diff --git a/tests/test_black_litterman.py b/tests/test_black_litterman.py
index df0f206..3c0a91e 100644
--- a/tests/test_black_litterman.py
+++ b/tests/test_black_litterman.py
@@ -239,8 +239,8 @@ def test_bl_cov_default():
 
 def test_market_risk_aversion():
     prices = pd.read_csv(
-        resource("spy_prices.csv"), parse_dates=True, index_col=0, squeeze=True
-    )
+        resource("spy_prices.csv"), parse_dates=True, index_col=0
+    ).squeeze("columns")
     delta = black_litterman.market_implied_risk_aversion(prices)
     assert np.round(delta, 5) == 2.68549
 
@@ -263,8 +263,8 @@ def test_bl_weights():
     bl = BlackLittermanModel(S, absolute_views=viewdict)
 
     prices = pd.read_csv(
-        resource("spy_prices.csv"), parse_dates=True, index_col=0, squeeze=True
-    )
+        resource("spy_prices.csv"), parse_dates=True, index_col=0
+    ).squeeze("columns")
 
     delta = black_litterman.market_implied_risk_aversion(prices)
     bl.bl_weights(delta)
@@ -316,8 +316,8 @@ def test_market_implied_prior():
     S = risk_models.sample_cov(df)
 
     prices = pd.read_csv(
-        resource("spy_prices.csv"), parse_dates=True, index_col=0, squeeze=True
-    )
+        resource("spy_prices.csv"), parse_dates=True, index_col=0
+    ).squeeze("columns")
     delta = black_litterman.market_implied_risk_aversion(prices)
 
     mcaps = get_market_caps()
@@ -375,8 +375,8 @@ def test_bl_market_prior():
     S = risk_models.sample_cov(df)
 
     prices = pd.read_csv(
-        resource("spy_prices.csv"), parse_dates=True, index_col=0, squeeze=True
-    )
+        resource("spy_prices.csv"), parse_dates=True, index_col=0
+    ).squeeze("columns")
 
     delta = black_litterman.market_implied_risk_aversion(prices)
 
@@ -468,8 +468,8 @@ def test_bl_tau():
     S = risk_models.sample_cov(df)
 
     prices = pd.read_csv(
-        resource("spy_prices.csv"), parse_dates=True, index_col=0, squeeze=True
-    )
+        resource("spy_prices.csv"), parse_dates=True, index_col=0
+    ).squeeze("columns")
 
     delta = black_litterman.market_implied_risk_aversion(prices)
 
diff --git a/tests/test_efficient_frontier.py b/tests/test_efficient_frontier.py
index c315986..6846163 100644
--- a/tests/test_efficient_frontier.py
+++ b/tests/test_efficient_frontier.py
@@ -24,7 +24,6 @@ def test_data_source():
     assert isinstance(df, pd.DataFrame)
     assert df.shape[1] == 20
     assert len(df) == 7126
-    assert df.index.is_all_dates
 
 
 def test_returns_dataframe():
@@ -33,7 +32,6 @@ def test_returns_dataframe():
     assert isinstance(returns_df, pd.DataFrame)
     assert returns_df.shape[1] == 20
     assert len(returns_df) == 7125
-    assert returns_df.index.is_all_dates
     assert not ((returns_df > 1) & returns_df.notnull()).any().any()
 
 
@@ -393,6 +391,9 @@ def test_max_sharpe_error():
     with pytest.raises(TypeError):
         ef.max_sharpe()
 
+    with pytest.raises(ValueError):
+        ef.max_sharpe(risk_free_rate=max(ef.expected_returns + 0.01))
+
 
 def test_max_sharpe_risk_free_warning():
     ef = setup_efficient_frontier()
@@ -1072,9 +1073,6 @@ def test_efficient_return():
 def test_efficient_return_error():
     ef = setup_efficient_frontier()
     max_ret = ef.expected_returns.max()
-
-    with pytest.raises(ValueError):
-        ef.efficient_return(-0.1)
     with pytest.raises(ValueError):
         # This return is too high
         ef.efficient_return(max_ret + 0.01)
diff --git a/tests/test_expected_returns.py b/tests/test_expected_returns.py
index 41225ab..93335a8 100644
--- a/tests/test_expected_returns.py
+++ b/tests/test_expected_returns.py
@@ -11,7 +11,6 @@ def test_returns_dataframe():
     assert isinstance(returns_df, pd.DataFrame)
     assert returns_df.shape[1] == 20
     assert len(returns_df) == 7125
-    assert returns_df.index.is_all_dates
     assert not ((returns_df > 1) & returns_df.notnull()).any().any()
 
 
diff --git a/tests/test_hrp.py b/tests/test_hrp.py
index 8b1eb3c..aa5b3d5 100644
--- a/tests/test_hrp.py
+++ b/tests/test_hrp.py
@@ -30,7 +30,7 @@ def test_hrp_portfolio():
     # uncomment this line if you want generating a new file
     # pd.Series(w).to_csv(resource("weights_hrp.csv"))
 
-    x = pd.read_csv(resource("weights_hrp.csv"), squeeze=True, index_col=0)
+    x = pd.read_csv(resource("weights_hrp.csv"), index_col=0).squeeze("columns")
     pd.testing.assert_series_equal(x, pd.Series(w), check_names=False, rtol=1e-2)
 
     assert isinstance(w, dict)