The Bitcoin “Penny Stock”

For almost a decade, Bitcoin has periodically captured the attention of the public. Sometimes for its technological potential, sometimes as an object of ridicule, but often times for its boom / bust cycles that have fueled the limitless imaginations of speculators.

Since the start of this year, Bitcoin and alt-coins have once again captured the attention of the public.

market-price-(usd)

Not only has Bitcoin risen dramatically in price, potentially minting hundreds of millionaires and possibly a few discrete billionaires, the blockchain, alt-coins, and ICOs appear to be carrying us at light-speed into a radically democratized and de-centralized future.

I’m not here to speak to the technological appeal of blockchains — for which there are many — as there are many more qualified minds that can do that better than I can.

However, I do have news for you:

Bitcoin’s meteoric rise in price year-to-date has more to do with the technicals and conditions normally found in penny stocks than likely any long-term fundamental factors. 

Before you immediately dismiss the rest of this post because you suspect my argument is for lower prices, I will be upfront and tell you that that is not the case. I have no particular view on whether cryptocurrencies will go up or down. My goal is simply to discuss what I believe has been the primary driver of upward momentum and leave it for the reader to assess whether these conditions will continue favorably or potentially reverse. Having observed the rise of many penny stocks, I have seen few that don’t eventually come crashing back down in dramatic fashion when the conditions that made the rise possible cease to persist.

The Anatomy of a Penny Stock Shooting Star

Most penny stocks never amount to anything. But occasionally, a few rise and rise and rise in dramatic fashion. Sometimes up to thousands of percents within a few days or months.

For example:

HGENCVSI

Every penny stock shooting star begins with a similar set of conditions: Limited information, micro market capitalizations, and extremely low liquidity.

All of these factors come together to maximize the chance that a / any penny stock can be easily manipulated to trade on everything but fundamentals.

Fundamentals are usually the enemy of penny stocks since most of these have no long-term successful business models. What they might have are seductive stories – potential to change the world, potential to transform society, and the most seductive story of all, the potential to make you very rich very quickly. Limited information creates the right environment to nurture these stories because whatever information you can get becomes definitive. The siren song these stocks sing are already powerful in and of itself, but even more so when there are no other credible voices of caution.

Micro market capitalizations further nurture this environment because it usually keeps professionals away. By virtue of having a small market cap, it is nearly impossible to make meaningful amounts of money for the professionals (e.g. shorting), and thus many that could see through the risks of penny stocks are not engaged. Retail investors also popularly assume that many long-term winner once began as penny stocks:

Investors who have fallen into the trap of the first fallacy believe Wal-Mart, Microsoft and many other large companies were once penny stocks that have appreciated to high dollar values. Many investors make this mistake because they are looking at the “adjusted stock price,” which takes into account all stock splits. By taking a look at both Microsoft and Wal-Mart, you can see that the respective prices on their first days of trading were $21 and $16.50, even though the prices adjusted for splits was about eight cents and one cent, respectively. Rather than starting at a low market price, these companies actually started high, continually rising until they needed to be split.

-Investopedia, The Lowdown on Penny Stocks

But the most important one of all – low liquidity. It is through low liquidity that penny stocks gain their immense volatility. As money pours in (or out), low liquidity guarantees that trades will easily move penny stocks like a leaf-blower through a forest floor.

Why Some Penny Stocks Soar While Others Languish and are Simply Forgotten

Many retail investors have limited ability (or perhaps desire) to conduct research on companies. Many retail investors are simply chartists. But to become a shooting star, penny stocks need a story. Although the most seductive story of all is always the same – you can be rich very quickly – even speculators usually demand a story that has some semblance of fundamental long-term potential.

Because of that, many penny stock shooting stars begin with a sponsor that formulates this story and sells it to potential speculators. These sponsors are the ones that get the flywheel going. Story formulation is not the hard part, but how do you convince speculators that there is potentially a lot of money to be made? The easiest way is to show that a lot of money has already been created, but don’t just sit there or you will miss out on all the rest! By targeting low liquidity penny stocks, a sponsor can buy a meaningful amount of stock initially, which drives up the price because of the low liquidity. This creates the initial gains that will eventually draw in other speculators. Once the flywheel is in full motion, the sponsor will quietly sell down the initial purchase at a handsome gain, leaving speculative followers with the aftermath.

