Added portfolio tests

asset_backtester/test/backtester/test_backtester.py

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+import numpy as np
+
+from asset_backtester import Backtest, Portfolio, Asset
+
+# We use Portfolio Visualizer (https://www.portfoliovisualizer.com/backtest-portfolio)
+# to find the actual return for the test porfolios.
+
+
+def test_ivy_portfolio(sample_datahandler):
+    bt = run_backtest(sample_datahandler, ivy_portfolio())
+
+    balance = bt.balance[1:]
+    tolerance = 0.0001
+    assert np.allclose(balance['capital'], balance['cash'] + balance['total value'], rtol=tolerance)
+    assert np.allclose(balance['capital'], bt.initial_capital * balance['accumulated return'], rtol=tolerance)
+
+    actual_return = 1.2041
+    return_tolerance = 0.01
+    assert np.isclose(balance['accumulated return'].iloc[-1], actual_return, rtol=return_tolerance)
+
+
+def test_ivy_monthly_rebalance(sample_datahandler):
+    bt = run_backtest(sample_datahandler, ivy_portfolio(), periods=1)
+
+    balance = bt.balance[1:]
+    tolerance = 0.0001
+    assert np.allclose(balance['capital'], balance['cash'] + balance['total value'], rtol=tolerance)
+    assert np.allclose(balance['capital'], bt.initial_capital * balance['accumulated return'], rtol=tolerance)
+
+    actual_return = 1.2043
+    return_tolerance = 0.01
+    assert np.isclose(balance['accumulated return'].iloc[-1], actual_return, rtol=return_tolerance)
+
+
+def test_all_weather_portfolio(sample_datahandler):
+    bt = run_backtest(sample_datahandler, all_weather_portfolio())
+
+    balance = bt.balance[1:]
+    tolerance = 0.0001
+    assert np.allclose(balance['capital'], balance['cash'] + balance['total value'], rtol=tolerance)
+    assert np.allclose(balance['capital'], bt.initial_capital * balance['accumulated return'], rtol=tolerance)
+
+    actual_return = 1.1874
+    return_tolerance = 0.01
+    assert np.isclose(balance['accumulated return'].iloc[-1], actual_return, rtol=return_tolerance)
+
+
+def test_all_weather_monthly_rebalance(sample_datahandler):
+    bt = run_backtest(sample_datahandler, all_weather_portfolio(), periods=1)
+
+    balance = bt.balance[1:]
+    tolerance = 0.0001
+    assert np.allclose(balance['capital'], balance['cash'] + balance['total value'], rtol=tolerance)
+    assert np.allclose(balance['capital'], bt.initial_capital * balance['accumulated return'], rtol=tolerance)
+
+    actual_return = 1.1828
+    return_tolerance = 0.01
+    assert np.isclose(balance['accumulated return'].iloc[-1], actual_return, rtol=return_tolerance)
+
+
+def test_constant_price(constant_price_datahandler):
+    bt = run_backtest(constant_price_datahandler, ivy_portfolio())
+
+    balance = bt.balance[1:]
+    tolerance = 0.0001
+    assert np.allclose(balance['% change'], 0.0, rtol=tolerance)
+    assert np.allclose(balance['capital'], bt.initial_capital, rtol=tolerance)
+    assert np.allclose(balance['total value'], bt.initial_capital, rtol=tolerance)
+    assert np.allclose(balance['accumulated return'], 1.0, rtol=tolerance)
+
+
+def test_zero_initial_capital(sample_datahandler):
+    bt = run_backtest(sample_datahandler, ivy_portfolio(), initial_capital=0)
+
+    balance = bt.balance[1:]
+    tolerance = 0.0001
+    assert np.allclose(balance['capital'], balance['cash'] + balance['total value'], rtol=tolerance)
+    assert np.allclose(balance['cash'], 0.0, rtol=tolerance)
+    assert np.allclose(balance['total value'], 0.0, rtol=tolerance)
+
+
+# Helpers
+def run_backtest(data, portfolio, initial_capital=1_000_000, periods=None):
+    bt = Backtest(data.schema, initial_capital=initial_capital)
+    bt.portfolio = portfolio
+    bt.data = data
+    bt.run(periods=periods)
+
+    return bt
+
+
+def ivy_portfolio():
+    portfolio = Portfolio()
+    assets = [Asset('VTI', 0.2), Asset('VEU', 0.2), Asset('BND', 0.2), Asset('VNQ', 0.2), Asset('DBC', 0.2)]
+
+    return portfolio.add_assets(assets)
+
+
+def all_weather_portfolio():
+    portfolio = Portfolio()
+    assets = [Asset('VTI', 0.3), Asset('TLT', 0.4), Asset('IEF', 0.15), Asset('GLD', 0.075), Asset('DBC', 0.075)]
+
+    return portfolio.add_assets(assets)

asset_backtester/test/conftest.py

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+import os
+
+import pytest
+
+from asset_backtester.datahandler import HistoricalAssetData
+
+TEST_DIR = os.path.abspath(os.path.dirname(__file__))
+
+# 2019 data for TLT, GLD, IEF, VTI, VEU, BND, VNQ and DBC
+SAMPLE_DATA = os.path.join(TEST_DIR, 'test_data', 'sample_data.csv')
+
+
+@pytest.fixture(scope='module')
+def sample_datahandler():
+    data = HistoricalAssetData(SAMPLE_DATA)
+    return data
+
+
+@pytest.fixture(scope='module')
+def constant_price_datahandler():
+    data = HistoricalAssetData(SAMPLE_DATA)
+    data['adjClose'] = data['close'] = 10.0
+    return data