From d975078568a7ebe57aa17c8bfc2387f6b1e1aa7e Mon Sep 17 00:00:00 2001 From: Blair Azzopardi Date: Wed, 8 Feb 2023 00:39:03 +0000 Subject: [PATCH] Simplify dependencies, add github workflows, black/isort code. --- .github/workflows/branch.yml | 57 ++ .readthedocs.yaml | 6 + .vscode/launch.json | 19 +- README.md | 6 +- docs/conf.py | 19 +- notebooks/Portfolio_Optimization.ipynb | 23 +- notebooks/Readme_Example.ipynb | 9 +- poetry.lock | 647 ++++++++++------------ pyproject.toml | 16 +- tests/test_portopt.py | 10 +- tests/test_strategy_runner.py | 3 +- tests/test_utilities.py | 21 +- yabte/backtest/__init__.py | 2 +- yabte/backtest/asset.py | 1 - yabte/backtest/trade.py | 1 + yabte/portopt/hierarchical_risk_parity.py | 9 +- yabte/portopt/inverse_volatility.py | 7 +- yabte/portopt/minimum_variance.py | 4 +- yabte/utilities/lagrangian.py | 2 +- yabte/utilities/pandas_extension.py | 8 +- yabte/utilities/strategy_helpers.py | 4 +- 21 files changed, 457 insertions(+), 417 deletions(-) create mode 100644 .github/workflows/branch.yml diff --git a/.github/workflows/branch.yml b/.github/workflows/branch.yml new file mode 100644 index 0000000..2f42653 --- /dev/null +++ b/.github/workflows/branch.yml @@ -0,0 +1,57 @@ +name: Push +on: [push] + +jobs: + test: + strategy: + fail-fast: false + matrix: + python-version: ['3.10'] + poetry-version: ['1.3.1'] + os: [ubuntu-latest] + runs-on: ${{ matrix.os }} + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + - name: Run image + uses: abatilo/actions-poetry@v2.1.6 + with: + poetry-version: ${{ matrix.poetry-version }} + - name: Install dependencies + run: poetry install + - name: Run tests + run: poetry run python -m unittest +# run: poetry run pytest --cov=./ --cov-report=xml +# - name: Upload coverage to Codecov +# uses: codecov/codecov-action@v2 + code-quality: + strategy: + fail-fast: false + matrix: + python-version: ['3.10'] + poetry-version: ['1.3.1'] + os: [ubuntu-latest] + runs-on: ${{ matrix.os }} + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + - name: Run image + uses: abatilo/actions-poetry@v2.1.6 + with: + poetry-version: ${{ matrix.poetry-version }} + - name: Install dependencies + run: poetry install --with dev + - name: Run black + run: poetry run black . --check + - name: Run isort + run: poetry run isort . --check-only --profile black +# - name: Run flake8 +# run: poetry run flake8 . +# - name: Run bandit +# run: poetry run bandit . +# - name: Run saftey +# run: poetry run safety check diff --git a/.readthedocs.yaml b/.readthedocs.yaml index e70371f..0281b8d 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -10,3 +10,9 @@ build: os: ubuntu-22.04 tools: python: "3.10" + + jobs: + post_install: + - pip install poetry==1.3.1 + - poetry config virtualenvs.create false + - poetry install --with doc diff --git a/.vscode/launch.json b/.vscode/launch.json index 00123cb..ddadd1c 100644 --- a/.vscode/launch.json +++ b/.vscode/launch.json @@ -5,22 +5,23 @@ "version": "0.2.0", "configurations": [ { - "name": "Python: Current File", + "name": "Python: Unittest", "type": "python", "request": "launch", - "program": "${file}", - "console": "integratedTerminal", - "justMyCode": false, - "env": {"PYTHONPATH": "."} + "module": "unittest", + "justMyCode": true }, { - "name": "Test Strat Runner", + "name": "Python: Current File", "type": "python", "request": "launch", - "program": "${workspaceFolder}/tests/test_strategy_runner.py", + "program": "${file}", "console": "integratedTerminal", "justMyCode": false, - "env": {"PYTHONPATH": "."