This is known as pump-and-dump:

The same scheme can be perpetrated by anyone with access to an online trading account and the ability to convince other investors to buy a stock that is supposedly ready to take off. The schemer can get the action going by buying heavily into a stock that trades on low volume, which usually pumps up the price. The price action induces other investors to buy heavily, pumping the share price even higher. At any point when the schemer feels the buying pressure is ready to fall off, he can dump his shares for a big profit.

-Investopedia, Pump and Dump

Regardless of how sophisticated you are with the markets, I’m quite certain most people know that pump-and-dumps never end well (unless you are the sponsor or a speculator that recognizes a pump-and-dump for what it is and are able to get out in time).

Drawing Parallels to Bitcoin

So what are the parallels to Bitcoin and alt-coins? Simple, all the conditions that make penny stocks potential vehicles for speculation have been present in Bitcoin and alt-coins.

Firstly, Bitcoins and alt-coins are new areas driven by technology that has not matured and continues to evolve. This creates an environment that is a vacuum for information that is necessary to judge the long-term fundamentals of the asset class. In addition, the amount of technical knowledge needed to understand cryptocurrencies mean that a small subset of people can establish themselves as the de-facto experts on the future and possibilities of cryptocurrencies. Regardless of whether these expert opinions are well-placed or not, they formulate and control the story and overwhelmingly the story has been about the potential for cryptocurrencies to change everything – your life, your finances, government, everything.

Cryptocurrencies in the aggregate recently accumulated a market cap of >$160bn, certainly not micro cap under any definition. However, we should view that in light of the 30-40x growth within the past year. We need to consider the market cap before the rise, and even as recently as October of last year, the aggregate market cap of all cryptocurrencies according to Coinmarketcap.com was as low as $13bn.

Cryptocurrency Market Cap

And as with penny stocks, the most important factor of all – low liquidity. I cannot overstate how important this factor is for understanding why Bitcoin and cryptocurrencies began a sudden rise less than a year ago.

Let’s take a look at Bitcoin trading volumes over the last 6 months (via data.bitcoinity.org):

6m Bitcoin Volume.jpg

We can observe a few spikes here and there, but overall the volumes have been fairly steady. Do note that volumes rose significantly as the recent sell-off intensified in August / September.

But the more informative chart is to see what volumes have done over the past year – you will be shocked:

Bitcoin 2 Year Volume

Volumes absolutely collapsed between December and January. In fact, liquidity nearly entirely dried up.

Where did the liquidity declines come from? Cutting the data another way, we can see which exchanges were responsible for most of the trading over the past two years: BTCChina, Huobi, and OKCoin. These three exchanges were responsible for close to 90% of all Bitcoin trading over the past 2 years, but suddenly the entire volumes of all three exchanges evaporated at the end of last year.

Bitcoin Volume by Exchange

The drop in volumes was due largely to Chinese regulations tightening up the trading of cryptocurrencies. Coindesk featured an interesting article highlighting this dynamic earlier in the year.

Due to the significant decline of Bitcoin trading volume earlier this year, I believe it is clear that Bitcoin’s low liquidity created conditions that are normally only observable in penny stocks. This low liquidity likely allowed well-meaning technologists and venture capitals that are true believers of cryptocurrencies to inadvertently act like sponsors akin to those of penny stock schemes. The buying of cryptocurrencies into extremely thin liquidity created the initial 5x-10x gains that would later bring masses of retail speculators.

Do All Shooting Stars Eventually Burn Out?

Here’s the thing – with penny stocks, the rise usually comes to an end because the sponsor sells out at the top. The sponsor considers when s/he has maximized the number of speculators (or prey depending on how you look at it) that can get pulled in and then will sell out at the top. Sponsors always have an endgame of getting out before the crowd finds out.

