Hull MA crossover strategy with SMA filter

Hull Moving Average (HMA) strategies are algorithmic trading methods that use this type of moving average to identify market trends, entry and exit signals, and potential trend reversals. The main goal of these strategies is to capture the fastest and smoothest market movements while minimizing the lag typical of traditional moving averages.

Unlike classic moving averages, HMAs respond more quickly to price changes, making the strategy particularly suitable for volatile markets or markets with strong, established trends. HMA-based strategies can be applied to a variety of assets, from major stock markets to cryptocurrencies, and across different timeframes, depending on the desired trading style (intraday, swing, or multi-day).

The Hull Moving Average (HMA) is a moving average developed by Alan Hull to reduce the lag typical of traditional moving averages while maintaining a smoother line compared to a simple moving average. The HMA combines weighted moving averages (WMA) and the square root of the period to achieve higher responsiveness, allowing traders to follow trends more quickly and accurately.

The general formula for the HMA is:

1. Calculate a WMA using half of the chosen period.

2. Subtract the WMA over the full original period from the half-period WMA and multiply the result by 2.

3. Apply a final WMA over the square root of the chosen period.

The result is a smooth and responsive moving average, capable of highlighting trends in real time and reducing false signals caused by minor price fluctuations.

ENTRY SIGNAL

The long entry signal is triggered when the faster Hull Moving Average (H_L1) crosses above the slower Hull Moving Average (H_L4). This crossover indicates a shift in bullish momentum: the more responsive HMA detects that the price is starting to move faster than the recent trend, signaling the potential start of a positive trend.

To increase the probability of success and reduce false signals caused by short-term fluctuations, the signal is filtered using a long-term SMA (SMA 500). The filter ensures that the order is executed only if the previous candle’s closing price is above the SMA(500), confirming that the market is in a well-established uptrend. In practice, this filter removes trades during sideways or bearish market conditions, allowing entries only when the likelihood of trend continuation is higher.

The signal is defined in Tradescript as follows:

SET H_L1 = REF( WMA( (WMA(CLOSE, 16) * 2) - WMA(CLOSE, 32), 6 ), 1 )

SET H_L4 = REF( WMA( (WMA(CLOSE, 16) * 2) - WMA(CLOSE, 32), 6 ), 4 )

SET C_L1 = REF(CLOSE, 1)

SET S_L1 = REF(SMA(CLOSE, 500), 1)

CROSSOVER(H_L1, H_L4) == TRUE AND

C_L1 > S_L1

This approach combines the speed and responsiveness of the Hull Moving Averages with the stability of the long-term trend, creating a long signal that enters the market only when bullish conditions are confirmed, thereby reducing exposure to false breakouts.

EXIT SIGNAL

The long exit signal is triggered when the slower Hull Moving Average (H_L4_EXIT) crosses below the faster Hull Moving Average (H_L1_EXIT). This crossover indicates a potential weakening of bullish momentum and the beginning of a possible trend reversal. In other words, it signals that the price may stop rising rapidly and that the likelihood of the positive trend continuing is decreasing.

This signal helps protect accumulated gains and limit drawdown risk by closing the long position before a more significant reversal can erode capital. Unlike the entry signal, no additional trend filters are necessary here: the HMA crossover alone is sufficient to detect a meaningful change in momentum.

In Tradescript, the exit signal is defined as follows:

SET H_L1_EXIT = REF( WMA( (WMA(CLOSE, 16) * 2) - WMA(CLOSE, 32), 6 ), 1 )

SET H_L4_EXIT = REF( WMA( (WMA(CLOSE, 16) * 2) - WMA(CLOSE, 32), 6 ), 4 )

CROSSOVER(H_L4_EXIT, H_L1_EXIT) == TRUE

This approach ensures that the strategy automatically closes positions during periods of potential trend weakness, maximizing capital protection and allowing for a structured and timely exit, while minimizing the impact of false signals or short-term fluctuations.

ORDER SIZING AND POSITION PROTECTION

The money management approach of this strategy depends heavily on the chosen asset, its price, and the initial capital allocated to the strategy. In this case, the strategy was tested and optimized on Ethereum/Euro (ETH/EUR) using 1-hour candles from 01/01/2025 to 19/09/2025, assuming an initial backtest capital of €10,000.

The entry signal generates a buy order of 4.2 ETH, while the exit signal generates a sell order of 4.2 ETH. Additionally, a long exposure limit of 4.2 ETH has been set, equal to the order size. This means the strategy is not allowed to open multiple positions simultaneously, and partial exits are not permitted: when the exit signal triggers, it closes the entire position.

To protect the position, each buy order is accompanied by a stop loss of the same quantity, set at a price 5% below the order placement price.

IDEAL MARKETS FOR THE STRATEGY

This strategy is particularly suited for high-volatility crypto markets, such as Bitcoin and Ethereum, where rapid swings provide significant profit opportunities. It performs best in uptrending markets with decisive movements and tends to lose effectiveness during bearish or sideways phases.

Thanks to its design, the strategy is suitable both for traders who want to monitor multiple assets simultaneously and for those seeking an automated approach that minimizes time spent in front of charts while maximizing the capital’s performance during positive trends.

BACKTEST SETTINGS

The strategy was tested on ETH/EUR using 1-hour candles from 01/01/2025 to 19/09/2025. The entry and exit signals, order sizing, and exposure limits were set as described in the previous sections. The initial capital for the backtest was €10,000, with fees set at 0.1% per order and no leverage applied (Margin Required 100%). The spread was neglected due to the high liquidity of Ethereum.