Category: Investing Insight

Investing insight to make you a better investor.

Momo "Rapid-Fire" Momentum

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High octane strategies for your portfolio

The biggest advantage that retail investors have is that they don’t have to worry about managing a huge portfolio with different types of investors with differing time-horizons and expectations. And of course, there’s the straightjacket of mandates that bind professional investors.

The problem with bucketing yourself as a “value investor,” “contrarian,” “growth,” or “momentum guy” is that you lose the biggest advantage that you have: flexibility and the ability to adapt to the market. Mandates, or lack thereof

Broadly, at a meta-level, investment strategies can either be Ferraris or busses but not both. They are built with different uses in mind. A Ferrari is not going to be able to seat 40 people or tug a 40 ton rig. And you don’t build a bus to go 0 to 60 mph in 3 seconds.

As a retail investor, your life becomes a lot simpler if you decide upfront if you want to drive a Ferrari or take the bus. But once you get on one, be at peace with your decision. Most investors would be better off taking the bus: DCA/SIP into a mutual fund, don’t chase performance, focus on asset allocation and increase your income and savings over time.

However, just because taking the bus is “right” according to conventional wisdom, doesn’t mean that everybody should be forced to get on one. Just like how you have Ferraris, buses and everything else in-between on the road, there are a wide range of investment strategies outside of the mainstream “at-scale” investment vehicles like mutual funds, PMS, managed accounts, etc.

Momo: The Ferrari Of Investment Strategies

Momentum is a well known Fama-French factor. The problem with momentum portfolios have always been the massive left-tail: when markets are volatile, the drawdowns have been heart-breaking. It doesn’t matter if the portfolio is long-only or long/short, there is no escaping the momentum whiplash.

Then there is the question of rebalancing frequency. To scale a momentum fund, managers need to trade-off transaction and impact costs with being responsive to the market. And that means leaving a fair bit of alpha on the table.

This is the constraint of driving a bus. It can be a fast bus. But it is still a bus.

However, what is true for professional investors and funds is not necessarily true for you, the retail investor.

Do It Often, Do It Better

Most of the early factors were researched at a time when compute power and data were hard to come by. Researchers took the short-cut of using monthly returns to run their analysis because it made the problem more tractable. That set a precedent that is being followed to this day: the monthly rebalance schedule.

The problem with a monthly or a quarterly rebalance schedule is that the market has got a lot faster since the days the papers were written. We live in a world where data is abundant and compute power is a fraction of what it used to be. And trading costs have crashed to a small fraction of what it was 30 years ago.

The world changed.

There is no reason why the market shouldn’t be sampled more frequently.

Some Left-Tails Can Be Docked

A higher frequency approach lends itself to better risk management. It allows for a more responsive position sizing system based on market volatility and the ability to employ “stop-loss” exits on individual positions.

While drawdowns are not entirely avoidable given the nature of the markets, it is quite possible to protect the portfolio against the extremely deep ones. And the deep ones seem to occur at least once every three years, or so.

Avoiding the worst of the drawdowns allows for faster compounding of the portfolio.

Momos are risk-managed, frequently sampled momentum strategies.

Our Experience With Momos

We have been running Momo portfolios for both Indian and US markets for a while and we do it for all three flavors of momentum: Relative, Velocity and Acceleration. We’ll get into the differences between these in later posts but irrespective of the flavor, the “container” within which they run are identical.

The flavors wax and wane depending on the market – there is really no way to quantifiably claim that one is better than the other. In terms of personal preference, I would rank Relative Momentum first, Velocity and then Acceleration. To keep things concise, we show Relative “Momo” Momentum performance below.

US Equities

Indian Equities

Does It Scale?

When we discuss these strategies with professional fund managers, the most common question that comes up is “does it scale?”

And the answer is: No.

It doesn’t scale to professional break-even levels. For eg: for an Indian PMS to break-even, it at least needs Rs. 100 cr in AUM. There is no way the Indian Momos scale up to that level.

But it really doesn’t matter to you, the retail investor. Remember: professional investors are driving a bus, you need not.

Trade-Offs

The market abhors a free lunch. So the next questions is: “What are the trade-offs?”

