ChaoZhang
Overview
This strategy uses the Relative Strength Index (RSI) indicator to determine overbought and oversold levels for shorts and longs. It is a typical RSI reversal trading strategy. The strategy also incorporates parameter optimization, stop losses etc. to adapt to different market conditions.
Strategy Logic
The core logic includes:
- Calculating the RSI value
- Setting RSI upper and lower limits
- Going short when RSI crosses above upper limit
- Going long when RSI crosses below lower limit
- Setting take profit and stop loss levels
- Exiting positions when RSI reverses or take profit/stop loss is hit
The RSI indicator shows overbought above 70 and oversold below 30 market conditions. The strategy utilizes this classic logic to determine long/short entries based on RSI value against preset limits. Customizable parameters also allow optimizing limits, stop loss etc. for market adaptation.
Advantages
- RSI effectively identifies overbought/oversold market states
- RSI has sound theoretical basis
- Customizable parameters adapt across instruments and conditions
- Incorporated take profit/stop loss controls risk
Risks and Mitigation
- Potential for false RSI signals leading to losses
- Require continuous optimization of RSI levels
- Stops can be hit frequently during choppy price action
Mitigations:
- Additional factors to confirm signals and avoid false ones
- Optimize RSI levels based on instrument characteristics
- Adjust stop loss placement to reduce whipsaw risks
Enhancement Opportunities
The strategy can be enhanced through:
Machine learning for auto RSI level optimization
Volume confirmation to avoid false breakouts
Additional factors like moving averages for multi-factor confirmation
Adaptive stops based on market volatility
Volume analysis for gauging fund inflows/outflows
Combining with non-correlated strategies to lower portfolio drawdown
Conclusion
This is a simple and practical mean reversion strategy using RSI for overbought/oversold detection. Customizable parameters allow adaptation to changing markets. Enhancements like adaptive stops, multi-factor confirmation, and parameter optimization can make the strategy more robust.
Strategy source code
/*backtest
start: 2023-08-19 00:00:00
end: 2023-09-18 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=3
strategy("4All V3", shorttitle="Strategy", overlay=true)
/////////////// Component Code Start ///////////////
testStartYear = input(2011, "Backtest Start Year")
testStartMonth = input(8, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,0,0)
testStopYear = input(2018, "Backtest Stop Year")
testStopMonth = input(9, "Backtest Stop Month")
testStopDay = input(29, "Backtest Stop Day")
// testStopDay = testStartDay + 1
testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay,0,0)
// A switch to control background coloring of the test period
testPeriodBackground = input(title="Color Background?", type=bool, defval=true)
testPeriodBackgroundColor = testPeriodBackground and (time >= testPeriodStart) and (time <= testPeriodStop) ? #00FF00 : na
bgcolor(testPeriodBackgroundColor, transp=97)
testPeriod() => true
/////////////// Component Code Stop ///////////////
src = close
len = input(4, minval=1, title="Length")
up = rma(max(change(src), 0), len)
down = rma(-min(change(src), 0), len)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
rsin = input(5)
sn = 100 - rsin
ln = 0 + rsin
/////////////// STRATEGY ///////////////
ts = input(99999, "Trailing Stop") / 10000
tp = input(15, "Take Profit") / 10000
sl = input(23, "Stop Loss") / 10000
pyr = input(1, "Pyramiding")
short = crossover(rsi, sn)
long = crossunder(rsi, ln)
totalLongs = 0
totalLongs := nz(totalLongs[1])
totalShorts = 0
totalShorts := nz(totalShorts[1])
totalLongsPrice = 0
totalLongsPrice := nz(totalLongsPrice[1])
totalShortsPrice = 0
totalShortsPrice := nz(totalShortsPrice[1])
sectionLongs = 0
sectionLongs := nz(sectionLongs[1])
sectionShorts = 0
sectionShorts := nz(sectionShorts[1])
if long
sectionLongs := sectionLongs + 1
sectionShorts := 0
if short
sectionLongs := 0
sectionShorts := sectionShorts + 1
longCondition = long and sectionLongs >= pyr
shortCondition = short and sectionShorts >= pyr
last_long = na
last_short = na
last_long := longCondition ? time : nz(last_long[1])
last_short := shortCondition ? time : nz(last_short[1])
long_signal = crossover(last_long, last_short)
short_signal = crossover(last_short, last_long)
last_open_long_signal = na
last_open_short_signal = na
last_open_long_signal := long_signal ? open : nz(last_open_long_signal[1])
last_open_short_signal := short_signal ? open : nz(last_open_short_signal[1])
last_long_signal = na
last_short_signal = na
last_long_signal := long_signal ? time : nz(last_long_signal[1])
last_short_signal := short_signal ? time : nz(last_short_signal[1])
in_long_signal = last_long_signal > last_short_signal
in_short_signal = last_short_signal > last_long_signal
last_high = na
last_low = na
last_high := not in_long_signal ? na : in_long_signal and (na(last_high[1]) or high > nz(last_high[1])) ? high : nz(last_high[1])
last_low := not in_short_signal ? na : in_short_signal and (na(last_low[1]) or low < nz(last_low[1])) ? low : nz(last_low[1])
long_ts = not na(last_high) and high <= (last_high - ts) //and high >= last_open_long_signal
short_ts = not na(last_low) and low >= (last_low + ts) //and low <= last_open_short_signal
long_tp = high >= (last_open_long_signal + tp)
short_tp = low <= (last_open_short_signal - tp)
long_sl = low <= (last_open_long_signal - sl)
short_sl = high >= (last_open_short_signal + sl)
leverage = input(1, "Leverage")
long_call = last_open_long_signal - (0.8 + 0.2 * (1/leverage)) / leverage * last_open_long_signal
short_call = last_open_short_signal + (0.78 + 0.2 * (1/leverage)) / leverage * last_open_short_signal
long_call_signal = low <= long_call
short_call_signal = high >= short_call
if testPeriod()
strategy.entry("Long", strategy.long, when=longCondition)
strategy.entry("Short", strategy.short, when=shortCondition)
strategy.close("Long", when=long_call_signal)
strategy.close("Short", when=short_call_signal)
strategy.close("Long", when=long_tp)
strategy.close("Short", when=short_tp)
strategy.close("Long", when=long_sl)
strategy.close("Short", when=short_sl)
strategy.close("Long", when=long_ts)
strategy.close("Short", when=short_ts)