I have no doubts that given the extremely low liquidity in cryptocurrencies today, that if the large cryptocurrency wallets (and yes, there are a number of wallets out there are are very massive in size) were to cash out, downside volatility would be as dramatic as the rise we have seen year to date.

The question is how many of the early “investors” in cryptocurrencies believe enough in the long term to not be concerned about volatility and therefore feel compelled to go back into cash / government-issued currency? If Bitcoins and alt-coins were truly only in the hands of true believers, low liquidity could mean that we continue to see these cryptocurrencies appreciate 50x or 100x or even more from here.

The question is, again, are cryptocurrencies in the hands of true believers?

One anchor that many investors / speculators in Bitcoin fixate on is that the number of Bitcoins that will ever be in existence is fixed (currently growing at a small rate but total that will ever be mined is fixed). Yes – this is true, and perhaps one reason why Bitcoin should appreciate relative to the growing stock of government-issued currency. But 30-40x in 9 months? That’s only possible not because the stock of Bitcoins is fixed, but because the tradable float of Bitcoin has been decliningJust ask yourself how many cryptocurrency investors you’ve heard say that they will buy and sit on it and never sell – these coins are locked away and in effect reduce the tradable float. The tradable float is declining every day.

When will this locked up float suddenly come back to exchanges? That will be a terrible moment.

As I mentioned at the beginning, I’ll leave it up to readers to decide on the direction of prices. I have no view. What I have a view on is that Bitcoin and alt-coins have increasingly become like penny stocks.

I’ll close with a quote from Fred Wilson, a celebrated Venture Capitalist:

I know a lot of people who are true believers in crypto and have made fortunes in it. They are “all in” on crypto and have much of their net worth (all in some cases) invested in this sector. I worry about them and this post is aimed at them and others like them. It is fine to be a true believer and being all in on crypto has made them a lot of money. But preservation of capital is about diversification and I think and hope that they will take some money off the table, pay the taxes, and invest it elsewhere.

-Fred Wilson, Diversification (aka How to Survive a Crash)

Beware – even the faith of the true believers may waiver.

The World’s Most Valuable E-Commerce Company

Is possibly going to be Alibaba very soon.

Amazon vs BABA

For a long while following it’s IPO in 2014, investors were highly skeptical of Alibaba. Many still are, but many more are starting to recognize Alibaba’s incredible dominance in China. More importantly, as mentioned briefly in my post Tencent vs Alibaba on the Quest to Go Global, the company stands a fairly good chance of going global.

Despite the rising enthusiasm for Alibaba, the company appears to be underrated. A few examples:

  • As of FY16, Alibaba reported gross merchandise volume (GMV) of $547 billion across its e-commerce platforms. Amazon does not report GMV but estimates peg it around $300 billion.
  • Alibaba had annual active buyers of 466 million as of 2Q17. Amazon does not report annual customer count, but Statista pegs it at ~300 million.
  • Alibaba owns approx. 1/3 of Ant Financial, which is the world’s largest fintech co. Amazon has surprisingly limited interest in fintech.

Amazon is rightly known as an aggressive competitor, but Jeff Bezos once squared off with Jack Ma in China and lost (Amazon was also relatively late to China). Both are now vying for control of India. But their strategies could not be more different: Amazon is essentially carrying out a very similar playbook to the one in the US (superior distribution/logistics + Prime), while Alibaba has gone the fintech route and leveraging that to enter e-commerce.

Will be interesting to see how India plays out since Amazon is determined to not let India slip out of its hands and is currently near pole position.

Predicting the Potential of “New Electricity” by Looking at the Lessons of “Old Electricity”

Andrew Ng (former Chief Scientist at Baidu, Co-founder of Coursera) is fond of referring to AI as the “new electricity”. Similar to how electrification ended up transforming every single industry during the 20th Century, AI is broadly expected to have similar (if not greater) impact in the coming years.

This post by Oscar Li does a great job encapsulating Andrew Ng’s thoughts as shared during a recent lecture at Stanford.

The social and business ramifications are easy to extrapolate / imagine: Anything that you can do now, you can do better with more AI and data. And as the technology that underpins AI continues to improve and the datasets continue to grow, AI will allow us (or machines) to do whole new things not possible before.

