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Bitcoin trading strategy
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Hi Daniel, Happy new Year! How can I backtest the bitcoin trading strategy of Alain Glücksman? Thank you
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@Levent-Yilmaz 1. Can you post the description of the strategy and the rules, or psuedo-code?
2. Do you have bitcoin historical data?
3. What timeframe does the system work on? eg. 5 minute bars, daily, or some other type of chart?
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@scottz1 Hi, Thank you. You can find the report here https://ethz.ch/content/dam/ethz/special-interest/mtec/chair-of-entrepreneurial-risks-dam/documents/dissertation/master thesis/Master_Thesis_Glücksmann_13June2019.pdf
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class BollingerBandsW(bt.Indicator): alias = ('BBW',) lines = ('bbw',) params = (('period', 20), ('devfactor', 2.0), ('movav', MovAv.Simple),) plotinfo = dict(subplot=True, bbw=dict(_name='bbw', color='green', ls='--', _skipnan=True), ) def __init__(self): self.boll = bt.indicators.BollingerBands(self.datas[0], period=self.params.period, devfactor=self.params.devfactor) self.lines.bbw = (self.boll.top - self.boll.bot) / self.boll.mid
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class VolatilityLevel(bt.Indicator): alias = ('VolatilityLevelIndex',) lines = ('bbw', 'VLI_fast', 'VLI_top', 'VLI_slow',) params = ( ('period', 20), ('devfactor', 2.0), ('movav', MovAv.Simple), ('fast_period', 20), ('slow_period', 100), ) plotinfo = dict(subplot=True, bbw=dict(_name='bbw', color='green', ls='--', _skipnan=True), VLI_fast=dict(_name='VLI_fast', color='red', ls='--', _skipnan=True), VLI_top=dict(_name='VLI_top', color='lightred', ls='--', _skipnan=True), VLI_slow=dict(_name='VLI_slow', color='blue', ls='--', _skipnan=True), ) def __init__(self): self.lines.bbw = BollingerBandsW(self.data, period=self.params.period, devfactor=self.params.devfactor) self.lines.VLI_fast = self.p.movav(self.lines.bbw, period=self.p.fast_period) self.lines.VLI_slow = self.p.movav(self.lines.bbw, period=self.p.slow_period) std = bt.ind.StdDev(self.lines.bbw, period=self.p.slow_period) self.lines.VLI_top = self.lines.VLI_slow + 2 * stdenjoy
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@jeff-lee Hi Jeff, thank you very much. Best regards,
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Hey @jeff-lee would love to get some feedback on the trading logic? Would really appreciate your insight.
def __init__(self): self.dataclose = self.datas[0].close self.datavolume = self.datas[0].volume self.datalow = self.datas[0].low self.sma_veryfast = btind.MovingAverageSimple(self.dataclose, period=10) self.sma_fast = btind.MovingAverageSimple(self.dataclose, period=20) self.sma_mid = btind.MovingAverageSimple(self.dataclose, period=50) self.sma_slow = btind.MovingAverageSimple(self.dataclose, period=100) self.sma_veryslow = btind.MovingAverageSimple(self.dataclose, period=200) # BollingerBandsWidth = upperband - lowerband/middleband. self.bbw = BollingerBandsW() self.boll = btind.BollingerBands(self.dataclose) self.std = btind.StdDev(self.bbw.l.bbw, period=100) self.lines_bbw = (self.boll.l.top - self.boll.l.bot) / self.boll.l.mid self.volatility_level = VolatilityLevel() self.low_volatility_level = self.volatility_level.l.VLI_fast < self.volatility_level.l.VLI_slow self.high_volatility_level = self.volatility_level.l.VLI_fast > self.volatility_level.l.VLI_slow self.extreme_volatility_level = self.bbw.l.bbw > self.volatility_level.l.VLI_top self.vol_condition = (btind.MovingAverageSimple(self.datavolume, period=10) > btind.MovingAverageSimple(self.datavolume, period=50)) self.crossdown_boll_top = bt.ind.CrossDown(self.dataclose, self.boll.top) self.crossup_boll_bot = bt.ind.CrossUp(self.dataclose, self.boll.bot) self.highest_high = btind.Highest(self.dataclose, period=20) self.low_of_last_candle = self.datalow[0] self.close_of_price = self.dataclose[0] self.stop_win = None self.stop_loss = None self.order = None @staticmethod def get_params(): return dict() def notify_order(self, order): if order.status in [order.Submitted, order.Accepted]: return if order.status == order.Completed: if order.isbuy(): self.stop_loss = self.stop_loss if self.stop_loss else 0.05 * self.dataclose[-1] take_profit = order.executed.price * (1.0 + self.stop_loss) sl_ord = self.sell(exectype=bt.Order.Stop, price=order.executed.price * (1.0 - self.stop_loss)) sl_ord.addinfo(name="Stop") tkp_ord = self.buy(exectype=bt.Order.Limit, price=take_profit) tkp_ord.addinfo(name="Prof") if self.stop_win: self.sell(price=(order.executed.price * (1 + self.stop_win)), exectype=bt.Order.Limit) self.order = None def _next(self): if self.order: return if self.crossdown_boll_top and self.vol_condition: if self.close_of_price > self.sma_fast: if self.bbw.bbw < self.volatility_level.l.VLI_top: if self.low_volatility_level: if self.sma_mid > self.sma_veryslow: self.buy() else: self.buy() elif self.sma_slow > self.sma_veryslow: self.buy() self.stop_loss = self.low_of_last_candle if self.crossup_boll_bot and self.vol_condition: self.close() self.stop_loss = None self.stop_win = None portfolio_value = self.broker.get_value() trade_profit = self.broker.get_value([self.data]) / portfolio_value if trade_profit > 0.03: self.stop_win = 0.01 elif trade_profit > 0.20: self.stop_win = 0.15 elif trade_profit > 0.25: self.stop_win = 0.20 elif trade_profit > 0.30: self.stop_win = 0.25 elif trade_profit > 0.35: self.stop_win = 0.30 elif trade_profit > 0.40: self.stop_win = 0.35 if self.crossup_boll_bot and self.vol_condition: self.sell() self.stop_loss = self.highest_high
