Implementing Walkforward to a Strategy

[chemcoder-2020]

I have a strategy class called VWAPBounceStrategy, in which the buys and sells are signaled by self.longs, self.shorts, self.longXs, and self.shortXs, which are outputs of a method called vwapbounce_signal.

I would like to implement walkforward analysis on this strategy. I looked at the ML notebook and some conversations on updating the optimal parameters. Here's a basic implementation. I would like to ask if this looks right, or is there something else needed. The workflow is retraining every month. This code does run.

  class VWAPWalkForwardStrategy(VWAPBounceStrategy):
      def next(self):
          month = (
              pd.Series(pd.DatetimeIndex(self.data.df.index).month)
              .diff()
              .abs().gt(0)
              .cumsum()
              .fillna(0)
          )
  
          if month.iloc[-1] < N_TRAIN:
              return
  
          if month.iloc[-1] == month.iloc[-2]:
              return super().next()
  
          data = self.data.df.reset_index()[month.gt(month.iloc[-1] - N_TRAIN - 1)]
          data = data.set_index("date")[:-1]
          support_rejection = [True, False]
          resistance_rejection = [True, False]
          combo_choices = list(
              itertools.product(
                  *[
                      support_rejection,
                      resistance_rejection,
                  ]
              )
          )
  
          rets = {}
          print(data.iloc[0])
          print(data.iloc[-1])
          for option in combo_choices:
              bt = Backtest(data, VWAPBounceStrategy, commission=0, cash=30000)
              output = bt.run(
                  support_rejection=option[0],
                  resistance_rejection=option[1],
              )
              _target = output["Win Rate [%]"] * output["Avg. Trade WL Ratio"]
              rets[option] = _target
          rets = pd.Series(rets)
          best = rets.idxmax()
          print(best)
  
          # use best result
          self.support_rejection = best[0]
          self.resistance_rejection = best[1]
          (
              self.longs,
              self.shorts,
              self.longXs,
              self.shortXs,
              self.ma_mid,
              self.rsi,
              self.eod,
          ) = self.I(
              self.vwapbounce_signal,
              self.data.df,
              plot=False,
          )
          super().next()

[chemcoder-2020]

More specifically, should super().next() be before the (self.longs, ...) = self.I(...) update, or after that, as it is now.