  1. Risk management is not free. There are always trading costs/taxes that affect the final outcome. But the known-knowns are factored into the performance metrics shown above.

  2. Execution lags. There is always a delay between when the trades are triggered and when the execution takes place. This can be narrowed down by automation to a de minimis.

  3. Compliance. There could be employer, broker or regulator imposed limits on how frequently positions can be churned in certain accounts. Momos would be a poor fit in these circumstances given that any deviation from the model triggered trades can lead to substantial deviation in performance.

Next Steps

If you decide that taking the bus is not for you, then we can help. Have a look at the Momo strategies linked below and let us know if you are interested. We are here to help.

US Momos

Relative Momentum

Velocity

Acceleration

Indian Momos

Relative Momentum

Velocity

Acceleration

Check out our completely automated strategies: stockviz.biz/themes

Investing in the US? We got you covered on us.stockviz.biz/themes

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Bitcoin is Forever

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The nature of Bitcoin is such that once version 0.1 was released, the core design was set in stone for the rest of its lifetime – Satoshi Nakamoto, creator of Bitcoin

This goes against the more well understood motto of technology startups: “move fast and break things.” Unlike a startup, or even a big company, Bitcoin doesn’t move fast, or break things. Of course, I am not talking about its price as measured in USD or INR. I am talking about the entire Bitcoin system, or Bitcoin, the protocol. Bitcoin is stagnant, ossified, set-in-stone, resistant-to-change, and any number of such synonyms you can look up in a thesaurus. There are a few obvious questions that come out of this:

  • Why is ossification preferred over, say, innovation?

  • How do you achieve ossification in software?

  • Does it matter?

If you sit back and think, the answers to these questions are not obvious. Let’s address them.

Why?

It seems obvious that innovation is good, innovation is right, and innovation works. Maybe it even captures the essence of the evolutionary spirit. So, why does Bitcoin not want to innovate? The answer lies in layers. By layers, I mean – in layers of abstraction. In any system, the base layer has to be set in stone for the layers above it to work. Think of civil engineering: it works because the laws of physics are set in stone. The value of the gravitational constant doesn’t change over time, thankfully, just because nature wants to innovate. 

Having an “innovative” base layer comes at a high cost to systems being built above it. Bitcoin was designed as a base layer for the world’s financial system. We can argue that that’s a stupidly ambitious goal, and is most likely not going to happen. That might very well be. Given the goal (stupid as it might be), innovation goes against Bitcoin’s purpose. An unchanging base layer of money allows innovation in layers above because a predictable foundation is a good foundation. Change-resistance tells its users that their initial trust in the system will not have to be recalibrated every now and then. A user’s understanding of Bitcoin doesn’t have to be updated after every recession. Money should be independent of booms and busts in the real economy. 

On the flip side, change-resistance resists all changes, good and bad. This is a philosophical preference, and reasonable sides have disagreed about this. Ethereum, the second most popular cryptocurrency, has argued that good changes are worth the cost, and is going ahead with radical changes to its base layer as we speak. And has done sweeping changes in the past.

How?

Software is just text interpreted by a computer to perform some actions. How do you design a software system that cannot be changed easily? This goes into the weeds of decentralized distributed peer-to-peer systems, and a bit of the mechanics of how Bitcoin works. 

Bitcoin, the system, is made of tens of thousands of computers that run a specific piece of software. Each computer runs its own local copy of the software and maintains its own local copy of the so-called “coin-ownership database.” Satoshi released the first version of this software after 2 years of working on it (or so he/she claimed). This software’s source code is open, and anyone can modify it, or run it as it is. Many groups of people have modified this software as per their own vision. Each group has their own version of the software, which they hope users will run. 