If you’re like me, it’s actually quite overwhelming to ponder the full implications of AI. But if AI is on track to transform the world like how electricity did, we should be able to learn some lessons and create some useful predictions by looking at what happened a century ago.

Lessons from Electrification:

  1. Everyone Electrified and then Electricity was no Longer a Differentiating Factor: Today, companies that use AI and data have an advantage over those that don’t. A similar dynamic existed a century ago. Retailers that were electrified had an advantage over those that didn’t. Factories that were electrified had an advantage over those that didn’t. Eventually all businesses either adopted electrification or were out-competed. However, once electrification was fully borne out, it was no longer an advantage. A similar dynamic also played out with air conditioning in the middle of the 20th century where early adopters had an advantage, but once every retailer adopted air conditioning, it became a necessity rather than an advantage.
  2. Electricity Changed How Business was Done But Had Less of an Impact on the “Jobs to be Done”: Electrification allowed businesses to extend their hours of operations, drastically increasing efficiency and productivity. Electrification also brought about new machinery and tools that similarly improved efficiency. In other words, electricity made businesses (and people) better at their craft but had less of an impact in terms of the goals that businesses pursued. Retailers remained retailers. Manufacturers remained manufacturers. Service providers remained service providers. This is perhaps the most interesting takeaway (or contrast) with current assumptions around AI – namely that AI will necessarily lead to “new” products / services.
  3. The New Business Model Created by Electrification was the Electric Utility: Although electrification had large ramifications on how existing industries operated, the only key new business model to emerge appears to be the electric utility to provide the fuel for the disruptive technology (I’m not quite sure if this statement is entirely accurate – if any readers have supporting evidence for / against, please do share). Similarly, how many new business models should we anticipate in the coming AI explosion? It’s clear that AI will be important for existing industries, but how many new types of businesses should we expect? Perhaps a “data utility”, but what else?
  4. Other than Utilities, No One Made Money on Electricity: Once every business adopted electricity, it was no longer a differentiating factor by and of itself. As a result, electrification become purely a cost of doing business. Only utilities made money off of electricity. Can this be extrapolated to AI and data? Will it purely become a cost of doing business?
  5. Electricity Led to a “Cambrian Explosion” in Hardware: Although electrification appeared to merely change how businesses were run, it did lead to many new hardware products such as light bulbs, phonographs, radios, televisions, etc. Turned out that the best way to monetize electricity other than operating a utility was to produce hardware. This was the genesis of General Electric. Perhaps that is also what we should expect of AI.

These are just a handful of lessons. There are probably more that can be added to this list.

Taking these into account, it’s not outrageous to ponder whether AI can truly be monetized if not offered as B2B service (e.g. the utility model) or bundled with hardware (e.g. Amazon Echo, Siri / Google Assistant / Cortana in devices). Are there alternate monetization pathways if neither of these are feasible?

One thing that is an interesting contrast between AI/data and electricity is that AI algorithms and datasets are not commodities like electricity. Every utility’s product is the same. But AI algorithms and datasets are not interchangeable. What are the implications of having non-interchangeable “fuel” for one of the most disruptive technologies of the 21st Century?

Tencent vs Alibaba on the Quest to Go Global

Finally catching up on some reading: Bloomberg published an excellent profile on Tencent and the co’s strategist, Martin Lau. I highly recommend the article as it not only goes through the history of the company, but reveals the type of thinking and mentality that has helped Tencent become one of the most successful companies in the world.

For the uninitiated, Tencent is one of the “BAT” trinity (Baidu, Alibaba, Tencent) that dominate the Chinese tech space. The Chinese are increasingly living their lives in a “digital-first” manner, and as a result, BAT’s influence extends across nearly all aspects of Chinese life in a way that Google, Facebook, Amazon, Apple can only wish (and try to replicate with limited success thus far). All three players operate across nearly all verticals including social, video/entertainment, e-commerce, search, browsers, app stores, delivery, cloud services, payments, finance, and many more. They have gone beyond being just software/service companies to essentially digital lifestyle companies.

