The Hawk Eye short-term trading strategy is a short-term trading strategy that combines multiple technical indicators. The strategy uses indicators like moving averages, MACD, RSI, Stoch, and VWMA to construct trading signals and make short-term trades within a 1-hour timeframe.
The strategy first calculates the fast moving average (21 periods) and slow moving average (55 periods). When the fast MA crosses above the slow MA, and MACD turns from negative to positive, a buy signal is generated. When the fast MA crosses below the slow MA, and MACD turns from positive to negative, a sell signal is generated. In addition, the strategy also incorporates the RSI indicator to filter signals. Buy signals are only generated when RSI is low and turning up. Sell signals are only generated when RSI is high and turning down. Finally, the strategy also utilizes VWMA to compare the positions of the fast and slow moving averages to further confirm the trend.
Specifically, when MACD turns from negative to positive, the fast MA crosses above the slow MA, and 50-period VWMA is below 200-period VWMA, a buy signal is generated. When MACD turns from positive to negative, the fast MA crosses below the slow MA, and 50-period VWMA is above 200-period VWMA, a sell signal is generated. The strategy buys when the fast Stoch is above the slow Stoch, and sells when the fast Stoch is below the slow Stoch.
The biggest advantage of this strategy is the combination of multiple indicators to filter signals, which can effectively reduce the probability of wrong trades. MACD determines trend direction, VWMA judges major trend location, Stoch filters overbought/oversold zones, and RSI avoids overshoot areas. The combination of multiple indicators makes trading signals more reliable. The use of multiple indicators ensures signal quality while controlling excessive trading.
In addition, short-term trading within the 1-hour timeframe can capture short-term opportunities in the market and achieve higher profits. Compared to long-term trading, short-term trading has a higher win rate.
The biggest risk of this strategy is that the combination of multiple indicators may be too complex. Improper parameter settings can lead to poor strategy performance. Extensive backtesting and optimization is needed to ensure good results.
In addition, short-term trading has higher trading frequency. Excessively frequent trading not only increases transaction costs but also increases operational risks. Failure to monitor the market continuously may result in missed entries and exits.
Finally, the combination of multiple indicators increases the risk of curve fitting. The optimization process may lead to overfitting issues and poor performance in live trading.
The strategy can be optimized in the following aspects:
Optimize indicator parameters to find the best parameter combination.
Add stop loss strategies to reduce single trade loss.
Optimize entry conditions to improve accuracy in judging trends.
Incorporate position sizing to optimize capital usage efficiency.
Test the effectiveness across different products and contracts.
Add machine learning algorithms that utilize historical data for training and reduce overfitting risks.
The Hawk Eye short-term trading strategy combines multiple indicators to construct trading signals and makes short-term trades within the 1-hour timeframe. The advantages of this strategy are reliable indicator combinations and high win rate. But there are also risks like difficulty in parameter optimization and high trading frequency. Overall, this strategy has great optimization potential. With proper parameter tuning, the performance can be very impressive. Through continuous optimization and testing, this strategy can become a very practical tool for short-term trading.
/*backtest
start: 2022-09-15 00:00:00
end: 2023-09-21 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=3
strategy("Hawk 1H Strategy", overlay=true)
fastLength = input(21)
slowlength = input(55)
MACDLength = input(8)
smallEMA = ema(close, fastLength)
largeEMA = ema(close, slowlength)
MACD = smallEMA - largeEMA
aMACD = ema(MACD, MACDLength)
delta = MACD - aMACD
smoothK = input(5, minval=1)
smoothD = input(5, minval=1)
lengthRSI = input(8, minval=1)
lengthStoch = input(21, minval=1)
src = input(close, title="RSI Source")
vFast = stoch(close, high, low, 8)
vSlow = sma(vFast, 5)
rsi1 = rsi(src, lengthRSI)
k = sma(stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = sma(k, smoothD)
fiftyVWMA = vwma(close, 55)
twohunVWMA = vwma(close,144)
if (MACD > MACD[1]) and (MACD[1] > MACD[2]) and (fiftyVWMA < twohunVWMA)
if (vFast > vSlow) and (k < 30) //and (vSlow < 40)
strategy.entry("MacdLE", strategy.long, comment='Buy')
if (MACD < MACD[1]) and (MACD[1] < MACD[2]) and (fiftyVWMA > twohunVWMA)
if (vFast < vSlow) and (k > 70)//and (vSlow > 60)//and (rsi1 > 60)
strategy.entry("MacdSE", strategy.short, comment='Sell')
//plot(strategy.equity, title="equity", color=red, linewidth=2, style=areabr)