The key thing to understand is that users decide what version of the software they want to run. All these users’ software together makes up the Bitcoin network. These users are not in a central database somewhere, with phone numbers or email addresses on which they can be contacted and asked to upgrade their software. They are not in a single country or jurisdiction where they can be coerced to upgrade their software, or else. They are spread all over the world in a loosely coordinated arrangement, interacting only through their already installed software. These could have been installed anytime over the last 11 years, and getting them all to agree on what software to run – is a coordination problem of mammoth proportions. Software that runs by itself on a device, while talking to a central server is reasonably easy to upgrade (like a gaming app on a phone). Software that only talks to peers will need other peers to also upgrade and follow the upgraded protocol for things to work. This kind of “protocol upgrade” is much harder to coordinate and enact. Cases in point: (a) the move from IPV4 addresses to IPV6 addresses on the Internet. (b) the disastrous set of upgrades from SSL 1.0->2.0->3.0->TLS 1.0->1.1->1.2->1.3 (SSL and TLS protocols enable the “S” in HTTPS).

The Bitcoin network agrees on a shared coin-ownership database despite every user running their own version of the software. If one user’s coin-ownership database differed from another user, Bitcoin would cease to work. So, how does it work then? This is where the idea of distributed consensus through proof of work comes in. Bitcoin nodes (each computer running the Bitcoin software is abstractly called a “node”) that also validate transactions and assign coin-ownership to users are called mining nodes, and these nodes have to burn enough electrical power to qualify every 10 minutes to propose valid transactions (a “block” of transactions) that the rest of the network accepts. The network rejects this block if it contains invalid transactions. What is valid/invalid was written in software by Satoshi in the first version of Bitcoin, and changing that requires the collective software upgrade that we encountered earlier. Additionally, this notion of what constitutes burnt electrical power is universal in nature, and all nodes can agree on this without relying on any trusted third party. This is the reason Bitcoin burns more power than your friendly neighboring country – to trustlessly determine who owns what through the universal physics of electricity.

But let’s say that some mining node decides to make a block with a transaction that allocates itself some additional money. An invalid transaction, so to speak. Let’s say this mining node can convince half the nodes in the network to change their software and accept that this block is valid. This half would accept this invalid block as valid and update their local copy of the coin-ownership database. The rest of the network would reject this block, and would have a different coin-ownership database. We have what is called a hard fork.

Bitcoin has had many hard forks in its history – almost all of them by design. And none of them with a 50-50 split; all of them were lopsided splits. A few people wanted to change the rules of the game over the years, got a few more people to agree with them, and decided to have different versions of the coin-ownership database. Think of how, before the partition of India in 1947 – there was one Rupee, and a database of who owns how many rupees. This database was, of course, not maintained on a computer – but through ownership of bearer notes. After partition, there were two versions of the Rupee, with two databases of who owns what. Each Bitcoin hard-fork can be thought of as a similar partition of a currency with separate coin-ownership databases going their own way after partition. The fork with the largest set of miners, users, economic value, and other intangible metrics takes the moniker of “Bitcoin.” Others call themselves “Bitcoin Cash,” “Bitcoin Cash SV,”, “Bitcoin Cash ABC” and so forth.

There is also a softer notion of partition called the “soft-fork”, which is a bit more technical and nuanced. Soft-forks do change the notion of what Bitcoin means, but affecting these soft-forks over the entire network takes many years of coordination, and can only be done for the least controversial changes. And there is no guarantee that they might ever see the light of the day. The last successful Bitcoin soft-fork (fork-name: SegWit) was in 2017 and the forking/upgrade process left such a scar on the system that the next fork/upgrade (fork-name: Taproot) though code-complete, and almost entirely uncontroversial, might take years to roll out – if at all.

If they are so hard, how does Ethereum pull off forks? These are some of my reasons (ranked in order of how controversial they could be):

  • Ethereum’s BDFL is well known in real life, very active, and has strong opinions on how Ethereum should evolve. His word commands respect in the community, and is able to affect change. Bitcoin’s creator disappeared in 2010, and has not been heard of since.

  • Ethereum’s nodes are comparatively harder to run, and are thus run by fewer people – who can coordinate upgrades more easily. Bitcoin nodes have a lighter CPU, memory, and network footprint, and can be run by more people.

  • Ethereum’s users want newer features and are willing to upgrade more easily. Bitcoin users are more resistant to change.

What now?

I claim that Bitcoin’s resistance to change is one of its biggest value propositions, and gives us a form of money whose monetary policy, rules of the game, and general contract with the outside world are almost set in stone. You can buy bitcoin, bury the private key, come back to it in 50 years, and it will still be valid, and perhaps, more valuable.

