Momentum Breakout Trading Strategy

Author: ChaoZhang, Date: 2023-09-18 21:28:22
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The strategy uses the momentum indicator Brin's Belt to break the trade, mainly to determine whether the price breaks out of the Brin's Belt and sends a buy/sell signal.

The Principle

The strategy is primarily based on the trend direction of the Brin-Band indicator. The Brin-Band is a band-like region composed of a moving average and its standard deviation. The Brin-Band median is the n-day moving average, the uptrend is the median +2 times the standard deviation, and the downtrend is the median +2 times the standard deviation.

Specifically, the strategy first calculates the highest price, the lowest price, and the intermediate price in n days ((((highest price + lowest price) / 2)); then calculates the closing price and the weighted moving average of the distance between the middle price and the middle price, which forms the center line of the Braille belt, and adds the double standard deviation on the center line to the bottom to form the upper trajectory.

If the closing price breaks out of the trajectory, it indicates an uptrend; if it breaks out of the trajectory, it indicates a downtrend.

In addition, the strategy also introduces a reverse open position mechanism. When the price breaks out of the Boolean band, a counter-market operation is taken to empty if the MACD is down.

The advantages

  1. The use of the Brainstorming belt to determine the direction of the trend has a certain trend tracking ability.

  2. In addition, the reverse-opening design can be used to make a profit against the trend.

  3. Parameters such as Blink cycle, standard deviation coefficient, etc. can be customized to suit different cycles of transactions.

  4. It can close reverse openings, reducing risk.

Risks and countermeasures

  1. Brainstorming bands are often used for highly volatile stocks and may not be suitable for varieties such as cycle-long resources or indices.

  2. Breakout signals can cause false breakouts. Other factors can filter the signal.

  3. Reverse openings may further widen the loss. Reverse openings can be closed.

  4. Withdrawals may be larger. Position sizes can be adjusted accordingly.

Optimized directions

  1. Consider including trend filtering to avoid market turmoil in an uncertain direction.

  2. Test the standard deviation of the Blink band to find a more suitable parameter.

  3. In addition, a stop-loss strategy can be introduced to control single loss.

  4. Optimizing the opening and raising logic to make trading signals clearer.

Summary

This strategy is based on the Brin indicator to determine the price trend breakout. The basic trend tracking strategy can be implemented using simple parameter settings. However, there is a certain false breakout risk, which needs to be filtered with other indicators. The parameter setting, stop-loss strategy, etc. can be further optimized to control the risk.

Overview

This strategy uses Bollinger Bands momentum indicator for breakout trading, mainly judging if price breaks through the upper or lower Bollinger Bands for trading signals.

Principles

The strategy is primarily based on Bollinger Bands indicator to determine trend direction. Bollinger Bands consist of a middle band based on a moving average and upper/lower bands defined by standard deviations. The middle band is a n-period moving average, the upper band is middle band + 2 standard deviations, and the lower band is middle band - 2 standard deviations. When price approaches the upper band it indicates overbought conditions, and when it approaches the lower band it signals oversold conditions.

Specifically, the strategy first calculates the highest high and lowest low over last n periods, and the middle price ((highest high + lowest low)/2). It then calculates the distance between close price and middle price, uses exponential moving average of the distance to form the middle band, and adds/subtracts 2 times standard deviation above and below to form the upper and lower bands.

When close price breaks through the upper band, it signals an uptrend; when it breaks the lower band, it signals a downtrend. The strategy goes long when the upper band is broken, and goes short when the lower band is broken.

In addition, the strategy incorporates a counter-trend mechanism. When price breaks the upper band but MACD is falling, it will take a counter-trend short position.

Advantages

  1. Using Bollinger Bands to determine trend direction provides certain trend following capability.

  2. Counter-trend design allows profiting from reversals.

  3. Customizable parameters like period and standard deviation multiples make it adaptable to different trading horizons.

  4. Disable counter-trend trading to reduce risk.

Risks and Mitigations

  1. Bollinger Bands work best for high volatility stocks, may not be suitable for stable commodities or indices. Can test different period parameters.

  2. Breakout signals may have false breakouts. Can add filters with other indicators.

  3. Counter-trend trading can further increase losses. Can disable counter-trend module.

  4. Drawdowns may be significant. Can adjust position sizing.

Enhancement Opportunities

  1. Consider adding trend filter to avoid whipsaw in non-directional markets.

  2. Test different standard deviation multiples to find optimal parameters.

  3. Incorporate stop loss to control single trade loss.

  4. Optimize entry and add-on logic for clearer trading signals.

Summary

The strategy uses Bollinger Bands as the primary indicator and trades based on trend breakouts. With simple parameters it provides basic trend following capabilities. But false breakout risks exist, requiring additional filters. Parameters, stop loss and risk controls can be enhanced. Overall it serves as a reasonable baseline breakout strategy.


