NoroBands Momentum Position Strategy

This strategy combines Noro's bands theory with quantitative techniques to form a momentum breakout strategy. It generates trading signals by calculating moving averages, RSI, bands, color bars and other indicators…

Pine ScriptMomentum Machine learning Breakout RSI SMA ATR

Author: ChaoZhang
Complexity: Intermediate · 93 lines
Parameters: 12
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

Calculate upper and lower bands using average true range. Price breaking through upper band indicates long signal while breaking lower band gives short signal.
Use RSI indicator to determine overbought and oversold zones. RSI below 30 suggests long while above 70 suggests short.
Breaking max and min prices shows price momentum direction.
Color bars indicate bullish or bearish markets. Green means bull market for long while red means bear market for short.
Combine moving average to identify divergence for trade signals.

Advantages

Multiple indicators combination improves accuracy.
Combining bands theory and quantitative techniques makes the strategy more effective.
Blending momentum breakout and mean reversion trading expands profit room.
High extensibility to adjust parameters according to markets.

Risks

Parameters need constant optimization and testing.
Fails to respond timely to long-short switches, causing losses probably.
High trading frequency, affected easily by fees and slippage.
Parameters should be adjusted timely to suit different cycles.

Optimization

Multi-timeframe validation to find best parameter combination.
Add stop loss to reduce single loss.
Larger position management to improve profit efficiency.
Combine deep learning for auto parameter optimization.

Summary

This strategy combines typical quantitative indicators to achieve effective profit through momentum and mean reversion indicators. It also uses average true range theory to locate reasonable entry points. A good example of combining theory and techniques. With parameters optimization and risk control improvement, it will become a efficient and stable quantitative strategy.

Parameters

Name	Default	What it controls
v_input_1	true	Long
v_input_2	true	Short
v_input_3	20	Period
v_input_4	true	Use ColorBar
v_input_5	true	Use CryptoBottom
v_input_6	true	Use RSI
v_input_7	true	Use min/max
v_input_8	true	Use pyramiding
v_input_9	false	Show Bands
v_input_10	false	Show Background
v_input_11	false	Show Locomotive
v_input_12	false	Show Avg.price line

Source Pine Script

/*backtest
start: 2023-01-11 00:00:00
end: 2024-01-17 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/


//@version=2
strategy("Noro's Bands Strategy v1.5", shorttitle = "NoroBands str 1.5", overlay=true)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
len = input(20, defval = 20, minval = 2, maxval = 200, title = "Period")
color = input(true, defval = true, title = "Use ColorBar")
usecb = input(true, defval = true, title = "Use CryptoBottom")
usersi = input(true, defval = true, title = "Use RSI")
usemm = input(true, defval = true, title = "Use min/max")
usepyr = input(true, defval = true, title = "Use pyramiding")
needbb = input(false, defval = false, title = "Show Bands")
needbg = input(false, defval = false, title = "Show Background")
needlo = input(false, defval = false, title = "Show Locomotive")
needpy = input(false, defval = false, title = "Show Avg.price line")
src = close

//Fast RSI
fastup = rma(max(change(src), 0), 2)
fastdown = rma(-min(change(src), 0), 2)
fastrsi = fastdown == 0 ? 100 : fastup == 0 ? 0 : 100 - (100 / (1 + fastup / fastdown))

//CryptoBottom
mac = sma(close, 10)
lencb = abs(close - mac)
sma = sma(lencb, 100)
max = max(open, close)
min = min(open, close)

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

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

//Trend
trend = close < ld and high < hd ? -1 : close > hd and low > ld ? 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")
plot(center, color = colo, linewidth = 1, transp = 0, title = "center")
plot(ld, color = colo, linewidth = 1, transp = 0, title = "Low band")
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)

//Signals
up = trend == 1 and ((close < open or color == false) or close < hd) and (min < min[1] or usemm == false) and (close < strategy.position_avg_price or usepyr == false or strategy.position_size <= 0) ? 1 : 0
dn = trend == -1 and ((close > open or color == false) or close > ld) and (max > max[1] or usemm == false) and (close > strategy.position_avg_price or usepyr == false or strategy.position_size >= 0) ? 1 : 0 
up2 = close < open and lencb > sma * 3 and min < min[1] and fastrsi < 10 and (close < strategy.position_avg_price or usepyr == false or strategy.position_size <= 0) ? 1 : 0 //CryptoBottom
//dn2 = close > open and len > sma * 3 and max > max[1] and fastrsi > 90 ? 1 : 0 //CryptoBottom
up3 = fastrsi < 5 and usersi == true and (close < strategy.position_avg_price or usepyr == false or strategy.position_size <= 0) ? 1 : 0
//dn3 = fastrsi > 95 and usersi = true ? 1 : 0

//Avg Price
colpy = needpy == false ? na : black
plot(strategy.position_avg_price, color = colpy)

up4 = close < strategy.position_avg_price and usepyr == true and strategy.position_size >= 0 ? 1 : 0 
dn4 = close > strategy.position_avg_price and usepyr == true and strategy.position_size <= 0 ? 1 : 0 

//Locomotive
uploco = trend == 1 and close < open and min < min[1] and close < center ? 1 : 0
plotarrow(needlo == true and uploco == 1 ? 1 : 0, colorup = black, colordown = black, transp = 0)

longCondition = up == 1 or (up2 == 1 and usecb == true) or (up3 == 1 and usersi == true) or up4 == 1
if (longCondition)
    strategy.entry("Long", strategy.long, needlong == false ? 0 : na)

shortCondition = dn == 1 or dn4 == 1
if (shortCondition)
    strategy.entry("Short", strategy.short, needshort == false ? 0 : na)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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