Previously, our intro to crypto:

define: bitcoin

define: ethereum

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Mandates, or lack thereof

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Individual investors’ greatest advantage is that they don’t have to fit into a “style box.”

If you can’t measure it, you can’t improve it. – Peter Drucker

The Industrial Revolution was fueled, in part, by the violent combination of applied statistics and physics. Rapidly improving methods of measurement lead to rapid innovation in both the underlying physics and the resulting machine. And in an era of rapid innovation, managers who could zero-in on the metrics that mattered the most and measure them with decent precision had a large competitive advantage over the innumerate. For instance, if a new type of cotton ginny was invented, you needed a quantitative method to figure out if it was worth replacing the existing ones.

Managers who measured well survived. And those who survived, preached.

Take education, for example. Before the Industrial Revolution, one would simply be an “Oxford graduate.” There were no grades. Once your advisor thought that you were “ready,” you graduated. It was the industrialists who demanded scoring and ranking as a way to fit graduates into roles. And educational institutions obliged.

And it was all downhill from there.

When a measure becomes a target, it ceases to be a good measure. – Goodhart’s Law

While measurement and metrics are helpful in the physical world, it tends to break apart in the social world.

Measuring Investments

The first modern mutual fund was launched in the U.S. in 1924.

CRSP completed the stock market database in 1964.

The CAPM was introduced between 1961 and 1966.

Morningstar Style Box for mutual funds was introduced in 1992.

SEBI finalizes the Categorization and Rationalization of Mutual Fund Schemes in 2017.

For more than 40 years, investors were happy knowing absolute returns – how much was invested, what it is worth now and how long it took. And they were plodding along just fine for more than 70 years without the Style Box. But now, there are a dozen different ways to measure investment returns across an equal number of investment styles. How did we get here?

The Agency Problem

The Agency Problem or the Principal-Agent Problem occurs when one person (the agent) is allowed to make decisions on behalf of another person (the principal).

Within asset management, compensation structures in large part drive managers’ interests, and if these contracts are not structured correctly, managers may have an incentive to act counter to the fiduciary duty they have to their investors. Furthermore, investors’ tendency to focus on short-term performance may indirectly provide managers with additional incentives that exacerbate this problem. The Principal–Agent Problem in Finance

In every bull market, there are a certain class of funds that focus on the meme stocks of that period. These “go-go” funds, focused on growth stocks and other high-risk securities, offer higher risks, but also higher potential returns. Typically, when the bull market eventually comes to an end, investors end up holding the bag while the asset manager would’ve earned enough in fees to retire.

Stakeholder Rights and Obligations

There are quite a few stakeholders in the asset management industry:

  1. The buyer/investor.

  2. The seller/manager.

  3. Independent/Sell-side/Buy-side analysts.

  4. Rating agencies.

  5. The broker/distributor.

  6. The advisor/allocator/consultant.

  7. The regulator.

  8. The tax-payer/government.

As the asset management industry grew, the number of people involved in creating, (re)packaging, advising and selling them grew as well. Often, the interests of each of these stakeholders are in conflict. Increasing popularity of metrics and measurement in the industry is essentially an attempt at keeping these stakeholders honest.

Mandates

A barometer measures pressure. A thermometer measures temperature. Pressure and temperature exist independently of barometers and thermometers. This is true about any physical environment. Social environments are different. Measuring something could very well alter the very thing being measured. This is true about asset management as well.

For example, how should a bond fund manager be incentivized? If it were only to beat an index, then he could just play Russian-roulette with risky high yield bonds – he gets paid for excess returns (every year) when they work and you hold the bag when it blows up (eventually, some time in the future.) So, you put some restrictions on what he can do: only AA or higher with durations less than 3 years; not more than 10% of the fund in the same issuer/promoter, etc.

These restrictions are called mandates.

Mandates drive everything in professional asset management. It sets down a common operating principle and a set of metrics that all stakeholders can agree on.

In fact, the failure of the Indian mutual fund industry to narrow down mandates led to SEBI fixing it themselves. Before SEBI’s edict, it was common for fund houses to have multiple funds in the same category and play the survivorship bias game.