} - } + "env": { + "PYTHONPATH": "." + } + }, + ] } \ No newline at end of file diff --git a/README.md b/README.md index 6e3660a..b3412f5 100644 --- a/README.md +++ b/README.md @@ -10,11 +10,7 @@ There are some basic tests but use at your own peril. It's not production level ## Core dependencies -The core module uses pandas. - -## Other dependencies - -The portfolio optimisation module uses scipy. +The core module uses pandas and scipy. ## Installation diff --git a/docs/conf.py b/docs/conf.py index 0bf9942..1207bfa 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -3,8 +3,8 @@ # For the full list of built-in configuration values, see the documentation: # https://www.sphinx-doc.org/en/master/usage/configuration.html -import sys import os +import sys # ensure project path avaliable to sphinx sys.path.insert(0, os.path.abspath("..")) @@ -13,22 +13,21 @@ # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information -project = 'yabte' -copyright = '2023, Blair Azzopardi' -author = 'Blair Azzopardi' +project = "yabte" +copyright = "2023, Blair Azzopardi" +author = "Blair Azzopardi" # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration -extensions = ['sphinx.ext.autodoc', 'sphinx.ext.mathjax', 'sphinx.ext.viewcode'] - -templates_path = ['_templates'] -exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] +extensions = ["sphinx.ext.autodoc", "sphinx.ext.mathjax", "sphinx.ext.viewcode"] +templates_path = ["_templates"] +exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"] # -- Options for HTML output ------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output -html_theme = 'sphinx_rtd_theme' -html_static_path = ['_static'] +html_theme = "sphinx_rtd_theme" +html_static_path = ["_static"] diff --git a/notebooks/Portfolio_Optimization.ipynb b/notebooks/Portfolio_Optimization.ipynb index f64b6a8..8b4000c 100644 --- a/notebooks/Portfolio_Optimization.ipynb +++ b/notebooks/Portfolio_Optimization.ipynb @@ -15,7 +15,13 @@ "import numpy.linalg as la\n", "import matplotlib.pyplot as plt\n", "\n", - "from yabte.backtest import Strategy, StrategyRunner, PositionalBasketOrder, OrderSizeType, Book\n", + "from yabte.backtest import (\n", + " Strategy,\n", + " StrategyRunner,\n", + " PositionalBasketOrder,\n", + " OrderSizeType,\n", + " Book,\n", + ")\n", "import yabte.utilities.pandas_extension\n", "from yabte.portopt.hierarchical_risk_parity import hrp\n", "from yabte.portopt.minimum_variance import minimum_variance\n", @@ -53,6 +59,7 @@ "source": [ "# run strategy for each portfolio optimization scheme\n", "\n", + "\n", "class PortfolioOptimizationStrat(Strategy):\n", " def init(self):\n", " data = self.data\n", @@ -84,11 +91,11 @@ " p[\"weights\"] = None\n", " if cd:\n", " closes = self.data.loc[:, (slice(None), \"Close\")].droplevel(axis=1, level=1)\n", - " returns = closes.price.log_returns\n", + " returns = closes.prc.log_returns\n", " Sigma = returns.cov()\n", " R = returns.corr()\n", " sigma = returns.std()\n", - " mu = closes.price.capm_returns()\n", + " mu = closes.prc.capm_returns()\n", "\n", " match p.weight_scheme:\n", " case \"HRP\":\n", @@ -178,13 +185,13 @@ " + df_combined.loc[:, (slice(None), \"Close\")]\n", " .mean(axis=1)\n", " .to_frame()\n", - " .price.log_returns.loc[first_date:, :]\n", + " .prc.log_returns.loc[first_date:, :]\n", " .iloc[1:, :]\n", " ).cumprod(),\n", " ]\n", ")\n", "market.columns = [\"MARKET\"]\n", - "pd.concat([df.loc[first_date:, :], market], axis=1).plot()\n" + "pd.concat([df.loc[first_date:, :], market], axis=1).plot()" ] }, { @@ -205,9 +212,11 @@ ], "source": [ "# plot the weightings for each scheme\n", - "fig, axs = plt.subplots(3, 1, figsize=(1*6, 3*4), sharex=True)\n", + "fig, axs = plt.subplots(3, 1, figsize=(1 * 6, 3 * 4), sharex=True)\n", "for ix, scheme in