/*backtest
start: 2023-08-18 00:00:00
end: 2023-09-17 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Noro
//2018

//@version=2
strategy("Noro's Bands Scalper Strategy v1.6", shorttitle = "Scalper str 1.6", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100.0, pyramiding = 0)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
takepercent = input(0, defval = 0, minval = 0, maxval = 1000, title = "take, %")
needbe = input(true, defval = true, title = "Bands Entry")
needct = input(false, defval = false, title = "Counter-trend entry")
bodylen = input(10, defval = 10, minval = 0, maxval = 50, title = "Body length")
trb = input(1, defval = 1, minval = 1, maxval = 5, title = "Trend bars")
len = input(20, defval = 20, minval = 2, maxval = 200, title = "Period")
needbb = input(true, defval = true, title = "Show Bands")
needbg = input(true, defval = true, title = "Show Background")
fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
src = close

//PriceChannel 1
lasthigh = highest(src, len)
lastlow = lowest(src, len)
center = (lasthigh + lastlow) / 2

//Distance
dist = abs(src - center)
distsma = sma(dist, len)
hd = center + distsma
ld = center - distsma
hd2 = center + distsma * 2
ld2 = center - distsma * 2

//Trend
chd = close > hd
cld = close < ld
uptrend = trb == 1 and chd ? 1 : trb == 2 and chd and chd[1] ? 1 : trb == 3 and chd and chd[1] and chd[2] ? 1 : trb == 4 and chd and chd[1] and chd[2] and chd[3] ? 1 : trb == 5 and chd and chd[1] and chd[2] and chd[3] and chd[4] ? 1 : 0
dntrend = trb == 1 and cld ? 1 : trb == 2 and cld and cld[1] ? 1 : trb == 3 and cld and cld[1] and cld[2] ? 1 : trb == 4 and cld and cld[1] and cld[2] and cld[3] ? 1 : trb == 5 and cld and cld[1] and cld[2] and cld[3] and cld[4] ? 1 : 0
trend = dntrend == 1 and high < center ? -1 : uptrend == 1 and low > center ? 1 : trend[1]

//trend = close < ld and high < center ? -1 : close > hd and low > center ? 1 : trend[1]

//Lines
colo = needbb == false ? na : black
plot(hd2, color = colo, linewidth = 1, transp = 0, title = "High band 2")
plot(hd, color = colo, linewidth = 1, transp = 0, title = "High band 1")
plot(center, color = colo, linewidth = 1, transp = 0, title = "center")
plot(ld, color = colo, linewidth = 1, transp = 0, title = "Low band 1")
plot(ld2, color = colo, linewidth = 1, transp = 0, title = "Low band 2")

//Background
col = needbg == false ? na : trend == 1 ? lime : red
bgcolor(col, transp = 80)

//Body
body = abs(close - open)
smabody = ema(body, 30) / 10 * bodylen

//Signals
bar = close > open ? 1 : close < open ? -1 : 0
up7 = trend == 1 and ((bar == -1 and bar[1] == -1) or (body > smabody and bar == -1)) ? 1 : 0
dn7 = trend == 1 and ((bar == 1 and bar[1] == 1) or (close > hd and needbe == true)) and close > strategy.position_avg_price * (100 + takepercent) / 100 ? 1 : 0
up8 = trend == -1 and ((bar == -1 and bar[1] == -1) or (close < ld2 and needbe == true)) and close < strategy.position_avg_price * (100 - takepercent) / 100 ? 1 : 0
dn8 = trend == -1 and ((bar == 1 and bar[1] == 1) or (body > smabody and bar == 1)) ? 1 : 0

if up7 == 1 or up8 == 1 
    strategy.entry("Long", strategy.long, needlong == false ? 0 : trend == -1 and needct == false ? 0 : na, when=(time > timestamp(fromyear, frommonth, 01, 00, 00) and time < timestamp(toyear, tomonth, 31, 00, 00)))

if dn7 == 1 or dn8 == 1
    strategy.entry("Short", strategy.short, needshort == false ? 0 : trend == 1 and needct == false ? 0 : na, when=(time > timestamp(fromyear, frommonth, 01, 00, 00) and time < timestamp(toyear, tomonth, 31, 00, 00)))
    
if time > timestamp(toyear, tomonth, 31, 00, 00)
    strategy.close_all()

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