The rational behind Morningstar’s Style Box was the same as well.

Metrics that sit on top of mandates allow stakeholders to rank how individual managers have performed.

Where there is a Match, there is Match-fixing

The problem with mandates is that if you make it too strict, then beating the benchmark becomes nearly impossible and if you make it too lax, then agency problems raise their ugly heads.

US bond fund managers were able to beat their benchmarks mostly by taking additional risks: term risk, corporate credit risk, emerging markets risk, and volatility risk. Traditional discretionary active bond strategies offer little in the way of true alpha. AQR, 2018.

Given that investors care primarily about the most recent three-year performance, the pressure to front-load returns is huge. A case in point is the recent Franklin Templeton debt funds fiasco.

Despite the regulations being clear, some mutual fund schemes seem to have chosen to have high concentrations of high risk, unlisted, opaque, bespoke, structured debt securities with low credit ratings and seem to have chosen not to rebalance their portfolios even during the almost 12 months available to them so far. SEBI’s statement on Franklin Templeton dated May 7, 2020

Metrics are notoriously unstable

Finance doesn’t have immutable laws of nature. The “physics envy” that finance academics have is obvious in the body of research they have produced – precise equations modeling a complex-dynamic-adaptive system. But the desire to tame the beast that is the asset-management industry has lead to too many rigid frameworks and restrictions placed on all the stakeholders.

There is absolutely zero stability in metrics used to analyze mutual fund performance. Whether it is alpha, beta or information ratio, they all vary over time and across market environments. Using them to pick the next “winning” fund is pointless. They are, at best, a measure of what happened in the past. – A quick note on performance metrics

So you have tighter mandates and unstable metrics. But the bigger question is: as an investor, do you want relative performance or absolute returns?

Free your mind

The problem with bucketing yourself as a “value investor,” “contrarian,” “growth,” or “momentum guy” is that you lose the biggest advantage that you have: flexibility and the ability to adapt to the market.

Fund managers, at the end of the day, are only human. They too suffer from confirmation bias. And to make matters worse, once they reach a certain level of fame, all their holdings are closely tracked and their decisions questioned. Once publicly committed to a position, they find it very difficult to backtrack and admit mistakes. You, as an individual investor, have no such pressure.

To top it all, the fund management business is geared towards the accumulation of assets. They are paid a % of assets under management (AUM,) after all. However, size is the enemy of outperformance. With break-evens running at Rs. 100 crore per fund, the “no-go” zones for managers are pretty large. You, as an individual investor, have no such constraints.

There is an oft repeated cliché that you should invest within your “circle of competence.” Most people use this as an excuse to keep fishing in the same pond till the water is dry and the fish are dead. Instead, you should think of it as a call to action. If you are not constantly learning and increasing your circle of competence, then what exactly are you doing with your life?

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Short Squeeze

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Always know if the juice is worth the squeeze

Unless you’ve been living under a rock the last month, you couldn’t have missed the GameStop (GME) short squeeze. A stock that was trading below $3 a few months ago suddenly shot up to $483 before collapsing to $63 yesterday. While the media narrative focused on how a bunch of YOLO traders in a subreddit took on Wall Street, what it really was, was a short-squeeze of epic proportions.

Why short a stock?

There are a lot of legitimate reasons to short a stock.

  1. You think a company is committing fraud. You short the stock and publish a report hoping to convince other investors to short it along with you and draw regulators to investigate the company.

    Twitter avatar for @HindenburgResHindenburg Research @HindenburgRes
    NEW FROM US: Clover Health: How the “King of SPACs” Lured Retail Investors Into a Broken Business Facing an Active, Undisclosed DOJ Investigation cc @chamath hindenburgresearch.com/clover/ $CLOV (1/x)Clover Health: How the “King of SPACs” Lured Retail Investors Into a Broken Business Facing an Active, Undisclosed DOJ Investigation(NASDAQ:CLOV) Today, we reveal how Clover Health and its Wall Street celebrity promoter, Chamath Palihapitiya, misled investors about critical aspects of Clover’s business in the run-up to the comp…hindenburgresearch.com

    February 4th 2021

    711 Retweets

  2. You think a company is headed towards bankruptcy where the stock is going to be worth zero. You short the stock and publish a report hoping to convince other investors to short it along with you1.

