The crypto market has not been faring well in recent months, with many analysts talking now about a “crypto winter”. Many newcomers are pushing back investment, while many seasoned traders are keeping a low profile. Can HAL’s algorithmic strategies be of any help in this context? The answer is yes, and we will explain why in this article.
It’s Chilly in Crypto Right Now
The figures don’t lie: the crypto market is in a period of decline. BTC’s value has fallen by -58,50% since October 2021, and ETH is following a similar trend (-65,50%).
Why is this happening?
First, there have been high profile crashes and bankruptcies (Terra-Luna, Celsius, Three Arrows Capital), sparking further concern in the industry and liquidations.
Then, the crypto market is not immune to the global financial crisis that is currently unfolding. As a matter of fact, the correlation between BTC and equities (especially tech stocks) has been rising in the past year. This means BTC is impacted by forces pushing down value for many assets: geopolitical issues such as the Russia-Ukraine war, fears over a looming recession, inflation…
Finally, in order to curb inflation, central banks have been rising interest rates, a policy decision that impacts all risky assets. That’s because the “risk-free” rate on assets such as US Treasury Bonds have a more attractive risk/reward ratio than investing money in riskier assets, and the cost of capital rises.
How Do HAL Strategies Cope in a Bear Market?
HAL strategies take different approaches when it comes to trading in bear markets – where prices are declining.
Wise strategies are long-only strategies: they can go long (buy), but they can never short-sell (sell an asset they don’t own). Their objective is to ride uptrends and avoid downtrend momentums. In order to do so, they open long positions when they identify a potential rise in value, and switch to neutral when the market seems to be going down.
Other strategies on HAL are long-short (Pulse). This means they can both buy and short-sell their underlying asset. The ability to short-sell allows them to bet on falling prices and therefore stay active in bear markets, but it also makes these strategies more risky.
Finally you’ll find on HAL pre-built and AI strategies (like the Dynamic and Artificial Intelligence (AI) Pick) which have a more absolute return profile in their construction due to the “pre-built” nature of the strategy (Dynamic) or with the use of artificial intelligence (Artificial Intelligence (AI) Pick).
The table above shows 12 months performance for HAL strategies and their underlying assets (“benchmark”). The top 3 strategies (Pulse: ETH, Artificial Intelligence (AI) Pick and Wise: Matic) performed especially well in this bear market, while other strategies did not rake in profit over the last year.
Focusing on performance, you can see that relative performance is positive for all strategies, sometimes significantly so – this means that all HAL strategies outperformed their underlying asset for the last 12 months, even if their absolute performance is negative. In a tough bear year, HAL strategies demonstrated they could help curb losses or even make profits.
Focus on Two Top Performers
Let’s have a closer look at last 12 months best-performing strategies, Artificial Intelligence (AI) Pick and Pulse: ETH, our best performers.
Pulse: ETH is an aggressive, short-term (hourly signal) strategy that trades on ETH’s uptrends and downtrends. Artificial Intelligence (AI) Pick is a strategy that uses machine learning to choose HAL’s top 3 performing strategies on BTC or ETH for the coming 24 hours and goes on to apply them.
As both graphs look quite similar and have the same results over 12 months, you can see that Pulse: ETH is more aggressive and volatile than the Artificial Intelligence (AI) Pick.
As a result, the relative performance is on the rise. While their underlying asset was plunging by almost 70%, the strategies achieved a decent positive return (33,42% for Pulse: ETH, 27,58% for Artificial Intelligence (AI) Pick). Pulse: ETH and Artificial Intelligence (AI) Pick outperformed their underlying asset by 102,30% and 98,50% respectively.
But return is not the only metric to take into account. The table above shows that the strategies also outperformed their underlying assets when it came to volatility and drawdowns (the maximum drop from a peak to a low, i.e the maximum pain point for the trader). As a result, their Sharpe (linked to volatility) and Calmar (linked to the maximum drawdown) ratios, that measure return against risk, are also better.
HAL’s automated trading strategies can be allies in times of falling crypto valuations. As we’ve seen, all HAL strategies outperformed their underlying asset over the last year at time of writing, exhibiting a positive relative performance.
This allowed them to reduce losses for traders, in a bear year where assets saw their value drop. Even when market performance is negative, they have been able to reduce losses for traders and, for the top-3 HAL strategies, even make gains.
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Investing involves risk, including the possible loss of all the money you invest. In particular, crypto-assets are a highly volatile and speculative asset class. HAL is only suitable for traders who are willing to bear the risk of loss and experience sharp drawdowns. Past performance is not necessarily a guide to future performance. The performances presented are real performances calculated net of execution fees and slippage from a proprietary Binance account.
The purpose of this material is to provide objective, educational and interesting commentary and analysis on developments in the crypto-assets sector. Nothing in this material should be interpreted as constituting an offer of (or any solicitation in connection with) any investment products or services by any member of the CoinShares Group where it may be illegal to do so. Access to any investment products or services of the CoinShares Group is in all cases subject to the applicable laws and regulations relating thereto.