This strategy is based on the Simple Moving Average (SMA) and Relative Strength Index (RSI) indicators. It goes short when the RSI crosses above the entry level and the close price is below the SMA; It closes positions when stop loss or take profit signals appear. The double filter helps avoid ineffective trades.
The strategy judges the market mainly based on two indicators:
SMA: Calculated based on the simple moving average of closing prices in the past 200 days, representing mid-long term trends.
RSI: Calculated based on the relative strength of closing prices in the past 14 days, representing short-term overbought/oversold levels.
When RSI crosses above 51 into the overbought zone and is above the SMA line, it indicates that the short-term and mid-long term trends are diverging, so a short position is opened.
After that, stop loss and take profit lines are set. Position is closed when RSI drops below 32 for take profit, or when RSI crosses above 54 or the stop loss is hit for stop loss.
The double filter of indicators increases the accuracy of entry signals. RSI determines short-term overbought levels and SMA determines mid-long term bearish signals, combining the two makes the signals more reliable.
The trailing stop locks in profits according to price action, avoiding giving back profits.
The logic is simple and straightforward, easy to understand and modify.
Does not consider factors like trading volume or volatility.
RSI parameters are fixed and may not suit all products and timeframes.
Does not consider trading costs like slippage and commissions.
The strategy is very simple and has limited room for expansion.
Test and optimize RSI and SMA parameters to find the best combination.
Add more types of stop loss/profit taking methods, like trailing stops, percentage-based stops.
Add trend filter indicators like MACD to avoid trading against the trend.
Consider volume indicators to filter out false breakouts with low volume.
The strategy has clear logic and some practical value. But its parameters are fixed and don’t adapt to market changes. There are also some details that can be improved. Overall, it can serve as an example for beginners to learn double indicator filtering strategies, but needs further testing and enhancement for actual trading.
/*backtest
start: 2023-09-07 00:00:00
end: 2023-10-07 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © abdllhatn
//@version=5
// strategy("Alpha Short SMA and RSI Strategy", overlay=true, initial_capital=10000, default_qty_value=100)
// Inputs
sma_length = input(200, title="SMA Length")
rsi_length = input(14, title="RSI Length")
rsi_entry = input(51, title="RSI Entry Level")
rsi_stop = input(54, title="RSI Stop Level")
rsi_take_profit = input(32, title="RSI Take Profit Level")
// Indicators
sma_value = ta.sma(close, sma_length)
rsi_value = ta.rsi(close, rsi_length)
var float trailingStop = na
var float lastLow = na
// Conditions
shortCondition = ta.crossover(rsi_value, rsi_entry) and close < sma_value
if (shortCondition)
strategy.entry("Sell", strategy.short)
trailingStop := na
lastLow := na
if (strategy.position_size < 0)
if (na(lastLow) or close < lastLow)
lastLow := close
trailingStop := close
if not na(trailingStop) and close > trailingStop
strategy.close("Sell")
if (rsi_value >= rsi_stop)
strategy.close("Sell")
if (rsi_value <= rsi_take_profit)
strategy.close("Sell")
// Plot
plot(sma_value, color=color.red, linewidth=2)