  3. You run a relative value or merger-arbitrage strategy. You go long company A vs. short company B, pocketing the spread. For instance:

    IBM’s bid for multinational software company Red Hat is a case in point, he says. ‘Red Hat had declined, its stock had gone down from a $170 peak in the summer to trade at $150 in Q4 and then it dropped to $120 before the IBM bid. So a $120 stock gets a $190 offer and, ironically, the market prices in a wider spread.

    ‘That’s a 60% premium but it wasn’t really much of a premium when you look at where Red Hat had been at its height.’

  4. You are mostly long stocks or bonds and you want to limit your downside by shorting stocks.

  5. You want to express a macro view. For example, if you think the entire housing market is going to collapse, then you can express that view by shorting housing stocks, housing-credit, etc.

Short-selling is an essential lubricant of the markets. It makes the market more efficient2.

When does it go wrong?

The problem with short-selling is that it has always seemed “wrong.” Elected representatives want to be seen encouraging entrepreneurship and short-sellers are the proverbial thorn in their sunny-skies-forever narrative. Over a period of time, this tilt against shorting has rigged the market to overwhelmingly favor longs.

To short-sell (i.e., sell a stock that you don’t own,) you need to first “borrow” it from someone. The lender demands that he be paid a fee for it. And if the stock price goes up, the borrower owes the difference to the lender. Also, in some cases, the lender has the right to recall the securities with little notice (“at call” 3.)

Usually, short-selling is as boring as long-buying. The practice is well understood and usually goes on without a hitch. But ever so often, things tend to go spectacularly wrong.

Asymmetric payoff

Suppose a stock is trading at Rs. 100 and you decide to short it. Your maximum profit is Rs. 100 whereas the person taking the long-side of it has no such limit to the upside. If the stock starts going up, you really have no way of telling what the eventual loss is likely to be. Beyond a certain limit, you’ll try and cover your short by buying the stock back in the market. But what if there are not enough stocks for you to buy?

Liquidity

There is a big difference between total market cap4, free float market cap5 and the number of shares that can be traded without making an impact6. Take Infosys (INFY,) for example.

Its total market cap is Rs. 5,42,24,574.74 lakhs and free float market cap is Rs. 4,71,41,375.59 lakhs. This means that more than 85% of the total number of stocks is available to trade. But on any “normal” day, only a small fraction of it trades. In INFY’s case, its 0.15%. And all this happens with an impact cost of 0.02%.

Now, contrast this to HATHWAY. Its free float is only 6% and about 1% of it trades in a day with an impact cost of ~1%

If you were equally bearish on these two stocks, which one is a better short?

The answer is INFY.

You are not the only shark in the tank

The biggest mistake that most investors make is assuming that they are the only player in the field. But the market is filled with sharks that will rush towards a drop of blood at the slightest hint.

In our example, when you short INFY, given the sheer amount of stocks available in the market, your actions are unlikely to raise eyebrows. However, if you shorted HATHWAY, then things are going to get interesting for you.

The dynamics of a short squeeze

Lets say that you are so bearish on HATHWAY that you decide to short about Rs. 100cr worth of the stock. Assuming that you were conservatively leveraged at 2x, all you had to do was put up Rs. 50cr in capital. But the total free float is Rs. 322cr and only about Rs. 1.7cr in value gets traded every day.

Either the news gets out that someone is short or the hero that you are, you send out a research report on why the company should be worth zero and everybody else should join you.

However, the sharks have their own take on this. It wouldn’t take much to move the price of a stock that trades only Rs. 1.7cr in value a day. Instead of shorting along with you, they decide to buy it. With its high impact cost, even a few small accounts buying 1-10 lakhs every day is enough to push the stock higher.

Now, you are on the clock. Every day, you have to post margin to maintain your short. You see the price go from Rs. 30 to 32, then to 35… 40. A 30% rise in price means that you have lost Rs. 30cr on a starting capital of Rs. 50cr. You decide to throw in the towel and buy some of the stock back. The sharks smell blood and move in for the kill.

