From e9bb795ecf052d6eba2cad2950b9e633f19bb48b Mon Sep 17 00:00:00 2001
From: gouravkr <gourav2711@gmail.com>
Date: Mon, 6 Jun 2022 08:33:58 +0530
Subject: [PATCH] Tests for beta and bug fixes

---
 pyfacts/pyfacts.py    |  4 ++--
 pyfacts/statistics.py |  2 ++
 tests/test_stats.py   | 34 ++++++++++++++++++++++++++++++++++
 3 files changed, 38 insertions(+), 2 deletions(-)

diff --git a/pyfacts/pyfacts.py b/pyfacts/pyfacts.py
index 49d3633..12a8306 100644
--- a/pyfacts/pyfacts.py
+++ b/pyfacts/pyfacts.py
@@ -140,7 +140,7 @@ class TimeSeries(TimeSeriesCore):
         self,
         data: List[Iterable] | Mapping,
         frequency: Literal["D", "W", "M", "Q", "H", "Y"] = None,
-        validate_frequency: bool = False,
+        validate_frequency: bool = True,
         date_format: str = "%Y-%m-%d",
     ):
         """Instantiate a TimeSeriesCore object"""
@@ -448,7 +448,7 @@ class TimeSeries(TimeSeriesCore):
             )
             rolling_returns.append(returns)
         rolling_returns.sort()
-        return self.__class__(rolling_returns, self.frequency.symbol)
+        return self.__class__(rolling_returns, frequency.symbol)
 
     @date_parser(1, 2)
     def volatility(
diff --git a/pyfacts/statistics.py b/pyfacts/statistics.py
index 6ef3f5e..d5e092f 100644
--- a/pyfacts/statistics.py
+++ b/pyfacts/statistics.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import datetime
 import statistics
 from typing import Literal
diff --git a/tests/test_stats.py b/tests/test_stats.py
index 7eee9b0..9ad1a61 100644
--- a/tests/test_stats.py
+++ b/tests/test_stats.py
@@ -82,3 +82,37 @@ class TestSharpe:
             return_period_value=12,
         )
         assert round(sharpe_ratio, 4) == 0.3199
+
+
+class TestBeta:
+    def test_beta_daily_freq(self, create_test_data):
+        market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
+        stock_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D, mu=0.12, sigma=0.08)
+        sts = pft.TimeSeries(stock_data, "D")
+        mts = pft.TimeSeries(market_data, "D")
+        beta = pft.beta(sts, mts, frequency="D", return_period_unit="days", return_period_value=1)
+        assert round(beta, 4) == 1.6001
+
+    def test_beta_daily_freq_daily_returns(self, create_test_data):
+        market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
+        stock_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D, mu=0.12, sigma=0.08)
+        sts = pft.TimeSeries(stock_data, "D")
+        mts = pft.TimeSeries(market_data, "D")
+        beta = pft.beta(sts, mts)
+        assert round(beta, 4) == 1.6292
+
+    def test_beta_monthly_freq(self, create_test_data):
+        market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
+        stock_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D, mu=0.12, sigma=0.08)
+        sts = pft.TimeSeries(stock_data, "D")
+        mts = pft.TimeSeries(market_data, "D")
+        beta = pft.beta(sts, mts, frequency="M")
+        assert round(beta, 4) == 1.629
+
+    def test_beta_monthly_freq_monthly_returns(self, create_test_data):
+        market_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D)
+        stock_data = create_test_data(num=3600, frequency=pft.AllFrequencies.D, mu=0.12, sigma=0.08)
+        sts = pft.TimeSeries(stock_data, "D")
+        mts = pft.TimeSeries(market_data, "D")
+        beta = pft.beta(sts, mts, frequency="M", return_period_unit="months", return_period_value=1)
+        assert round(beta, 4) == 1.6023