The Lazy Bear Squeeze Momentum strategy is a quantitative trading strategy that combines Bollinger Bands, Keltner Channels and a momentum indicator. It utilizes Bollinger Bands and Keltner Channels to determine if the market is currently in a squeeze, then uses a momentum indicator to generate trading signals.
The main advantage of this strategy is being able to automatically identify the start of trending moves and determine entry timing with the momentum indicator. However, there are also certain risks that need to be addressed through optimization across different products.
The Lazy Bear Squeeze Momentum strategy makes judgements based on the following three indicators:
When the Bollinger upper band is below the Keltner upper line and the Bollinger lower band is above the Keltner lower line, we determine the market is in a squeeze. This usually implies a trending move is about to start.
To pinpoint entry timing, we use the momentum indicator to gauge the speed of price changes. A buy signal is generated when momentum crosses above its moving average, and a sell signal when momentum crosses below its moving average.
The main advantages of the Lazy Bear Squeeze Momentum strategy:
There are also certain risks to the Lazy Bear Squeeze Momentum strategy:
To mitigate risks, recommendations include: optimizing lengths for Bollinger & Keltner, adjusting stop loss, selecting liquid products, verifying signals with other indicators.
The main directions to further enhance performance:
Through rigorous testing and optimization, the strategy’s edge and profitability can be greatly improved.
The Lazy Bear Squeeze Momentum strategy has strong signal generation through a multi-indicator approach, and can effectively identify new trend starts. But it also carries risks that necessitate optimization across trading instruments. With continual testing and enhancement, it can become a robust algorithmic trading system.
/*backtest start: 2024-01-31 00:00:00 end: 2024-02-01 00:00:00 period: 1h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=5 // This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/ // © mtahreemalam original strategy by LazyBear strategy(title = 'SQM Strategy, TP & SL', shorttitle = 'Squeeze.M Strat', overlay = true, pyramiding = 0, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, initial_capital = 1000, commission_type=strategy.commission.percent, commission_value=0.0, process_orders_on_close=true, use_bar_magnifier=true) //Strategy logic strategy_logic = input.string("Cross above 0", "Strategy Logic", options = ["LazyBear", "Cross above 0"]) // Date Range testPeriodSwitch = input(false, "Custom Backtesting Date Range",group="Backtesting Date Range") i_startTime = input(defval = timestamp("01 Jan 2022 00:01 +0000"), title = "Backtesting Start Time",group="Backtesting Date Range") i_endTime = input(defval = timestamp("31 Dec 2022 23:59 +0000"), title = "Backtesting End Time",group="Backtesting Date Range") timeCond = true isPeriod = testPeriodSwitch == true ? timeCond : true //// Stoploss and Take Profit Parameters // Enable Long Strategy enable_long_strategy = input.bool(true, title='Enable Long Strategy', group='SL/TP For Long Strategy', inline='1') long_stoploss_value = input.float(defval=5, title='Stoploss %', minval=0.1, group='SL/TP For Long Strategy', inline='2') long_stoploss_percentage = close * (long_stoploss_value / 100) / syminfo.mintick long_takeprofit_value = input.float(defval=5, title='Take Profit %', minval=0.1, group='SL/TP For Long Strategy', inline='2') long_takeprofit_percentage = close * (long_takeprofit_value / 100) / syminfo.mintick // Enable Short Strategy enable_short_strategy = input.bool(true, title='Enable Short Strategy', group='SL/TP For Short Strategy', inline='3') short_stoploss_value = input.float(defval=5, title='Stoploss %', minval=0.1, group='SL/TP For Short Strategy', inline='4') short_stoploss_percentage = close * (short_stoploss_value / 100) / syminfo.mintick short_takeprofit_value = input.float(defval=5, title='Take Profit %', minval=0.1, group='SL/TP For Short Strategy', inline='4') short_takeprofit_percentage = close * (short_takeprofit_value / 100) / syminfo.mintick //// Inputs //SQUEEZE MOMENTUM STRATEGY length = input(20, title='BB Length', group = "Squeeze Momentum Settings") mult = input(2.0, title='BB MultFactor', group = "Squeeze Momentum Settings") source = close lengthKC = input(20, title='KC Length', group = "Squeeze Momentum Settings") multKC = input(1.5, title='KC MultFactor', group = "Squeeze Momentum Settings") useTrueRange = input(true, title='Use TrueRange (KC)', group = "Squeeze Momentum Settings") signalPeriod=input(5, title="Signal Length", group = "Squeeze Momentum Settings") show_labels_sqm = input(title='Show Buy/Sell SQM Labels', defval=true, group = "Squeeze Momentum Settings") h0 = hline(0) // Defining MA ma = ta.sma(source, length) // Calculate BB basis = ma dev = mult * ta.stdev(source, length) upperBB = basis + dev lowerBB = basis - dev // Calculate KC range_1 = useTrueRange ? ta.tr : high - low rangema = ta.sma(range_1, lengthKC) upperKC = ma + rangema * multKC lowerKC = ma - rangema * multKC // SqzON | SqzOFF | noSqz sqzOn = lowerBB > lowerKC and upperBB < upperKC sqzOff = lowerBB < lowerKC and upperBB > upperKC noSqz = sqzOn == false and sqzOff == false // Momentum val = ta.linreg(source - math.avg(math.avg(ta.highest(high, lengthKC), ta.lowest(low, lengthKC)), ta.sma(close, lengthKC)), lengthKC, 0) red_line = ta.sma(val,signalPeriod) blue_line = val // lqm = if val > 0 // if val > nz(val[1]) // long_sqm_custom // if val < nz(val[1]) // short_sqm_custom // Plots //plot(val, style = plot.style_line, title = "blue line", color= color.blue, linewidth=2) //plot(ta.sma(val,SignalPeriod), style = plot.style_line, title = "red line",color = color.red, linewidth=2) //plot(val, color=blue, linewidth=2) //plot(0, color=color.gray, style=plot.style_cross, linewidth=2) //plot(red_line, color=red, linewidth=2) //LOGIC //momentum filter //filterMom = useMomAverage ? math.abs(val) > MomentumMin / 100000 ? true : false : true //} ////SQM Long Short Conditions //Lazy Bear Buy Sell Condition // long_sqm_lazy = (blue_line>red_line) // short_sqm_lazy = (blue_line<red_line) long_sqm_lazy = ta.crossover(blue_line,red_line) short_sqm_lazy = ta.crossunder(blue_line,red_line) //Custom Buy Sell Condition dir_sqm = val < 0 ? -1 : 1 long_sqm_custom = dir_sqm == 1 //and dir_sqm[1] == -1 short_sqm_custom = dir_sqm == -1 //and dir_sqm[1] == 1 long_sqm = strategy_logic == "LazyBear" ? long_sqm_lazy : long_sqm_custom short_sqm = strategy_logic == "LazyBear" ? short_sqm_lazy : short_sqm_custom // Plot Stoploss & Take Profit Levels long_stoploss_price = strategy.position_avg_price * (1 - long_stoploss_value / 100) long_takeprofit_price = strategy.position_avg_price * (1 + long_takeprofit_value / 100) short_stoploss_price = strategy.position_avg_price * (1 + short_stoploss_value / 100) short_takeprofit_price = strategy.position_avg_price * (1 - short_takeprofit_value / 100) plot(enable_long_strategy and not enable_short_strategy ? long_stoploss_percentage : na, color=color.red, style=plot.style_linebr, linewidth=2, title='Long SL Level') plot(enable_long_strategy and not enable_short_strategy ? long_takeprofit_percentage : na, color=color.green, style=plot.style_linebr, linewidth=2, title='Long TP Level') plot(enable_short_strategy and not enable_long_strategy ? short_stoploss_price : na, color=color.red, style=plot.style_linebr, linewidth=2, title='Short SL Level') plot(enable_short_strategy and not enable_long_strategy ? short_takeprofit_price : na, color=color.green, style=plot.style_linebr, linewidth=2, title='Short TP Level') // Long Strategy if long_sqm and enable_long_strategy == true strategy.entry('Long', strategy.long) strategy.exit('Long SL/TP', from_entry='Long', loss=long_stoploss_percentage, profit=long_takeprofit_percentage) strategy.close('Long', comment = "L. CL") // Short Strategy if short_sqm and enable_short_strategy == true strategy.entry('Short', strategy.short) strategy.exit('Short SL/TP', from_entry='Short', loss=short_stoploss_percentage, profit=short_takeprofit_percentage) strategy.close('Short', comment = "S.Cl") plot_sqm_long = long_sqm and not long_sqm[1] plot_sqm_short = short_sqm and not short_sqm[1] plotshape(plot_sqm_long and show_labels_sqm, title='Buy', style=shape.labelup, location=location.belowbar, size=size.normal, text='Buy', textcolor=color.new(color.white, 0), color=color.new(color.green, 0)) plotshape(plot_sqm_short and show_labels_sqm, title='Sell', style=shape.labeldown, location=location.abovebar, size=size.normal, text='Sell', textcolor=color.new(color.white, 0), color=color.new(color.red, 0)) // Date Range EXIT if (not isPeriod) strategy.cancel_all() strategy.close_all()template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6