Long AI Short HypeFighting innovation is a fool’s errand. Getting entangled in hype is no less.
Generative AI is drawing attention. ChatGPT skyrocketed in popularity since launch last November. With its intuitive responses, it has become the fastest-growing app in history reaching one million users in five days and 100 million in two months. In contrast, Google took 12 months and Facebook required four years to get there.
The virality highlights the potential disruptive power of generative AI. Disruptive innovation is not new. Railways in 1800s to Blockchain in the recent past provide ample history.
As observed before, innovation takes time to mature. Yet the hype cycle races ahead only to plunge in time to normalise.
This paper uses iShares Exponential Technologies ETF (XT) as a proxy to cutting edge innovation. XT invests in global firms with exposure to exponential tech, which displaces older tech. It invests across nine themes comprising of firms in both developed and emerging markets that create or use exponential tech.
This paper argues for gains to be harvested from sinking hype using a spread trade. A long position in CME Micro E-Mini Nasdaq Futures (MNQ) combined with a short position in XT will deliver a compelling 1.49x reward to risk ratio.
HISTORY OF HYPED INNOVATION
Gartner hype cycle graphically depicts disruptive innovation journey. First comes the climb to peak hype. Second, fall to trough of disillusion. Third, slope of enlightenment followed by plateau of productivity.
Using Google Trends as a proxy for hype cycle, it shows that market mania around AI is not new. AI searches surged in 2011 with the launch of Siri, Cortana, and IBM’s Watson. With natural language processing tech still in infancy, practical applications were limited then. And soon, the frenzy fizzled.
Innovation in new machine learning algo such as convolutional neural networks and deep learning led to the launch of ChatGPT. Its potential is clear. Yet the tech is in early stages requiring a lot more work before it can mount serious challenge to existing tools.
Tech parity will take considerable time let alone the meaningful monetisation which requires legal and ethical AI use hurdles to be cleared.
One of the foremost examples of Gartner’s Hype Cycle is the boom in US Railways between 1840-1860. Hopes of ever-increasing returns attracted large scale investments only to result in eventual disappointment. Illustrations from recent past (Crypto, IoT, and Blockchain) shows similar fate of over-hyped tech.
CURRENT HYPE IN XT, C3 AI, AND BEIJING DEEP GLINT
A 23% surge in price in iShares Exponential Technologies ETF since mid-October last year is emblematic of Gartner’s hype cycle.
This is even more evident in the share price of C3.ai. Founded by legendary entrepreneur Tom Siebel, this company was named C3 Energy when formed. It changed its name to C3 IoT in 2016 and then renamed again to C3.ai in 2019 to ride the waves of hype.
US equities cannot claim monopoly over hype. Equities elsewhere get swayed too. Shares in Beijing Deep Glint Technology also rallied 80% spurred by ChatGPT. However, last week, the company announced challenges in offering ChatGPT-linked products causing its shares to tank 10%.
ROAD AHEAD FOR GENERATIVE AI
Generative AI is here to stay. Infancy for now but the tech will mature. Competition will rise. Winners will emerge. But monetization is another story altogether.
Favouring innovation while frowning on hype fuelled by inflated expectations, this case study proposes a spread trade. A long position in CME Micro E-Mini Nasdaq Futures (MNQ) combined with a short position in iShares Exponential Technologies ETF (XT) delivers a compelling 1.49 reward to risk ratio.
TRADE SET UP
Why a spread trade? In the short term, elevated levels of uncertainty have left experts puzzled on whether we are in a bull market or a bear market rally. Hence, to extract pure alpha (by neutralising beta) of securing gains from diminishing hype, this case study proposes a spread trade.
The spread will gain in a bullish market when MNQ rises relative to XT. Similarly, the spread will gain in a bearish market when XT falls more than MNQ.
CME’s Micro E-Mini Nasdaq-100 Index Futures expiring in June 2023 (MNQM2023) provides a notional exposure to $2 x Nasdaq-100 index. With MNQM2023 settling at 12,525.50 on February 17th, the futures provide a notional exposure of $25,051.
XT settled at $52.58 on the same day. A spread requires notional value of both the legs to be identical. Therefore, this requires short selling 476 units of XT for a short exposure of $25,028.
• Entry: 238.218
• Target: 255
• Stop: 227
• Profit at Target: $ 1,760
• Loss at Stop: $ 1,180
• Reward-to-Risk Ratio: 1.49x
MARKET DATA
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DISCLAIMER
This case study is for educational purposes only and does not constitute investment recommendations or advice. Nor are they used to promote any specific products, or services.
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REFERENCES
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Gartnerhypecycle
Bitcoin - stick a fork in meWhere are we on the Bitcoin/crypto journey?
This log scale chart roughly guesses at different stages on the Gartner hype cycle. We might still be on the way up to the peak of speculation, we may have peaked, and the chart also imagines that this asset class might continue to grow more modestly than it has previously done, up to September next year. And maybe that's a reasonable assumption, as this might be the year that scaling and mass adoption of blockchain gets cemented.
With Bitcoin reaching its tenth birthday next year, it'll be interesting to find out. Let's see how well this ages.
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I know a lot of people will disagree with this, but I believe that this will go up again. This is part of the psychology market cycle or Gartners Hype. (feel free to google) The same exact pattern is reoccurring just on a bigger time frame. There are fractals on top of other fractals. The psychology of the market makes these skyrocket within a limited duration, but take forever to retrace. It feels like it bleeds out until it reaches just below the .786 mark and consolidates for a while before shooting up and repeating the same pattern over. History repeats itself.