Merge branch 'dev' into master

okama/asset_list.py

@@ -290,7 +290,7 @@ def get_cagr(self, period: Optional[int] = None, real: bool = False) -> pd.Serie
         cagr = Frame.get_cagr(df[dt:])
         if real:
             if not hasattr(self, "inflation"):
-                raise Exception(
+                raise ValueError(
                     "Real CAGR is not defined. Set inflation=True in AssetList to calculate it."
                 )
             mean_inflation = Frame.get_cagr(self.inflation_ts[dt:])
@@ -389,7 +389,7 @@ def get_cumulative_return(
         cr = Frame.get_cumulative_return(df[dt:])
         if real:
             if not hasattr(self, "inflation"):
-                raise Exception(
+                raise ValueError(
                     "Real cumulative return is not defined (no inflation information is available)."
                     "Set inflation=True in AssetList to calculate it."
                 )
@@ -613,7 +613,7 @@ def real_mean_return(self) -> pd.Series:
         dtype: float64
         """
         if not hasattr(self, "inflation"):
-            raise Exception(
+            raise ValueError(
                 "Real Return is not defined. Set inflation=True to calculate."
             )
         df = pd.concat(

okama/common/helpers.py

@@ -235,7 +235,7 @@ def get_okid_index(rates: pd.Series, symbol: str) -> pd.Series:
             )
             start_period += 1
         if index_total is None:
-            raise Exception("`index_total` should not be `None`")
+            raise ValueError("`index_total` should not be `None`")
         result = index_total
         result = (np.diff(result) / result[:-1] + 1.0).cumprod() - 1.0
         result = [0] + result

okama/common/make_asset_list.py

@@ -242,7 +242,7 @@ def _make_real_return_time_series(self, df: pd.DataFrame) -> pd.DataFrame:
         Rate of return monthly data is adjusted for inflation.
         """
         if not hasattr(self, "inflation"):
-            raise Exception(
+            raise ValueError(
                 "Real return is not defined. Set inflation=True when initiating the class."
             )
         df = (1.0 + df).divide(1.0 + self.inflation_ts, axis=0) - 1.0

okama/frontier/multi_period.py

@@ -232,7 +232,7 @@ def _get_cagr(self, weights):
         acc_return = (ts + 1.).prod() - 1.
         return (1. + acc_return) ** (_MONTHS_PER_YEAR / ts.shape[0]) - 1.
 
-    def minimize_risk(self, target_return: float) -> Dict[str, float]:
+    def minimize_risk(self, target_value: float) -> Dict[str, float]:
         """
         Returns the optimal weights and risk / cagr values for a min risk at the target cagr.
         """
@@ -253,7 +253,7 @@ def objective_function(w):
                             'fun': lambda weights: np.sum(weights) - 1
                             }
         cagr_is_target = {'type': 'eq',
-                          'fun': lambda weights: target_return - self._get_cagr(weights)
+                          'fun': lambda weights: target_value - self._get_cagr(weights)
                           }
 
         weights = minimize(objective_function,
@@ -270,10 +270,10 @@ def objective_function(w):
         if weights.success:
             asset_labels = self.symbols if self.ticker_names else list(self.names.values())
             point = {x: y for x, y in zip(asset_labels, weights.x)}
-            point['CAGR'] = target_return
+            point['CAGR'] = target_value
             point['Risk'] = weights.fun
         else:
-            raise Exception(f'There is no solution for target cagr {target_return}.')
+            raise RecursionError(f'No solution found for target risk value: {target_value}.')
         return point
 
     def maximize_risk(self, target_return: float) -> Dict[str, float]:
@@ -319,7 +319,7 @@ def objective_function(w):
             point['CAGR'] = target_return
             point['Risk'] = - weights.fun
         else:
-            raise Exception(f'There is no solution for target cagr {target_return}.')
+            raise RecursionError(f'No solution found for target risk value: {target_return}.')
         return point
 
     @property

okama/frontier/single_period.py

@@ -96,7 +96,7 @@ def gmv_weights(self) -> np.ndarray:
         if weights.success:
             return weights.x
         else:
-            raise Exception("No solutions where found")
+            raise RecursionError("No solutions where found")
 