Despite the BAT moniker, investors view the strengths of each company quite differently.

Generally, Baidu (the company with search as its core strength) is viewed as the weakest. Unlike Google’s dominance in the US, Baidu has struggled to find its place in China’s highly digitized mobile world were users largely spend their time in Tencent or Alibaba’s walled gardens. Whereas Google has been able to run its search crawlers through the open internet and through the Android platform (majority global share), Baidu does not have the luxury of a dominant mobile platform nor access to the increasingly large amounts of data that is generated outside of the browser.

Of the remaining two, Alibaba and Tencent are generally neck-and-neck. Alibaba absolutely dominates in e-commerce and payments/finance while Tencent owns the incredibly sticky WeChat messaging super-app with a fast growing payments solution. Nonetheless, investors overwhelmingly consider Tencent to be a much stronger business with a 1yr forward P/E of 45x to Alibaba’s 34x despite similar growth rates according to consensus estimates. The difference in perception largely comes down to the fact that investors consider WeChat to be mostly un-disruptable while Alibaba is currently contending with a sizable #2 player in JD.

However, I believe that perception is misplaced especially when we consider Tencent’s and Alibaba’s prospects for going global.

The Bloomberg article mentioned above highlights the challenges that Tencent faces in trying to export its WeChat model abroad:

Then there’s the matter of Facebook Inc. and WhatsApp, which have a huge market advantage pretty much everywhere outside China. Going overseas, Lau says, “is essentially the challenge of every Chinese company. We tried to make WeChat international. The reality was that there were other products in the market already.”

Tencent faces a much more formidable competitor in Facebook as they try to expand abroad, while the global e-commerce landscape is much more benign for Alibaba. E-commerce is much more fragmented on a global scale, and Amazon is nowhere near as dominant on a global scale as Facebook is for social networking.

The valuation gap between the two companies only make sense in a China-specific context. In a global context, why should that gap exist?

Disclosure: I have no direct beneficial interest in Tencent (700 HK) or Alibaba (BABA) as of publishing date and have no intent to initiate a position within the next 48 hours. 

What Apple, Google, and Facebook’s Business Models Tell Us About Their Ability to Adapt to the Coming AI-Future

 

Judging from market multiples, it’s clear the market is skeptical of Apple’s ability to continue to succeed and has been for many years (currently, 1-yr forward P/E of ~15x despite recent re-rating), while holding limited concern for Google and Facebook (both 1-yr forward at ~26x).

This concern is understandable given the ever-changing tech environment and the long list of tech companies that have been buried over time (e.g. Nokia, Blackberry, Motorola). Even industry stalwarts of the bygone PC-era such as HP, Dell, and even Intel/Microsoft now stand on far weaker ground. And this concern for Apple is not new as Horace Dediu points out at Asymco

However, I contend that Apple’s business model is far more robust than Google’s in the coming artificial intelligence (AI)-revolution. 

Leaving aside potential differences in technical competency, AI is likely more complementary to Apple’s business model, but potentially highly disruptive to Google’s.

And to understand why, it requires understanding the job-to-be-done for search users and how Google’s ad-centric business model fits in.

The Assumptions Behind Search

Let’s start with the user – why do Google users search? What is the job-to-be-done?Seemingly simple question with a straight-forward answer: We are curious about many things and don’t have perfect knowledge. Google can help us answer what we don’t know. For most of Google Search’s existence, the service has approached this job-to-be-done by returning a curated list of search results that are most likely to match what the user is looking for. These are organic results that are designed to improve over time as the algorithm takes into account the answers/results users found most useful in the aggregate. Fairly simple and straight-forward.

So now turning to the business model – Google Search makes money on the ads that appear alongside search results. Every click on an ad (as opposed to an organic result) generates a small bit of revenue for Google.

Under what circumstances would a user prefer an ad over an organic result? 

