BT combined strategies example for pmorissette/bt#415

README.md

@@ -1 +1,36 @@
-# bt-composite-strategies
+# BT composite strategies
+
+This repository shows the effect of the issue https://github.com/pmorissette/bt/issues/415. 
+For more details see the `test_interpreter.py` unit test or use the Jupyter notebook `example.ipynb`
+
+
+# Simple buy and hold strategy:
+
+We create a simple buy and hold strategy with the QQQ. 
+* Everything is fine. 
+* We have transactions. 
+* The backtest works fine. 
+* The portfolio gets rebalanced every day. 
+
+# First level composite strategy
+We create a combined strategy containing two buy and hold strategies of QQQ and SPY
+* The strategy does not have a return, but some other statistics. 
+* It has sold everything on the 4th day and rebalancing is not propagated to the children. 
+
+# Second level composite strategy
+We create a combined strategy containing to combined strategies and one asset. 
+* The execution fails with 
+```shell
+ZeroDivisionError: Could not update df876984-3be8-40c9-8847-e3b3c6af3cdc on 2023-05-17 00:00:00. Last value was 0.0 and net flows were 0. Currentvalue is 1000000.0. Therefore, we are dividing by zero to obtain the return for the period.
+```
+
+# How to get this working?
+
+```shell
+git clone https://github.com/Pirat83/bt-composite-strategies.git
+cd bt-composite-strategies/
+conda create --name bt-composite-strategies
+conda env update
+```
+
+If you can contribute to the solution I would appreciate it very much.  

environment.yml

@@ -0,0 +1,14 @@
+name: bt-composite-strategies
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python>=3.10
+  - jupyter
+  - pandas<2.0.0
+  - pip
+  - pytest
+
+  - pip:
+      - git+https://github.com/pmorissette/bt.git
+      - pytest-resource-path

src/interpreter.py

@@ -0,0 +1,119 @@
+from datetime import date
+from typing import Union
+
+import bt
+import pandas as pd
+from pandas import DataFrame, Series
+
+
+def flatten(i, result=None) -> list[bt.Backtest]:
+    if result is None:
+        result = []
+    if isinstance(i, bt.Backtest):
+        result.append(i)
+    elif isinstance(i, bt.backtest.Result):
+        for b in i.backtest_list:
+            flatten(b, result)
+    elif isinstance(i, list):
+        for b in i:
+            flatten(b, result)
+    elif isinstance(i, tuple):
+        for b in i:
+            flatten(b, result)
+    else:
+        raise NotImplementedError()
+
+    return result
+
+
+class BTInterpreter:
+    root: dict
+
+    start: date
+    end: date
+    rebalance: bt.algos.RunPeriod
+
+    def __init__(self, root: dict, start: date, end: date):
+        self.root = root
+
+        self.start = start
+        self.end = end
+
+    def traverse(self, node: dict = None) -> bt.backtest.Result:
+        if node is None:
+            node = self.root
+        node_type: str = node.get('node-type')
+        match node_type:
+            case 'group':
+                return self.parse_group(node)
+            case 'group':
+                return self.parse_group(node)
+            case 'asset':
+                return self.parse_asset(node)
+            case _:
+                raise NotImplementedError()
+
+    def parse_group(self, node: dict) -> bt.backtest.Result:
+        identifier: str = node.get('id')
+
+        children: list = node.get('children')
+        children: list[bt.backtest.Result] = [self.traverse(c) for c in children]
+
+        prices: DataFrame = pd.DataFrame()
+        for p in [c.prices for c in children]:
+            prices = bt.merge(p)
+
+        backtests: list[bt.Backtest] = flatten([c.backtest_list for c in children])
+        #for p in [b.data for b in backtests]:
+        #    prices = bt.merge(prices, p)
+
+        strategies: list[bt.Strategy] = [b.strategy for b in backtests]
+        #for p in [s.universe for s in strategies]:
+        #    prices = bt.merge(prices, p)
+
+        strategy: bt.Strategy = self.build_strategy(identifier, strategies, debug=True)
+        backtest: bt.Backtest = self.build_backtest(strategy, prices)
+        result: bt.backtest.Result = bt.run(backtest)
+        return result
+
+    def parse_asset(self, node: dict) -> bt.backtest.Result:
+        identifier: str = node.get('id')
+
+        ticker: str = node.get('ticker')
+        prices: DataFrame = bt.data.get(ticker, clean_tickers=False, start=self.start, end=self.end)
+        strategy: bt.Strategy = self.build_strategy(identifier, [bt.Security(ticker)])
+        backtest: bt.Backtest = self.build_backtest(strategy, prices)
+        result: bt.backtest.Result = bt.run(backtest)
+        return result
+
+    def build_strategy(self, name: str,
+                       children: Union[list[bt.algos.SecurityBase], list[bt.core.StrategyBase]],
+                       selection: bt.algos.Algo = bt.algos.SelectAll(),
+                       weight: bt.algos.Algo = bt.algos.WeighInvVol(),
+                       debug: bool = False
+                       ) -> bt.Strategy:
+        algos: [list[bt.algos.Algo]] = [
+            bt.algos.RunAfterDate(self.start),
+            bt.algos.RunDaily(),
+            selection,
+            weight
+        ]
+        if debug:
+            algos.append(bt.algos.PrintInfo('\n{now}: {name} -> Value:{_value:0.0f}, Price:{_price:0.4f}'))
+            algos.append(bt.algos.PrintTempData('Weights: \n{weights}'))
+
+        algos.append(bt.algos.Rebalance())
+        result: bt.Strategy = bt.Strategy(name, algos, children)
+        return result
+
+    @staticmethod
+    def build_backtest(strategy: bt.Strategy, prices: Union[Series, DataFrame]) -> bt.Backtest:
+        return bt.Backtest(strategy, prices, integer_positions=False)
+
+
+def main():
+    print("Hello World!")
+
+
+if __name__ == "__main__":
+    main()