     @property
     def gmv_monthly(self) -> Tuple[float, float]:
@@ -169,7 +169,7 @@ def objective_function(w, ror):
             }
             return point
         else:
-            raise Exception("No solutions where found")
+            raise RecursionError("No solutions where found")
 
     def minimize_risk(
         self,
@@ -233,7 +233,7 @@ def objective_function(w):
             # point['CAGR (approx)'] = r_gmean
             point["Risk"] = a_risk
         else:
-            raise Exception("No solutions were found")
+            raise RecursionError("No solutions were found")
         return point
 
     @property

okama/macro.py

@@ -48,7 +48,7 @@ def _check_namespace(self):
         namespace = self.symbol.split(".", 1)[-1]
         allowed_namespaces = get_macro_namespaces()
         if namespace not in allowed_namespaces:
-            raise Exception(
+            raise ValueError(
                 f"{namespace} is not in allowed namespaces: {allowed_namespaces}"
             )
 
@@ -76,7 +76,7 @@ def cumulative_inflation(self) -> pd.Series:
         Return cumulative inflation rate time series for a period from first_date to last_date.
         """
         if self.symbol.split(".", 1)[-1] != "INFL":
-            raise Exception("cumulative_inflation is defined for inflation only")
+            raise ValueError("cumulative_inflation is defined for inflation only")
         return (self.values_ts + 1.0).cumprod() - 1.0
 
     @property
@@ -96,7 +96,7 @@ def rolling_inflation(self) -> pd.Series:
         Return 12 months rolling inflation time series.
         """
         if self.symbol.split(".", 1)[-1] != "INFL":
-            raise Exception("cumulative_inflation is defined for inflation only")
+            raise ValueError("cumulative_inflation is defined for inflation only")
         x = (self.values_ts + 1.0).rolling(_MONTHS_PER_YEAR).apply(
             np.prod, raw=True
         ) - 1.0

okama/portfolio.py

@@ -452,7 +452,7 @@ def get_cagr(self, period: Optional[int] = None, real: bool = False) -> pd.Serie
         cagr = Frame.get_cagr(df[dt:])
         if real:
             if not hasattr(self, "inflation"):
-                raise Exception(
+                raise ValueError(
                     "Real CAGR is not defined. Set inflation=True in Portfolio to calculate it."
                 )
             mean_inflation = Frame.get_cagr(self.inflation_ts[dt:])
@@ -557,7 +557,7 @@ def get_cumulative_return(self, period: Union[str, int, None] = None, real: bool
         cr = Frame.get_cumulative_return(df[dt:])
         if real:
             if not hasattr(self, "inflation"):
-                raise Exception(
+                raise ValueError(
                     "Real cumulative return is not defined (no inflation information is available)."
                     "Set inflation=True in Portfolio to calculate it."
                 )
@@ -723,7 +723,7 @@ def real_mean_return(self) -> float:
         0.3088967455111862
         """
         if not hasattr(self, "inflation"):
-            raise Exception(
+            raise ValueError(
                 "Real Return is not defined. Set inflation=True to calculate."
             )
         infl_mean = Float.annualize_return(self.inflation_ts.mean())

tests/test_asset_list.py

@@ -13,7 +13,7 @@
 
 @mark.asset_list
 def test_asset_list_init_failing():
-    with pytest.raises(Exception, match=r"Assets must be a list."):
+    with pytest.raises(ValueError, match=r"Assets must be a list."):
         ok.AssetList(assets=("RUB.FX", "MCFTR.INDX"))
 
 
@@ -153,7 +153,7 @@ def test_get_cagr_value_error(self):
             self.asset_list.get_cagr(period=3, real=True)
 
     def test_get_cagr_real_no_inflation_exception(self):
-        with pytest.raises(Exception):
+        with pytest.raises(ValueError):
             self.asset_list_no_infl.get_cagr(period=1, real=True)
 
     @pytest.mark.parametrize(
@@ -171,7 +171,7 @@ def test_get_rolling_cagr(self, real, expected1, expected2):
         (0, False, ValueError),  # window should be at least 12 months for CAGR
         (12.5, False, ValueError),  # not an integer
         (10 * 12, False, ValueError),  # window size should be in the history period
-        (12, True, Exception),  # real CAGR is defined when AssetList(inflation=True) only
+        (12, True, ValueError),  # real CAGR is defined when AssetList(inflation=True) only
     ]
 
