If dogecoin goes to the moon, a risk manager should go too

There seems little logic to the price of meme assets – but bold investors can protect themselves, says tech expert

Dogecoin and bitcoin

Earlier this year, a group of amateur investors turned markets on their heads with concerted speculative bets on the Robinhood trading app. The episode provides a cautionary tale for cryptocurrency investors today, and shows that risk management is often about reacting fast to what is happening now, rather than predicting what is going to happen next.

In the case of cryptocurrencies, a lot has been happening. Bitcoin, the world’s largest digital currency by market capitalisation, has seen a dramatic price collapse following a series of tweets by the well-known founder of an electric car company. At the time of writing, its price was $39,000, down 38% from a year’s high of $63,000.

Other digital currencies have been caught up in the melee, too. One is dogecoin, until recently an obscure token thought to have been started as a parody, but which has now become the sixth-largest cryptocurrency by market capitalisation, according to data from CoinMarketCap. Its price is down more than 50% from its year highs.

For traders and risk managers, this is a frightening idea. Their job – to assess the risk that these assets pose – is made all the more difficult by the unprecedented levels of retail investor capital injected into public markets, some of it from government stimulus cheques.

What was clear from January’s GameStop saga is that existing systems at many fund managers are simply not set up to capture this new and unpredictable element to the markets – not unless the world’s top asset managers start spending a lot more time on Reddit, that is. Just ask Melvin Capital, the hedge fund that fell victim to this new brand of retail-driven volatility when it suffered eye-watering losses of 50% on various short positions on GameStop back in January, and was bailed out by Citadel.

Whether this type of retail activity continues once the stimulus cheques dry up and furloughed workers return to their day jobs, remains to be seen. But for asset managers who are considering investing in crypto – or even those who have already taken the plunge – robust, real-time views of risk are critical.

Managers need to be able to identify which assets are potentially exposed when prices start fluctuating rapidly, but they also need to be able to analyse and assess what that means for their portfolio quickly and accurately. This especially applies to cryptocurrencies that aren’t always immediately liquid, such as dogecoin.

Risk alerts that can provide early warnings of a dramatic price swing are a natural option. But, first, managers will need to add or expand categories to identify and track those assets that are at risk of these kinds of moves, which itself is no mean feat.

Next is to identify the quantitative and qualitative elements of an early-warning system that portfolio risk managers can use to expand their awareness of exposure. This information can also feed into scenario analyses to better prepare managers for the next event. There may also be an opportunity to incentivise traders to minimise their exposure to meme-susceptible assets, by adding large movement stress scenarios into the risk limit calculations.  

Mega-cap companies like Google or Microsoft have large and liquid enough share bases to fend off even the most sustained retail investor assaults. But does the same stand for dogecoin, or even bitcoin? The wild price swings we’ve seen recently for both currencies would suggest not.

 

 

Simply disincentivising portfolio managers from trading those assets by forcing them to consider the losses they’d face under large stress scenarios would effectively shut down a lot of crypto strategies.

These are all effective use cases for machine learning techniques, although so far the datasets required to train those algorithms are still accumulating. The underlying R&D platform needs quality data sources, both structured, such as price and volume history, and unstructured, like Elon Musk’s Twitter feed.

Managers will also need to be able to test multiple hypotheses quickly and at scale. Cloud computing can be useful for these tests, as firms can rent capacity and pay for just what they need. But what is clear is that legacy trading and risk management systems need updating. In a world where currencies, assets and even art are literally being created out of thin air, having suitable infrastructure to trade, value and determine risk on digital assets is a must.

Mark Higgins is co-founder and chief analytics officer of Beacon Platform, a cloud-based trading and pricing engine. He previously spent eight years at JP Morgan, where he launched the Athena project. Before that, he spent eight years at Goldman Sachs as a strategist on the foreign exchange and interest rate market-making desks.

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