Cross Limit Order Cross Period Trading Strategy

This strategy is a trend following trading strategy that uses simple moving average to determine market trend direction and place limit orders along the moving average line to follow the trend. 1. Calculate the…

Pine ScriptTrend following Volatility SMA

Author: ChaoZhang
Complexity: Intermediate · 63 lines
Parameters: 16
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

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Summary

This strategy is a trend following trading strategy that uses simple moving average to determine market trend direction and place limit orders along the moving average line to follow the trend.

Strategy Logic

Calculate the Simple Moving Average (SMA) and the trend direction trend.
If Anti-Saw filter is enabled, uptrend is identified when lows are above SMA, downtrend is identified when highs are below SMA. If Anti-Saw filter is disabled, uptrend is identified when close is above SMA, downtrend is identified when close is below SMA.
Place limit orders at SMA price according to the trend direction trend and enabled trading directions needlong and needshort:
- If long trade is needed (needlong is true) and in uptrend, place long limit order at SMA price
- If short trade is needed (needshort is true) and in downtrend, place short limit order at SMA price
Set stop loss logic to exit positions if position direction does not match trend direction.
Only trade within specified date range based on date range parameters.

Advantage Analysis

Using SMA to determine trend can effectively filter market noise and lock in longer term trend.
Placing limit orders at SMA price can get good entry points when trend starts.
Flexibility to only go long or short according to personal trading style.
Stop loss in place to avoid enlarging losses.
Trading time range sets to avoid volatility around major events.

Risk Analysis

SMA as trend indicator has lagging effect, may miss trend turning points and cause losses.
Limit orders lack flexibility, may not get into positions due to short term trend adjustments.
SMA period parameter needs proper configuration, improper settings lead to wrong trend determination.
Trading session parameters need to be reasonable to avoid missing opportunities or trading in risky periods.

Optimization Directions

Consider adding other indicators for multi-indicator confirmation, avoiding SMA lagging issues.
Switch to market order trailing when price breaks SMA, improving tracking flexibility.
Dynamically optimize SMA period to adapt to different market cycles.
Set stop loss to swing low/high instead of strictly at SMA price for more flexible stops.
Increase algorithmic elements for smarter dynamic trading sessions avoiding major risk events.

Summary

Overall this is a relatively simple trend following strategy, with the core idea of determining trend direction with SMA and placing limit orders at SMA price to follow the trend. With certain optimizations it can improve flexibility, adaptability and intelligence. The strategy is easy to understand and implement, suitable for algorithmic trading beginners, but requires risk awareness, cautious backtest evaluation, strict monitoring and optimization for live trading.

Parameters

Name	Default	What it controls
v_input_1	true	long
v_input_2	true	short
v_input_3	100	Lot, %
v_input_4_close	0	MA Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_5	5	SMA length
v_input_6	false	SMA offset
v_input_7	true	Anti-saw filter
v_input_8	false	Reverse
v_input_9	true	Show MA
v_input_10	false	Show background
v_input_11	1900	From Year
v_input_12	2100	To Year
v_input_13	true	From Month
v_input_14	12	To Month
v_input_15	true	From day
v_input_16	31	To day

Source Pine Script

/*backtest
start: 2022-10-27 00:00:00
end: 2023-03-12 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Noro
//2020

//@version=4
strategy(title = "Noro's CrossLimit", shorttitle = "CrossLimit", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100.0, pyramiding = 0, commission_value = 0.0)

needlong = input(true, "long")
needshort = input(true, "short")
lotsize = input(100, defval = 100, minval = 1, maxval = 10000, title = "Lot, %")
src = input(close, defval = close, title = "MA Source")
len = input(5, defval = 5, minval = 1, title = "SMA length")
off = input(0, defval = 0, minval = 0, title = "SMA offset")
anti = input(true, defval = true, title = "Anti-saw filter")
rev = input(false, defval = false, title = "Reverse")
showma = input(true, defval = true, title = "Show MA")
showbg = input(false, defval = false, 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")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

//MA
ma = sma(src, len)[off]
macol = showma ? color.blue : na
plot(ma, color = macol, linewidth = 3, transp = 0)

//Background
trend = 0
trend := anti == false and close > ma ? 1 : anti == false and close < ma ? -1 : low > ma ? 1 : high < ma ? -1 : trend[1]
bgcol = showbg ? trend == 1 ? color.lime : trend == -1 ? color.red : na : na
bgcolor(bgcol, transp = 70)

//Signals
bar = close > open ? 1 : close < open ? -1 : 0
up = (trend == 1 and rev == false) or (trend == -1 and rev == true)
dn = (trend == -1 and rev == false) or (trend == 1 and rev == true)

//Trading
size = strategy.position_size
truetime = time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)
lot = 0.0
lot := size != size[1] ? strategy.equity / close * lotsize / 100 : lot[1]
if trend != 0
    strategy.entry("Long", strategy.long, lot, limit = ma, when = needlong and truetime and up)
    strategy.entry("Short", strategy.short, lot, limit = ma, when = needshort and truetime and dn)
if size > 0 and needshort == false and trend == -1
    strategy.exit("Stop Long", "Long", limit = ma)
if size < 0 and needlong == false and trend == 1
    strategy.exit("Stop Short", "Short", limit = ma)
if time > timestamp(toyear, tomonth, today, 23, 59)
    strategy.close_all()
    strategy.cancel("Long")
    strategy.cancel("Short")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-03. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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Summary

Strategy Logic

Advantage Analysis

Risk Analysis

Optimization Directions

Summary

Parameters

Source Pine Script

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