enumerate(schemes):\n", - " srs[ix].trade_history.pivot_table(index=\"ts\", values=\"quantity\", columns=\"asset_name\").cumsum().plot(ax=axs[ix], title=scheme)" + " srs[ix].trade_history.pivot_table(\n", + " index=\"ts\", values=\"quantity\", columns=\"asset_name\"\n", + " ).cumsum().plot(ax=axs[ix], title=scheme)" ] }, { diff --git a/notebooks/Readme_Example.ipynb b/notebooks/Readme_Example.ipynb index 68daa5e..e623e77 100644 --- a/notebooks/Readme_Example.ipynb +++ b/notebooks/Readme_Example.ipynb @@ -27,6 +27,7 @@ "\n", "data_dir = Path(inspect.getfile(Strategy)).parents[2] / \"tests/data/nasdaq\"\n", "\n", + "\n", "class SMAXO(Strategy):\n", " def init(self):\n", " # enhance data with simple moving averages\n", @@ -97,8 +98,12 @@ "for symbol, scol, lcol in [(\"GOOG\", \"red\", \"green\"), (\"MSFT\", \"blue\", \"yellow\")]:\n", " long_ix = th.query(f\"asset_name == '{symbol}' and quantity > 0\").ts\n", " short_ix = th.query(f\"asset_name == '{symbol}' and quantity < 0\").ts\n", - " bvh.loc[long_ix].rename(columns={\"PrimaryBook\": f\"{symbol} Short\"}).plot(color=scol, marker=\"v\", markersize=5, linestyle=\"None\", ax=ax)\n", - " bvh.loc[short_ix].rename(columns={\"PrimaryBook\": f\"{symbol} Long\"}).plot(color=lcol, marker=\"^\", markersize=5, linestyle=\"None\", ax=ax)\n" + " bvh.loc[long_ix].rename(columns={\"PrimaryBook\": f\"{symbol} Short\"}).plot(\n", + " color=scol, marker=\"v\", markersize=5, linestyle=\"None\", ax=ax\n", + " )\n", + " bvh.loc[short_ix].rename(columns={\"PrimaryBook\": f\"{symbol} Long\"}).plot(\n", + " color=lcol, marker=\"^\", markersize=5, linestyle=\"None\", ax=ax\n", + " )" ] }, { diff --git a/poetry.lock b/poetry.lock index 55f70cd..91276ce 100644 --- a/poetry.lock +++ b/poetry.lock @@ -71,32 +71,48 @@ files = [ [[package]] name = "black" -version = "22.12.0" +version = "23.1.0" description = "The uncompromising code formatter." category = "dev" optional = false python-versions = ">=3.7" files = [ - {file = "black-22.12.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eedd20838bd5d75b80c9f5487dbcb06836a43833a37846cf1d8c1cc01cef59d"}, - {file = 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"^1.10.0" + +[tool.poetry.group.dev] +optional = true [tool.poetry.group.dev.dependencies] -black = "^22.12.0" mypy = "^0.991" matplotlib = "^3.6.2" isort = "^5.11.4" ipykernel = "^6.20.2" -sphinx = "^6.1.3" -sphinx-rtd-theme = "1.2.0rc4" +black = {extras = ["jupyter"], version = "^23.1.0"} +[tool.poetry.group.docs] +optional = true -[tool.poetry.group.portopt.dependencies] -scipy = "^1.10.0" -scikit-learn = "^1.2.1" +[tool.poetry.group.docs.dependencies] +sphinx = "^6.1.3" +sphinx-rtd-theme = "1.2.0rc4" [tool.isort] profile = "black" diff --git a/tests/test_portopt.py b/tests/test_portopt.py index 2856efc..0611639 100644 --- a/tests/test_portopt.py +++ b/tests/test_portopt.py @@ -6,14 +6,14 @@ import tests._unittest_numpy_extensions # noqa import yabte.utilities.pandas_extension # noqa from tests._helpers import generate_nasdaq_dataset -from yabte.utilities.lagrangian import Lagrangian +from yabte.portopt.hierarchical_risk_parity import hrp +from yabte.portopt.inverse_volatility import inverse_volatility from yabte.portopt.minimum_variance import ( minimum_variance, minimum_variance_numeric, minimum_variance_numeric_slsqp, ) -from yabte.portopt.hierarchical_risk_parity import hrp -from yabte.portopt.inverse_volatility import inverse_volatility +from yabte.utilities.lagrangian import Lagrangian class PortOptTestCase(unittest.TestCase): @@ -23,11 +23,11 @@ def setUpClass(cls): cls.closes = cls.df_combined.loc[:, (slice(None), "Close")].droplevel( axis=1, level=1 ) - cls.returns = cls.closes.price.log_returns + cls.returns = cls.closes.prc.log_returns def test_min_var(self): Sigma = self.returns.cov() - mu = self.closes.price.capm_returns() + mu = self.closes.prc.capm_returns() r = 0.1 w = minimum_variance(Sigma, mu, r) diff --git a/tests/test_strategy_runner.py b/tests/test_strategy_runner.py index f084b9e..720e5e6 100644 --- a/tests/test_strategy_runner.py +++ b/tests/test_strategy_runner.py @@ -5,6 +5,7 @@ import numpy as np import pandas as pd +from tests._helpers import generate_nasdaq_dataset from yabte.backtest import ( BasketOrder, Book, @@ -17,8 +18,6 @@ ) from yabte.utilities.strategy_helpers import crossover -from tests._helpers import generate_nasdaq_dataset - logger = logging.getLogger(__name__) diff --git a/tests/test_utilities.py b/tests/test_utilities.py index 56e9d6e..e744724 100644 --- a/tests/test_utilities.py +++ b/tests/test_utilities.py @@ -13,12 +13,14 @@ class UtilitiesTestCase(unittest.TestCase): @classmethod def setUpClass(cls): cls.asset_meta, cls.df_combined = generate_nasdaq_dataset() - cls.closes = cls.df_combined.loc[:, (slice(None), "Close")].droplevel(axis=1, level=1) - cls.returns = cls.closes.price.log_returns + cls.closes = cls.df_combined.loc[:, (slice(None), "Close")].droplevel( + axis=1, level=1 + ) + cls.returns = cls.closes.prc.log_returns def test_lagrangian(self): Sigma = self.returns.cov() - mu = self.closes.price.capm_returns() + mu = self.closes.prc.capm_returns() r = 0.1 # solve algebraically @@ -28,10 +30,10 @@ def test_lagrangian(self): A = mu.T @ SigmaInv @ ones B = mu.T @ SigmaInv @ mu C = ones.T @ SigmaInv @ ones - D = B*C - A*A - l1 = (C*r - A)/D - l2 = (B - A*r)/D - w = SigmaInv@(l1 * mu + l2 * ones) + D = B * C - A * A + l1 = (C * r - A) / D + l2 = (B - A * r) / D + w = SigmaInv @ (l1 * mu + l2 * ones) # sanity checks self.numpyAssertAllclose(w.sum(), 1) @@ -44,11 +46,12 @@ def test_lagrangian(self): lambda x: r - x.T @ mu, lambda x: 1 - x.T @ ones, ], - x0=np.ones(m)/m + x0=np.ones(m) / m, ) wn = L.fit() self.numpyAssertAllclose(wn, w) + if __name__ == "__main__": - unittest.main() \ No newline at end of file + unittest.main() diff --git a/yabte/backtest/__init__.py b/yabte/backtest/__init__.py index f803e23..dba4be9 100644 --- a/yabte/backtest/__init__.py +++ b/yabte/backtest/__init__.py @@ -28,4 +28,4 @@ "Trade", "Strategy", "StrategyRunner", -] \ No newline at end of file +] diff --git a/yabte/backtest/asset.py b/yabte/backtest/asset.py index 1319478..6518e39 100644 --- a/yabte/backtest/asset.py +++ b/yabte/backtest/asset.py @@ -1,6 +1,5 @@ from dataclasses import dataclass - __all__ = ["Asset"] diff --git a/yabte/backtest/trade.py b/yabte/backtest/trade.py index 706796e..93dc4f4 100644 --- a/yabte/backtest/trade.py +++ b/yabte/backtest/trade.py @@ -13,6 +13,7 @@ class Trade: """A frozen record of the transaction for time `ts` and `asset_name` along with `quantity` and `price`.""" + ts: pd.Timestamp quantity: Decimal price: Decimal diff --git a/yabte/portopt/hierarchical_risk_parity.py b/yabte/portopt/hierarchical_risk_parity.py index 9223d28..6ddf6b7 100644 --- a/yabte/portopt/hierarchical_risk_parity.py +++ b/yabte/portopt/hierarchical_risk_parity.py @@ -12,13 +12,13 @@ 59–69. https://doi.org/10.3905/jpm.2016.42.4.059 """ -import pandas as pd import numpy as np +import pandas as pd from scipy.cluster.hierarchy import linkage, to_tree - # following 3 functions taken directly from paper [LP] + def _getIVP(cov, **kargs): # Compute the inverse-variance portfolio ivp = 1.0 / np.diag(cov) @@ -33,6 +33,7 @@ def _getClusterVar(cov, cItems): cVar = np.dot(np.dot(w_.T, cov_), w_)[0, 0] return cVar + def _getRecBipart(cov, sortIx): # Compute HRP alloc w = pd.Series(1, index=sortIx) @@ -61,9 +62,9 @@ def hrp(corr: pd.DataFrame, sigma: np.ndarray) -> np.ndarray: cov = np.diag(sigma) @ corr @ np.diag(sigma) cov.index, cov.columns = corr.index, corr.columns rho = corr.values - D = np.sqrt((1 - rho)/2) + D = np.sqrt((1 - rho) / 