Trading-ethereum using a fast Shepherd's momentum binary signal

Introduction

This blog is the second of a series where I explore using our proprietary Shepherd's momentum (SM) signal to trade a cryptocurrency.

The complete series list is:

• "Trading Bitcoin using a fast Shepherd's Momentum signal",
• this blog, "Trading Ethereum, using a fast Shepherd's momentum binary signal",
• "Trading Ripple (XRP) using a fast Shepherd's Momentum signal",
• and, finally, "Trading Solana using a fast Shepherd's Momentum binary signal",

In this series of blogs I backtest trading Bitcoin, Ethereum, XRP and Solana. I use two different versions of the SM (continuous and binary both with with no short sell allowed) and I also start simulations either from a low price or a peak. The following table shows the backtest classification:

This time I use a binary no shorts version of the Shepherd's momentum to trade Ethereum. As before, I aim to make this blog both accessible to beginners and engaging for experienced investors.

This blog is not an invitation to trade. Also does not intend to provide trading advice. Trading involves risks, and readers are solely responsible for their trading decisions.

The next graph shows Ethereum's price and volume, on a semi-logarithmic scale, since September first, 2015.

Shepherd's momentum on Ethereum

The Shepherd's momentum is a twist on the traditional moving average crossover indicator. The Shepherd's momentum is defined between -1 and 1. A value of 1 means full long and a value of -1 full short. Values in between indicate partial investment in Ethereum and the rest in cash.

The following graph shows the Ethereum price together with the full Shepherd's momentum signal.

Binary Shepherd's momentum and buy and hold performance

I modify SM in two ways:

• First short positions will not not be allowed as I assume that most investors are not able to short sell cryptocurrencies. Consequently if the signal is less than zero, the position will be zero.
• Second, I cover the case where investors either want to be out of the market or fully invested. This means that the signal will only be zero or one. The signal will be 0 if SM less or equal to 0, and 1 if SM is greater than 0 and less or equal to 1.

In summary, the amount of Ethereum held (the position) is given by: position = signal x capital / price, where signal is either 0 or 1.

As it is usual in finance, and as I did in my previous trading Bitcoin blog, I will compare Shepherd's momentum performance with a buy and hold (B&H) strategy. The buy-and-hold strategy acts as a benchmark to assess whether Shepherd's momentum provides additional value.

The next graph shows, on a semi-logarithmic scale, the Shepherd's momentum and buy and hold portfolios value over time, starting with an initial capital of 1000 USD.

The next graph shows the Shepherd's momentum strategy percent invested. While B&H is always 100% invested, the binary SM is either out of the market or fully invested.

The next table shows the main statistics for the both SM and B&H strategies.

As it can be seen in the table above, the binary Shepherd's momentum strategy is superior to buy and hold in most of the presented indicators, in particular:

• SM's Information Ratio is about 50% higher than B&H's.
• In spite of being frequently out of the market, by the end of the backtest the SM's capital is about 3.5 times B&H's.
• Both Value at Risk (VaR) and Conditional VaR (CVaR) are better for the SM strategy. The CVaR (also called expected shortfall - ES) gives the expected loss in the worst 5% (this threshold was arbitrarily set by me) of cases.
• SM's maximum drawdown is about 0.7 of B&H's.

The kurtosis (the kurtosis here is taken to be the excess kurtosis) is lower (which is theoretically better) for the B&H strategy. That is due to the fact that SM has many zero returns, consequence of being often out of the market. This makes the returns distribution very concentrated around the mean.

Distributions with kurtosis higher than zero are said to be leptokurtic. Leptokurtic distribution have more extreme values, which means that both this investment strategies are prone to both large positive and negative returns.

Note also that while SM's yearly standard deviation is lower than B&H's, at 76% and 100%, they are both high. One standard deviation losses are a likely occurrence over time.

Finally note that Ethereum's price at the end of February 2025 is about at the same level as it was in the middle of April 2021. This means that Ethereum's price has been flat for about the last 4 years.

Final remarks

There are a few points to have in mind:

• The results presented here are a simulation (a backtest).
• Trading involves risks, and readers are solely responsible for their trading decisions.
• Losses, when investing in leveraged products like futures and options, may exceed the original investment's value.
• Past performance, even when actually realized, is not indicative of future results.
• Buy and hold is easy and low-cost. Active trading is complex and incurs costs (slippage and commissions).
• Trading costs were not considered. Trading costs can significantly impact performance, especially in a relatively fast-moving strategy like this version of the SM.