Trading ripple (XRP) using a fast Shepherd's momentum signal

Introduction

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

The complete series list is:

• "Trading Bitcoin using a fast Shepherd's Momentum signal",
• "Trading Ethereum using a fast Shepherd's Momentum binary signal",
• this blog, "Trading 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:

As always, 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 XRP's price and volume, on a semi-logarithmic scale, since January first, 2014.

Shepherd's momentum on XRP

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 XRP and the rest in cash.

The following graph shows the XRP price together with the Shepherd's momentum signal ranging from -1 to 1.

Shepherd's momentum and buy and hold performance

Short positions will not not be allowed as I assume that most investors are not able to easily short sell cryptocurrencies. Consequently if the signal is less than zero, the position will be zero.

Therefore, the number of units of XRP held (the position) is given by: position = signal x capital / price, where signal is a value greater or equal to 0 and less or equal to 1.

As it is usual in finance, in this blog series, 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.

In this blog I test how the Shepherd's momentum performs when starting the backtest near a price high. Therefore I started the backtest at the beginning of 2018.

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 in January, first 2018.

The next graph shows the Shepherd's momentum and buy and hold strategy percent invested. While B&H is always 100% invested, SM is mostly only partially invested.

The next table shows the main statistics, calculated on logarithmic returns, for both SM and B&H strategies.

In my sample XRP's price on January first, 2015 was about 2.31 USD. At the end of my sample, March third 2025 was about 2.94 USD. This is an increase of about 27% in more or less 7 years. Note that different data sources may have different prices for the same date. Cryptocurrency markets operate continuously everyday for 24 hours a day and the price providers do not all give the price taken at exactly the some time or from the same source. The Shepherd's momentum strategy, during the same 7 year period, achieved a return of about 100%, about 1.6 times better than B&H. This result is achieved while SM is frequently out of the market and rarely, if at all, fully invested.

The information ratios are 0.03 and 0.01, for SM and B&H respectively. Shepherd's momentum's returns are reasonable but very volatile, consequently the Information Ratio is low.

Importantly, Shepherd's momentum has a better risk profile than buy and hold:

• SM's yearly standard deviation is about half of B&H's. Nevertheless, both yearly standard deviations are high at 54 and 105. Bear in mind that one standard deviation losses are a likely occurrence over time.
• 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 0.8 of B&H's.

Distributions with higher than zero kurtosis (For more on kurtosis check my "A word on financial returns" blog) are said to be leptokurtic. Both SM and B&H strategies logarithmic returns distribution are Leptokurtic. Leptokurtic distribution have more extreme values, which means that both this investment strategies are prone to both large positive and negative returns.

The 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.

Finally note that XRP's price at the end of February 2025 is below the peak attained in the beginning of January 2018.

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.