backtest/strategies.py

import datetime
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pandas_datareader import data as pdr
import backtrader as bt

reserve = 5  # usd for comms etc cause I cant math

"""
class LSI(bt.Strategy):
    def start(self):
        self.val_start = self.broker.get_cash()

    def nextstart(self):
        size = math.floor((self.broker.get_cash() - 10) / self.data[0])
        self.buy(size=size)

    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(
            "Annualised:       {:.2f}%".format(
                100 * ((1 + self.roi) ** (365 / (endDate - actualStart).days) - 1)
            )
        )
        print(
            "Gross Return:    ${:,.2f}".format(self.broker.get_value() - self.val_start)
        )
"""


class PercentageCommisionScheme(bt.CommInfoBase):
    params = (
        ("commission", 0.0004),
        ("stocklike", True),
        ("commtype", bt.CommInfoBase.COMM_PERC),
    )

    def _getcommission(self, size, price, pseudoexec):
        return abs(size * price * self.p.commission) + 4  # 290rub/month + 0.04%


class Investing(bt.Strategy):
    def __init__(self, params={"sum": 500, "coef": 1}):
        self.monthly_params = params
        self.order = None
        self.cost = 0  # no comms
        self.comms = 0
        self.units = 0
        self.times = 0
        self.months = 0

    def log(self, txt, dt=None):
        dt = dt or self.datas[0].datetime.date(0)
        # print( "%s, V:%.2f, C:%.2f, %s" % (dt.isoformat(), self.broker.get_value(), self.broker.get_cash(), txt))

    def start(self):
        self.broker.set_fundmode(fundmode=True, fundstartval=100.0)

        self.cash_start = self.broker.get_cash()
        self.val_start = 100.0

        # ADD A TIMER
        self.add_timer(
            when=bt.timer.SESSION_START,
            monthdays=[1],
            monthcarry=True
            # timername='buytimer',
        )

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            return
        else:
            self.log(
                "%s Price %.2f, Units %.0f, Value %.2f, Comm %.2f, "
                % (
                    "BUY" if order.isbuy() else "SELL",
                    order.executed.price,
                    order.executed.size,
                    order.executed.value,
                    order.executed.comm,
                )
            )

        if order.status in [order.Completed]:
            if order.isbuy():
                self.units += order.executed.size
                self.cost += order.executed.value

            elif order.issell():
                self.units -= order.executed.size

            self.comms += order.executed.comm
            self.times += 1

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log("Order Canceled/Margin/Rejected")
            print(order.status, [order.Canceled, order.Margin, order.Rejected])

        self.order = None

    @property
    def monthly_cash(self):
        return self.monthly_params["sum"] * self.monthly_params["coef"] ** (self.months)

    def calc_params(self):
        # calculate actual returns
        self.froi = self.broker.get_fundvalue() - self.val_start
        return [
            self.froi,
            self.cost,
            self.broker.get_value(),
            self.times,
            self.units,
            self.comms,
            self.monthly_cash,
        ]

    def notify_timer(self, timer, when, *args):
        self.months += 1
        self.broker.add_cash(self.monthly_cash)


class FormulaInvesting(Investing):
    def notify_timer(self, timer, when, *args):
        super().notify_timer(timer, when, *args)
        self.formula()


class VA(FormulaInvesting):
    def formula(self):
        target_value = (
            min(
                self.monthly_cash * self.months,
                self.broker.get_value(),
            )
            - reserve
        )
        self.order_target_value(target=target_value),
        self.broker.set_cash(self.broker.get_cash() * self.monthly_params["t_rate"])


class QVA(VA):
    def formula(self):
        if not self.months % 3:
            super().formula()


class DCA(FormulaInvesting):
    def formula(self):
        target_value = self.broker.get_value() - reserve
        self.order_target_value(target=target_value)


class QDCA(DCA):
    def formula(self):
        if not self.months % 3:
            super().formula()


class SmaCross(Investing):
    params = dict(
        pfast=50,  # period for the fast moving average
        pslow=200,  # period for the slow moving average
    )
    # list of parameters which are configurable for the strategy
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        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.order_target_value(target=self.broker.get_cash())  # enter long

        elif self.crossover < 0:  # in the market & cross to the downside
            self.close()  # close long position


class SmaVA(SmaCross):
    def next(self):
        if not self.position:  # not in the market
            if self.crossover > 0:  # if fast crosses slow to the upside
                self.order_target_value(target=self.broker.get_cash())  # enter long

        elif self.crossover < 0:  # in the market & cross to the downside
            self.order_target_value(target=self.broker.get_value() / 2)  # close half