add smacross, increment investment, fix va

compare.py

@@ -43,7 +43,7 @@ def run(strategy, data, fund_mode=False):
     )
     thestrats = cerebro.run()
     thestrat = thestrats[0]
-    # cerebro.plot(iplot=False, style="candlestick")
+    cerebro.plot(iplot=False, style="candlestick")
     return thestrat
 
 
@@ -65,18 +65,18 @@ if __name__ == "__main__":
         ]
     )
 
-    stockList = ["SWPPX"]
+    stockList = ["^GSPC"]
     # startDate = datetime.datetime.fromisoformat("2000-01-01")
     # endDate = datetime.datetime.fromisoformat("2022-01-01")
     print(stockList[0])
-    for period_years in (1, 2, 5, 10, 15, 20, 25):
+    for period_years in (20, 50):
         endDate = datetime.datetime.now()
         startDate = endDate - datetime.timedelta(days=period_years * 365)
         stockData = get_data(stockList[0], startDate, endDate)
         actualStart: datetime.datetime = stockData.index[0]
         data = bt.feeds.PandasData(dataname=stockData)
 
-        for i, strategy in enumerate((st.DCA, st.QDCA, st.VA, st.QVA)):
+        for i, strategy in enumerate((st.SmaCross,)):
             therun = run(strategy, data)
             dd = therun.analyzers.drawdown
             ret = therun.analyzers.returns

strategies.py

@@ -7,9 +7,31 @@ from pandas_datareader import data as pdr
 import backtrader as bt
 
 reserve = 5  # usd for comms etc cause I cant math
-month_sum = 500  # usd
+month_sum = 5000  # usd
 
 
+class SmaCross(bt.Strategy):
+    # list of parameters which are configurable for the strategy
+    params = dict(
+        pfast=50,  # period for the fast moving average
+        pslow=200,  # period for the slow moving average
+    )
+
+    def __init__(self):
+        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average
+        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average
+        self.crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal
+
+    def next(self):
+        if not self.position:  # not in the market
+            if self.crossover > 0:  # if fast crosses slow to the upside
+                self.buy()  # enter long
+
+        elif self.crossover < 0:  # in the market & cross to the downside
+            self.close()  # close long position
+
+
+"""
 class LSI(bt.Strategy):
     def start(self):
         self.val_start = self.broker.get_cash()
@@ -21,7 +43,6 @@ class LSI(bt.Strategy):
     def stop(self):
         # calculate actual returns
         self.roi = (self.broker.get_value() / self.val_start) - 1
-        """
         print("Starting Value:  ${:,.2f}".format(self.val_start))
         print("ROI:              {:.2f}%".format(self.roi * 100.0))
         print(
@@ -111,7 +132,7 @@ class FormulaInvesting(bt.Strategy):
         return (
             self.froi,
             self.cost,
-            self.broker.get_value() + self.broker.get_cash(),
+            self.broker.get_value(),
             self.times,
             self.units,
             self.comms,
@@ -119,13 +140,19 @@ class FormulaInvesting(bt.Strategy):
 
     def notify_timer(self, timer, when, *args):
         self.months += 1
-        self.broker.add_cash(month_sum)
+        self.broker.add_cash(month_sum * 1.005 ** (self.months))
         self.formula()
 
 
 class VA(FormulaInvesting):
     def formula(self):
-        target_value = min(self.months * month_sum, self.broker.get_value()) - reserve
+        target_value = (
+            min(
+                self.months * month_sum * 1.005 ** (self.months),
+                self.broker.get_value(),
+            )
+            - reserve
+        )
         self.order_target_value(target=target_value),