Philosophically, Ben Evans (A16Z partner and almost always more than a few steps ahead of the curve) hits the nail on the spot:

In essence, the existence of ads on Google Search is the most egregious effigy to the failure of the underlying search algorithm. Every time a user clicks on an ad, it is an implicit acknowledgement that Google Search did not accomplish its job-to-be-done, that the desired answer would not have been provided had the advertiser not paid for that placement.

Given a long enough time horizon, if Google Search is truly improving, barreling towards a future where Google can answer any question without doubt and with perfect context, Google’s business model would have to evolve because ads do not have an obvious place in that future. 

And that future is coming closer with the advancements in AI. 

Search and AI

What could search look like in an AI-driven world?

It might not look all that different – perhaps Google’s I’m Feeling Lucky option or the knowledge graph cards.

But, it could also be radically different such as the search results provided by assistants such as Apple’s Siri or Amazon’s Alexa.

Regardless of the ultimate direction, it’s clear that ads have a far less obvious place in this future. If AI can be used to surface the right answer the user needs, the user would have less of a need to click on an ad.

I think we’ve seen the first instance of this issue with Google’s recent Beauty and the Beast ad on Google Home. The Google Home assistant (like Alexa) does not offer a natural channel for ads, and as a result, Google will have to find increasingly creative ways to adapt their business model for the changing environment. But history is filled with examples of failed business model surgeries.

It also makes Google’s persistent pursuit of a hardware/software business model a la Apple much more understandable. Perhaps selling hardware isn’t just about protecting access to market (after all, it’s unlikely that Android will be unseated now that it is so entrenched, so why continue with the direct hardware efforts?), it could be a deliberate attempt to evolve their business model to ensure financial relevancy in the AI-driven future.

Why Investors Seem Complacent

I contend that investors (or analysts) are confusing two separate concepts to be the same thing – the universal desire to know (hence search) and the need for ads to provide that information.

There is no doubt that search queries will only grow. It’s not farfetched to imagine a future where there are 7 billion search users instead of the less than 2 billion today. But that’s a far different conclusion from assuming Google’s financial future and business model are robust as long as search queries grow.

Search is robust, but are ads robust relative to our AI-future?

Apple’s Business Model is Far More Complementary to AI

Apple’s business model, on the other hand, is much more aligned. Sell the best products available for customers’ job-to-be-done.

AI is not orthogonal to this pursuit and business model. The only question is whether Apple has the technological capabilities to do so. However, even under the assumption that Apple is not the leader in AI-technology, it is not clear that it matters. After all, Apple was not the original leader in GUIs (Xerox PARC was). Apple was not the original leader in phones (Microsoft, Palm, Blackberry, Nokia, etc. were). Despite not being the original leader, Apple had the business model and insight to ensure that they could ride the underlying technological trend, and if I were to take a bet today, I believe Apple’s business model makes them more prepared to usher in an AI-world than Google is. AI is a feature to Apple. AI is a potential danger to Google’s business model.

From a business model standpoint, Apple is far more robust in an AI-world.

What About Facebook?

Facebook’s an ad-driven business model. What about them? Surely, Facebook is potentially in danger as well.

Facebook’s situation is less clear cut because the job-to-be-done for users is different vs search. Search has a “right” set of answers. Facebook’s feeds do not. Users are not necessarily searching for anything specific but rather using the services as an outlet for time. The “wrong” answer in a search query is far more obvious than a “wrong” answer in a Facebook feed.

And if AI can be used effectively to ensure that organic content on News Feed, Instagram, etc. are more relevant and engaging, then perhaps that can even offset any deterioration in experience from an increase in ad load. AI can never make Google’s organic results more engaging to the point where a user will tolerate a less user-friendly ad environment.

Facebook’s job-to-be-done is to, cynically, offer a time sink. Google’s job-to-be-done is to get you your answer as fast as possible. One of these is more complementary for an ad-driven business model. 

Concluding Thought

Is Google as robust as investors think? Borrowing from Peter Thiel – is this something that could be true that no one believes? Is Apple in as much danger as the average person believes?

Disclosure: I have no direct beneficial interest in AAPL, GOOGL, or FB as of publishing date and have no intent to initiate a position within the next 48 hours.