     @pytest.mark.parametrize("window, real, exception", get_rolling_cagr_error_data)
@@ -221,7 +221,7 @@ def test_get_cumulative_return_value_error(self):
             self.asset_list.get_cumulative_return(period=3, real=True)
 
     def test_get_cumulative_return_real_no_inflation_exception(self):
-        with pytest.raises(Exception):
+        with pytest.raises(ValueError):
             self.asset_list_no_infl.get_cumulative_return(period=1, real=True)
 
     def test_get_rolling_cumulative_return(self):
@@ -286,7 +286,7 @@ def test_get_dividend_mean_growth_rate_value_err(self):
 
     def test_tracking_difference_failing(self):
         with pytest.raises(
-            Exception,
+            ValueError,
             match="At least 2 symbols should be provided to calculate Tracking Difference.",
         ):
             self.spy.tracking_difference
@@ -318,7 +318,7 @@ def test_skewness(self):
 
     def test_rolling_skewness_failing(self):
         with pytest.raises(
-            Exception, match=r"window size is more than data history depth"
+            ValueError, match=r"window size is more than data history depth"
         ):
             self.asset_list.skewness_rolling(window=24)
 

tests/test_frontier.py

@@ -11,13 +11,13 @@
 
 @mark.frontier
 def test_init_efficient_frontier_failing():
-    with pytest.raises(Exception, match=r'The number of symbols cannot be less than two'):
+    with pytest.raises(ValueError, match=r'The number of symbols cannot be less than two'):
         ok.EfficientFrontier(assets=['MCFTR.INDX'])
 
 
 @mark.frontier
 def test_bounds_setter_failing(init_efficient_frontier):
-    with pytest.raises(Exception, match=r'The number of symbols \(2\) and the length of bounds \(3\) should be equal.'):
+    with pytest.raises(ValueError, match=r'The number of symbols \(2\) and the length of bounds \(3\) should be equal.'):
         init_efficient_frontier.bounds = ((0, 1.), (0.5, 1.), (0, 0.5))
 
 

tests/test_frontier_reb.py

@@ -13,7 +13,7 @@
 @mark.rebalance
 @mark.frontier
 def test_init_efficient_frontier_reb():
-    with pytest.raises(Exception, match=r'The number of symbols cannot be less than two'):
+    with pytest.raises(ValueError, match=r'The number of symbols cannot be less than two'):
         ok.EfficientFrontierReb(assets=['MCFTR.INDX'])
 
 

tests/test_portfolio.py

@@ -168,7 +168,7 @@ def test_get_cagr_real(portfolio_rebalanced_month, input_data, expected):
 
 
 def test_get_cagr_real_no_inflation_exception(portfolio_no_inflation):
-    with pytest.raises(Exception):
+    with pytest.raises(ValueError):
         portfolio_no_inflation.get_cagr(period=1, real=True)
 
 
@@ -185,7 +185,7 @@ def test_cumulative_return(portfolio_rebalanced_month, period, real, expected):
 cumulative_return_fail = [
     (1.5, False, TypeError),
     (-1, False, ValueError),
-    (1, True, Exception),
+    (1, True, ValueError),
 ]
 
 
@@ -210,7 +210,7 @@ def test_describe_no_inflation(portfolio_no_inflation):
 def test_percentile_from_history(portfolio_rebalanced_month, portfolio_short_history):
     assert portfolio_rebalanced_month.percentile_from_history(years=1).iloc[0, 1] == approx(0.12456, rel=1e-2)
     with pytest.raises(
-        Exception,
+        ValueError,
         match="Time series does not have enough history to forecast. "
         "Period length is 0.90 years. At least 2 years are required.",
     ):
@@ -235,23 +235,23 @@ def test_get_rolling_cagr(portfolio_rebalanced_month, window, real, expected):
 
 def test_get_rolling_cagr_failing_short_window(portfolio_not_rebalanced):
     with pytest.raises(
-        Exception,
+        ValueError,
         match="window size should be at least 1 year"
     ):
         portfolio_not_rebalanced.get_rolling_cagr(window=1)
 
 
 def test_get_rolling_cagr_failing_long_window(portfolio_not_rebalanced):
     with pytest.raises(
-        Exception,
+        ValueError,
         match="window size is more than data history depth"
     ):
         portfolio_not_rebalanced.get_rolling_cagr(window=100)
 
 
 def test_get_rolling_cagr_failing_no_inflation(portfolio_no_inflation):
     with pytest.raises(
-        Exception,
+        ValueError,
         match="Real return is not defined. Set inflation=True when initiating the class."
     ):
         portfolio_no_inflation.get_rolling_cagr(real=True)