EMA, Hull and RSI Opportunity Tracking Strategy

Author: ChaoZhang, Date: 2024-01-18 15:46:35



This strategy constructs trading signals based on moving averages, Hull moving averages and the Relative Strength Index (RSI). It belongs to a typical opportunity tracking strategy that can automatically identify market opportunities and switch between long and short positions. It is suitable for medium and short term trading.

Strategy Logic

  1. Calculate the 50-period Exponential Moving Average (EMA) as the indicator for judging the trend.
  2. Calculate the 7-day Hull Moving Average as a more sensitive and leading average indicator, crossing EMA to form golden crosses and dead crosses.
  3. Set the overbought line and oversold line for RSI at 60 and 45 respectively. RSI above 60 is an overbought signal and RSI below 45 is an oversold area.
  4. When overbought happens at the same time as an upwards penetration of EMA, it is a short signal.
  5. When oversold happens at the same time as a downwards penetration of EMA, it is a long signal.

Advantages of the Strategy

  1. Uses a combination of EMA, Hull and RSI to comprehensively judge market trends, momentum and overbought/oversold areas, improving signal accuracy.
  2. EMA judges mid-to-long term trends, Hull leads shorter term moves, RSI identifies overbought/oversold levels. Different period indicators working together capture trading opportunities across timeframes.
  3. Entry signals must meet criteria for trend, momentum and overbought/oversold zones simultaneously to trigger, effectively filtering false signals.

Risks of the Strategy

  1. Only using 3 indicators may miss some trading opportunities.
  2. EMA and Hull periods need continual testing and optimization, improper parameter selections can impact signal quality.
  3. RSI parameters also need to be adjusted for different equities and currencies which may have different overbought/oversold standards.

Enhancement Areas

  1. More auxiliary indicators can be introduced, e.g. Bollinger Bands, KC Lines etc to create multi-resonance decision making.
  2. Parameters can be optimized for different products.
  3. Higher timeframe analysis can be incorporated to avoid being misled by short term fakeouts.
  4. Stop loss strategies can be implemented to manage risk.


This strategy uses the combination of EMA, Hull and RSI across timeframes to capture medium and short term trading opportunities. Entry signals must meet criteria in trend, momentum and overbought/oversold dimensions simultaneously in order to filter out false signals. The strategy can be further enhanced through parameter optimization and introducing more auxiliary indicators to improve stability and trading performance.

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"}]

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Bitduke

strategy(shorttitle="EHR", title="Simple EMA_Hull_RSI", overlay=false, 
     calc_on_every_tick=false, pyramiding=0, default_qty_type=strategy.cash, 
     default_qty_value=1000, currency=currency.USD, initial_capital=1000,
     commission_type=strategy.commission.percent, commission_value=0.075)

// EMA
len = input(minval=1, title="EMA Length", defval=50)
src = input(close, title="EMA Source")
final_ema = ema(src, len)
plot(final_ema, color=color.red, title="EMA")

overbought = input(60, title="overbought value")
oversold = input(45, title="oversold value")

overbought_signal = rsi(close, 14) > overbought
oversold_signal = rsi(close, 14) < oversold
barcolor(overbought_signal ? color.black : na)
barcolor(oversold_signal ? color.blue : na)
// Hull MA
n = input(title="Hull Length", defval=7)



// Strategy Logic
longCondition =  overbought_signal and crossover(n1,final_ema) 
shortCondition = oversold_signal and crossover(final_ema,n1) 

strategy.entry("EHR_Long", strategy.long, when=longCondition)
strategy.entry("EHR_Short", strategy.short, when=shortCondition)