2) I, J = np.triu_indices_from(D, 1) - link = linkage(np.sqrt(np.sum((D[I] - D[J])**2, axis=1))) + link = linkage(np.sqrt(np.sum((D[I] - D[J]) ** 2, axis=1))) ix_sorted = to_tree(link, rd=False).pre_order() cols_sorted = corr.columns[ix_sorted] return _getRecBipart(cov, cols_sorted) diff --git a/yabte/portopt/inverse_volatility.py b/yabte/portopt/inverse_volatility.py index e6965ed..bc8e7ae 100644 --- a/yabte/portopt/inverse_volatility.py +++ b/yabte/portopt/inverse_volatility.py @@ -12,7 +12,8 @@ import numpy as np -def inverse_volatility(cov : np.ndarray) -> np.ndarray: + +def inverse_volatility(cov: np.ndarray) -> np.ndarray: """Calculate weights using inverse variance.""" - sigma_inv = np.sqrt(np.diag(cov))**-1 - return sigma_inv / (np.ones_like(sigma_inv) @ sigma_inv) \ No newline at end of file + sigma_inv = np.sqrt(np.diag(cov)) ** -1 + return sigma_inv / (np.ones_like(sigma_inv) @ sigma_inv) diff --git a/yabte/portopt/minimum_variance.py b/yabte/portopt/minimum_variance.py index 622b9c8..4ed5638 100644 --- a/yabte/portopt/minimum_variance.py +++ b/yabte/portopt/minimum_variance.py @@ -50,7 +50,9 @@ def minimum_variance_numeric(Sigma: np.ndarray, mu: np.ndarray, r: float) -> np. return L.fit() -def minimum_variance_numeric_slsqp(Sigma: np.ndarray, mu: np.ndarray, r: float) -> np.ndarray: +def minimum_variance_numeric_slsqp( + Sigma: np.ndarray, mu: np.ndarray, r: float +) -> np.ndarray: """Calculate weights using Lagrangian multipliers and numeric solution (using scipy's minimize function).""" from scipy.optimize import minimize diff --git a/yabte/utilities/lagrangian.py b/yabte/utilities/lagrangian.py index 27597f3..a925a7d 100644 --- a/yabte/utilities/lagrangian.py +++ b/yabte/utilities/lagrangian.py @@ -2,7 +2,7 @@ from typing import Callable, List, Optional import numpy as np -from scipy.optimize import root, OptimizeResult +from scipy.optimize import OptimizeResult, root from scipy.optimize._numdiff import approx_derivative diff --git a/yabte/utilities/pandas_extension.py b/yabte/utilities/pandas_extension.py index f7e3362..40fd86c 100644 --- a/yabte/utilities/pandas_extension.py +++ b/yabte/utilities/pandas_extension.py @@ -1,8 +1,8 @@ -import pandas as pd import numpy as np +import pandas as pd -@pd.api.extensions.register_dataframe_accessor("scale") +@pd.api.extensions.register_dataframe_accessor("scl") class ScaleAccessor: def __init__(self, pandas_obj): self._obj = pandas_obj @@ -12,7 +12,7 @@ def standard(self): return (self._obj - self._obj.mean()) / self._obj.std() -@pd.api.extensions.register_dataframe_accessor("price") +@pd.api.extensions.register_dataframe_accessor("prc") class PriceAccessor: # TODO add ledoit cov (via sklearn) # http://www.ledoit.net/honey.pdf @@ -57,7 +57,7 @@ def capm_returns(self, risk_free_rate=0): def null_blips(self, sd=5, sdd=7): df = self._obj - z = df.scale.standard + z = df.scl.standard zd = z.diff() # TODO support blips longer than 1 day? for col, series in df[z.abs() > sd].dropna(how="all").dropna(axis=1).items(): diff --git a/yabte/utilities/strategy_helpers.py b/yabte/utilities/strategy_helpers.py index c854438..8d5d264 100644 --- a/yabte/utilities/strategy_helpers.py +++ b/yabte/utilities/strategy_helpers.py @@ -2,7 +2,7 @@ def crossover(series1: pd.Series, series2: pd.Series) -> bool: - """Determine if two series cross over one another. Returns `True` + """Determine if two series cross over one another. Returns `True` if `series1` just crosses above `series2`. >>> crossover(self.data.Close, self.sma) @@ -11,4 +11,4 @@ def crossover(series1: pd.Series, series2: pd.Series) -> bool: try: return series1[-2] < series2[-2] and series1[-1] > series2[-1] except IndexError: - return False \ No newline at end of file + return False