(price_func, slippage_per_trade=0.0, commission_per_trade=0)[source]¶
            
+class pyqstrat.strategy_components.SimpleMarketSimulator(price_func, slippage_pct=0.0, commission=0, price_rounding=3, post_trade_func=None)[source]¶
 
            Bases: object
            
 
            A function object with a signature of MarketSimulatorType.
 It can take into account slippage and commission
@@ -4198,7 +4359,7 @@ 
            Submodules
 
            
 __call__(orders, i, timestamps, indicators, signals, strategy_context)[source]¶
            
-
            TODO: code for limit orders and stop orders
            
+
            TODO: code for stop orders
            
 
            
 
            Return type:
            
 
            list[Trade]
            
@@ -4216,14 +4377,14 @@ 
            Submodules
 
            
-__init__(price_func, slippage_per_trade=0.0, commission_per_trade=0)[source]¶
            
+__init__(price_func, slippage_pct=0.0, commission=0, price_rounding=3, post_trade_func=None)[source]¶
 
            
 
            Parameters:
            
 
              
 
            • price_func (Callable[[Contract, ndarray, int, SimpleNamespace], float]) – A function that we use to get the price to execute at
              • 
-
            • slippage_per_trade (float) – Slippage in local currency. Meant to simulate the difference
              • 
-
            • price (between bid/ask mid and execution) – 
              • 
-
            • commission_per_trade (float) – Fee paid to broker per trade
              • 
+
            • slippage_pct (float) – Slippage per dollar transacted.
+Meant to simulate the difference between bid/ask mid and execution price
              • 
+
            • commission (float) – Fee paid to broker per trade
              • 
 
            
 
            
 
            
@@ -4234,14 +4395,63 @@ 
            Submodulescommission: float¶
 
            
 
+
            
+
            
+post_trade_func: Optional[Callable[[Trade, SimpleNamespace], None]]¶
            
+
            
+
 
            
 
            
 price_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
 
            
 
 
            
-
            
-slippage: float¶
            
+
            
+price_rounding: int¶
            
+
            
+
+
            
+
            
+slippage_pct: float¶
            
+
            
+
+
            
+
+
            
+
            
+class pyqstrat.strategy_components.StopReturnExitRule(reason_code, price_func, stop_return_func)[source]¶
            
+
            Bases: object
            
+
            A rule that exits any given positions if a stop is hit.
+You should set entry_price in the strategy context in the market simulator when you enter a position
            
+
            
+
            
+__call__(contract_group, i, timestamps, indicator_values, signal_values, account, current_orders, context)[source]¶
            
+
            Call self as a function.
            
+
            
+
            Return type:
            
+
            list[Order]
            
+
            
+
            
+
            
+
+
            
+
            
+__init__(reason_code, price_func, stop_return_func)¶
            
+
            
+
+
            
+
            
+price_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
+
            
+
+
            
+
            
+reason_code: str¶
            
+
            
+
+
            
+
            
+stop_return_func: Callable[[Contract, ndarray, int, SimpleNamespace], float]¶
            
 
            
 
 
            
@@ -4285,7 +4495,7 @@ 
            Submodules
 
            
-class pyqstrat.strategy_components.VWAPEntryRule(reason_code, vwap_minutes, price_func, long=True, percent_of_equity=0.1, stop_price_ind=None, min_price_diff=0, single_entry_per_day=False)[source]¶
            
+class pyqstrat.strategy_components.VWAPEntryRule(reason_code, vwap_minutes, price_func, long=True, percent_of_equity=0.1, stop_price_ind=None, min_price_diff_pct=0, single_entry_per_day=False)[source]¶
 
            Bases: object
            
 
            A rule that generates VWAP orders
            
 
            
@@ -4298,8 +4508,8 @@ 
            Submodulesbool) – Whether we want to go long or short
            
 
          • percent_of_equity (float) – Order qty is calculated so that if the stop price is reached, we lose this amount
            • 
 
          • stop_price_ind (Optional[str]) – Don’t enter if estimated entry price is
-market price <= stop price + min_price_diff (for long orders) or the opposite for short orders
            • 
-
          • min_price_diff (float) – See stop_price_ind
            • 
+market price <= stop price + min_price_diff_pct * market_price (for long orders) or the opposite for short orders
            
+
          • min_price_diff_pct (float) – See stop_price_ind
            • 
 
          
 
 
@@ -4316,7 +4526,7 @@ 
          Submodules
 
          
-__init__(reason_code, vwap_minutes, price_func, long=True, percent_of_equity=0.1, stop_price_ind=None, min_price_diff=0, single_entry_per_day=False)[source]¶
          
+__init__(reason_code, vwap_minutes, price_func, long=True, percent_of_equity=0.1, stop_price_ind=None, min_price_diff_pct=0, single_entry_per_day=False)[source]¶
 
          
 
 
          
@@ -4325,8 +4535,8 @@ 
          Submodules
-
          
-min_price_diff: float¶
          
+
          
+min_price_diff_pct: float¶
          
 
          
 
 
          
@@ -4475,7 +4685,7 @@ 
          Submodules
 
          
-pyqstrat.strategy_components.get_contract_price_from_array_dict(price_dict, contract, timestamp)[source]¶
          
+pyqstrat.strategy_components.get_contract_price_from_array_dict(price_dict, contract, timestamp, allow_previous)[source]¶
 
          
 
          Return type:
          
 
          float
          
diff --git a/docs/searchindex.js b/docs/searchindex.js
index 7b4dd9d..f7e1809 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["index", "modules", "pyqstrat"], "filenames": ["index.rst", "modules.rst", "pyqstrat.rst"], "titles": ["API documentation for pyqstrat", "pyqstrat", "pyqstrat package"], "terms": {"pleas": 0, "read": [0, 2], "readm": 0, "rst": 0, "main": [0, 2], "directori": [0, 2], "get": [0, 1, 2], "start": [0, 2], "packag": [0, 1], "index": [0, 2], "modul": [0, 1], "search": 0, "page": 0, "submodul": 1, "pq_util": 1, "pqexcept": [1, 2], "path": [1, 2], "creat": [1, 2], "assert_": [1, 2], "bootstrap_ci": [1, 2], "day_of_week_num": [1, 2], "day_symbol": [1, 2], "find_in_subdir": [1, 2], "get_child_logg": [1, 2], "get_config": [1, 2], "get_empty_np_valu": [1, 2], "get_main_logg": [1, 2], "get_path": [1, 2], "get_temp_dir": [1, 2], "has_displai": [1, 2], "in_ipython": [1, 2], "infer_compress": [1, 2], "infer_frequ": [1, 2], "is_new": [1, 2], "linear_interpol": [1, 2], "millis_since_epoch": [1, 2], "monotonically_increas": [1, 2], "nan_to_zero": [1, 2], "np_bucket": [1, 2], 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\ No newline at end of file
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"zero_to_nan() (in module pyqstrat.pq_utils)": [[2, "pyqstrat.pq_utils.zero_to_nan"]]}})
\ No newline at end of file