chore: check if an asset has historical data period too short (ListMaker)

Author: chilango74

main.py

@@ -1,41 +1,6 @@
 import okama as ok
 
-tk = ['VCIT.US',
- 'VTIP.US',
- 'TIP.US',
- 'SCHP.US',
- 'FXRU.MOEX',
- 'HACK.US',
- 'JETS.US',
- 'XAR.US',
- 'QQQ.US',
- 'VBR.US',
- 'VBK.US',
- 'PGJ.US',
- 'VOO.US',
- 'IHAK.US',
- 'VNQ.US',
- 'SLV.US',
- 'GLDM.US']
+tk = ['FXGD.MOEX', 'FXRD.MOEX']
+al = ok.AssetList(assets=tk, ccy='USD', inflation=True, last_date='2021-10')
 
-wt = [0.14,
- 0.13,
- 0.03,
- 0.29,
- 0.05,
- 0.03,
- 0.01,
- 0.01,
- 0.01,
- 0.04,
- 0.03,
- 0.01,
- 0.02,
- 0.02,
- 0.03,
- 0.03,
- 0.12]
-
-pf = ok.Portfolio(assets=tk, weights=wt, ccy='USD', inflation=True)
-
-print(pf.dividend_yield)
+print(al.wealth_indexes)

okama/asset.py

@@ -4,7 +4,7 @@
 import numpy as np
 
 from .common.helpers.helpers import Frame
-from .settings import default_ticker
+from .settings import default_ticker, PeriodLength, _MONTHS_PER_YEAR
 from .api.data_queries import QueryData
 from .api.namespaces import get_assets_namespaces
 
@@ -31,6 +31,10 @@ def __init__(self, symbol: str = default_ticker):
         self.period_length: float = round(
             (self.last_date - self.first_date) / np.timedelta64(365, "D"), ndigits=1
         )
+        self.pl = PeriodLength(
+            self.ror.shape[0] // _MONTHS_PER_YEAR,
+            self.ror.shape[0] % _MONTHS_PER_YEAR,
+        )
 
     def __repr__(self):
         dic = {

okama/common/helpers/helpers.py

@@ -554,6 +554,10 @@ def subtract_years(dt: pd.Timestamp, years: int) -> pd.Timestamp:
             raise TypeError("The period should be integer")
         return new_dt
 
+    @staticmethod
+    def get_difference_in_months(last_day: pd.Timestamp, first_day: pd.Timestamp):
+        return last_day.to_period('M') - first_day.to_period('M')
+
 
 class Index:
     @staticmethod

okama/common/make_asset_list.py

@@ -6,7 +6,7 @@
 import matplotlib.pyplot as plt
 
 from .validators import validate_integer
-from ..common.helpers.helpers import Frame, Float
+from ..common.helpers.helpers import Frame, Float, Date
 from ..macro import Inflation
 from ..asset import Asset
 from ..settings import default_ticker, PeriodLength, _MONTHS_PER_YEAR
@@ -61,7 +61,7 @@ def __init__(
             self.assets_first_dates,
             self.assets_last_dates,
             self.assets_ror,
-        ) = self._make_list(ls=self._list_of_asset_like_objects).values()
+        ) = self._make_list(ls=self._list_of_asset_like_objects, first_date=first_date, last_date=last_date).values()
         if first_date:
             self.first_date = max(self.first_date, pd.to_datetime(first_date))
         self.assets_ror = self.assets_ror[self.first_date:]
@@ -101,7 +101,7 @@ def __repr__(self):
     def __len__(self):
         return len(self.symbols)
 
-    def _make_list(self, ls: list) -> dict:
+    def _make_list(self, ls: list, first_date, last_date) -> dict:
         """
         Make an asset list from a list of symbols.
         """
@@ -117,21 +117,26 @@ def _make_list(self, ls: list) -> dict:
         df = pd.DataFrame()
         for i, x in enumerate(ls):
             asset = x if hasattr(x, 'symbol') and hasattr(x, 'ror') else Asset(x)
-            asset_obj_dict.update({asset.symbol: asset})
+            if asset.pl.years == 0 and asset.pl.months <= 2:
+                raise ValueError(f'{asset.symbol} period length is {asset.pl.months}. It should be at least 3 months.')
+            asset_first_date = max(asset.first_date, pd.to_datetime(first_date)) if first_date else asset.first_date
+            asset_last_date = min(asset.last_date, pd.to_datetime(last_date)) if last_date else asset.last_date
+            if Date.get_difference_in_months(asset_last_date, asset_first_date).n < 2:
+                raise ValueError(f'{asset.symbol} historical data period length is too short. '
+                                 f'It must be at least 3 months.')
+            asset_obj_dict[asset.symbol] = asset
             if i == 0:  # required to use pd.concat below (df should not be empty).
                 df = self._make_ror(asset, currency_name)
             else:
                 new = self._make_ror(asset, currency_name)
                 df = pd.concat([df, new], axis=1, join="inner", copy="false")
-            currencies.update({asset.symbol: asset.currency})
-            names.update({asset.symbol: asset.name})
-            first_dates.update({asset.symbol: asset.first_date})
-            last_dates.update({asset.symbol: asset.last_date})
-        # Add currency to the date range dict
-        first_dates.update({currency_name: currency_first_date})
-        last_dates.update({currency_name: currency_last_date})
-        currencies.update({"asset list": currency_name})
-
+            currencies[asset.symbol] = asset.currency
+            names[asset.symbol] = asset.name
+            first_dates[asset.symbol] = asset.first_date
+            last_dates[asset.symbol] = asset.last_date
+        first_dates[currency_name] = currency_first_date
+        last_dates[currency_name] = currency_last_date
+        currencies["asset list"] = currency_name
         first_dates_sorted: list = sorted(first_dates.items(), key=lambda y: y[1])
         last_dates_sorted: list = sorted(last_dates.items(), key=lambda y: y[1])
         if isinstance(df, pd.Series):

tests/conftest.py

@@ -78,7 +78,6 @@ def _init_asset_list(
         inflation=True,
     )
 
-
 # Portfolio
 @pytest.fixture(scope="package")
 def init_portfolio_values():

tests/test_asset_list.py

@@ -15,6 +15,10 @@
 def test_asset_list_init_failing():
     with pytest.raises(ValueError, match=r"Assets must be a list."):
         ok.AssetList(assets=("RUB.FX", "MCFTR.INDX"))
+    with pytest.raises(ValueError, match=r"FXRD.MOEX historical data period length is too short. "
+                                         r"It must be at least 3 months."):
+        ok.AssetList(assets=['FXRD.MOEX'], last_date="2021-10", inflation=True)
+
 
 
 @mark.asset_list