tests/test_interpreter.py

@@ -0,0 +1,99 @@
+import pprint
+from datetime import date, timedelta
+
+import bt.algos
+
+from interpreter import BTInterpreter
+
+
+def print_backtest_results(result: bt.backtest.Result):
+    result.display()
+    for k, v in result.items():
+        pprint.pp(result.get_transactions(k))
+        pprint.pp(result.get_weights(k))
+        pprint.pp(result.get_security_weights(k))
+
+
+def test_traverse_asset():
+    node: dict = {
+        'id': 'df876984-3be8-40c9-8847-e3b3c6af3cdc',
+        'node-type': 'asset',
+        'ticker': 'QQQ'
+    }
+
+    subject = BTInterpreter(node, date.today() - timedelta(weeks=4), date.today())
+    actual: bt.backtest.Result = subject.traverse()
+    print_backtest_results(actual)
+
+
+def test_traverse_first_level_asset():
+    node: dict = {
+        'id': '5fc986bf-d7c8-4582-bc27-f1ede76bdc29',
+        'node-type': 'group',
+        'children': [
+            {
+                'id': 'df876984-3be8-40c9-8847-e3b3c6af3cdc',
+                'node-type': 'asset',
+                'ticker': 'QQQ'
+            },
+            {
+                'id': '742dc790-d0f7-472d-bd3e-405e411c0b2c',
+                'node-type': 'asset',
+                'ticker': 'SPY'
+            }
+        ]
+    }
+
+    subject = BTInterpreter(node, date.today() - timedelta(weeks=4), date.today())
+    actual: bt.backtest.Result = subject.traverse()
+    print_backtest_results(actual)
+
+
+def test_traverse_second_level_asset():
+    node: dict = {
+        'id': 'c20d0968-2dfa-4ff7-8dfc-4c3d0df36dd4',
+        'node-type': 'group',
+        'children': [
+            {
+                'id': '5fc986bf-d7c8-4582-bc27-f1ede76bdc29 ',
+                'node-type': 'group',
+                'children': [
+                    {
+                        'id': 'df876984-3be8-40c9-8847-e3b3c6af3cdc',
+                        'node-type': 'asset',
+                        'ticker': 'QQQ'
+                    },
+                    {
+                        'id': '742dc790-d0f7-472d-bd3e-405e411c0b2c ',
+                        'node-type': 'asset',
+                        'ticker': 'SPY'
+                    }
+                ]
+            },
+            {
+                'id': 'e5286ea7-9591-4b43-896e-cf34fb63a0e0',
+                'node-type': 'group',
+                'children': [
+                    {
+                        'id': '9e4f255b-343a-43ee-a433-f2366f8e9e62',
+                        'node-type': 'asset',
+                        'ticker': 'IYY'
+                    },
+                    {
+                        'id': '57033cdf-c185-4091-9d3e-3fc1e17913be  ',
+                        'node-type': 'asset',
+                        'ticker': 'IWM'
+                    }
+                ]
+            },
+            {
+                'id': '07306351-709d-41d8-b8dd-d8f6e6ae2900  ',
+                'node-type': 'asset',
+                'ticker': 'IVV'
+            }
+        ]
+    }
+
+    subject = BTInterpreter(node, date.today() - timedelta(weeks=4), date.today())
+    actual: bt.backtest.Result = subject.traverse()
+    print_backtest_results(actual)