year_intervals and long_periods

long_periods.py

@@ -0,0 +1,39 @@
+import datetime
+import lib
+from matplotlib import pyplot as plt
+import strategies as st
+import pandas as pd
+
+if __name__ == "__main__":
+    stockList = ["^GSPC"]
+    monthly_params = dict(sum=100000, coef=1.005, t_rate=1 + 0.02 / 12)
+    # startDate = datetime.datetime.fromisoformat("2000-01-01")
+    # endDate = datetime.datetime.fromisoformat("2022-01-01")
+    print(stockList[0])
+    stockData = lib.get_data(
+        stockList[0],
+    )
+    print(
+        "Investing monthly, increasing {:.2f}%, starting from ${}".format(
+            (monthly_params["coef"] * 100) - 100,
+            monthly_params["sum"],
+        )
+    )
+    for period_years in (10, 20):
+        end = datetime.date.today()
+        start = end - datetime.timedelta(days=period_years * 365)
+        stockData = lib.get_data(stockList[0], start, end)
+        print(
+            "{} to {}, {:.1f} years".format(
+                start,
+                end,
+                (end - start).days / 365,
+            )
+        )
+        newdf = pd.concat(
+            [
+                lib.test_strategy(stockData, strategy, monthly_params)
+                for strategy in (st.DCA, st.QDCA)
+            ]
+        )
+        print(newdf.to_string())

year_intervals.py

@@ -5,24 +5,16 @@ import strategies as st
 import pandas as pd
 
 if __name__ == "__main__":
-    stockList = ["BRK-A"]
+    stockList = ["^GSPC"]
     monthly_params = dict(sum=100000, coef=1.005, t_rate=1 + 0.02 / 12)
     # startDate = datetime.datetime.fromisoformat("2000-01-01")
     # endDate = datetime.datetime.fromisoformat("2022-01-01")
     print(stockList[0])
-    """
-    for period_years in (10, 20):
-        end_date = datetime.datetime.now()
-        start_date = end_date - datetime.timedelta(days=period_years * 365)
-        stockData = get_data(stockList[0], start_date, end_date)
-        simulate(stockData, monthly_params)
-    """
-    period_years = 5
     stockData = lib.get_data(
         stockList[0],
     )
     start_date = stockData.index[0]
-    year_step = 3
+    year_step = 5
     print(
         "Investing monthly, increasing {:.2f}%, starting from ${}".format(
             (monthly_params["coef"] * 100) - 100,