There are no stocks to buy.

?? ???

Diamond hands to the moon.

You panic close your short and send the stock rocketing to the moon.

This is exactly what happened to GameStop last month.

Not the first time, and will not be the last

Short-squeezes have been around since the dawn of markets.

The earliest one in recorded history was Piggly Wiggly7, circa 1923. A short-squeeze sent the shares of the department store from $40 to $124. But in typical Wall Street style, when the going got tough, they just changed the rules8.

The shorts were cornered and only had until the next day (Wednesday) to deliver their shares. But then, the rules changed.

The Governing Committee of the Exchange announced a suspension in Piggly Wiggly trading and an extension to the short sellers delivery deadline. Saunders countered and offered a deal of $150 a share for delivery by end of day Thursday and $250 a share thereafter.

Unfortunately, very few short sellers came forward to pay Saunders what he wanted. Then, the Governing Committee delivered the death blow to Saunders. They restricted trading of Piggly Wiggly and gave the short sellers until the next Monday to deliver the shares.

The extension granted by the Committee gave the shorts enough time to find other shareholders across the country (i.e. widows and orphans) who they could buy shares from. Instead of getting paid in dollars, Saunders got the last thing he wanted—more Piggly Wiggly shares.

By the end of day Friday, most of the shorts had covered their positions and Saunders was left holding the bag while still $10 million in debt. He had lost. Wall Street had won.

One of the more memorable squeezes before GameStop was the Volkswagen Infinity Squeeze in 2008. Volkswagen was increasingly being viewed as a potential bankruptcy candidate. However, an orchestrated short squeeze on VW shares caused VW to briefly become the most valuable company in the world, worth more by market cap than Exxon Mobil.

On October 26th, 2008, rival automaker Porsche made a surprise announcement that it had increased its stake in VW to over 74%. It was a stealth move, made possible through the use of multiple purchases of cash-settled derivatives which had been accumulated separately through different European investment banks.

The short interest9 seemed not excessive, at just 12.8% of outstanding shares. But what the market failed to appreciate was that the true availability of tradeable shares to cover those short positions was actually far lower than what many understood.

Around 55% of VW shares were already unavailable in the market for any realistic purposes (mostly owned by index funds and sovereign wealth funds.) As a result, when Porsche increased its stake by an additional 44%, it meant that the true available float went down from 45% of outstanding shares to around just 1% of outstanding shares. Suddenly the seemingly “low” short interest of 12.8% turned in to a massive supply and demand imbalance. Millions of shares needed to be bought immediately even though there were simply no shares available to be sold.

Following the announcement by Porsche, the resulting panic caused a short squeeze in VW shares that saw the deeply troubled automaker briefly become the most valuable company in the world – despite being in the middle of the worst financial crisis since the great depression. VW’s share price briefly exceeded €1,000 intraday with a market cap of over €300 billion.

As a result of its skillful financial engineering, Porsche netted itself more than $10 billion in profits in a matter of just a few short weeks.

On the other side of the trade, the hedge funds who had sold VW short quickly saw their collective losses exceed $30 billion.

The odds are forever against you

Short-sellers have to navigate a lot of asymmetries to emerge successful in the long term.

  1. Most of the world in long-only and that tilts politics against the short-sellers.

  2. The P&L profile is that of unlimited downside vs. limited upside.

  3. Crowded trades end in squeezes.

  4. No company ever hands out bad news if they are not forced to.

  5. The rules of the game can always be changed.

Does this mean that you should go squeeze hunting? Not necessarily:

  1. Short-interest data can be misleading if most of the longs are #neversell or in funds that cannot lend out those stocks to short-sellers.

  2. Most of the time, the shorts are legitimate and squeezing them requires a shift in the zeitgeist.

  3. The reaction of the management when this battle is being fought is a wildcard that cannot be modelled.

In the end, is the juice worth the squeeze?

4

Outstanding number of shares of a company multiplied by its current market price.

5

The value of the company calculated by excluding shares held by the promoters.

6

Impact cost is the cost that a buyer or seller of stocks incurs while executing a transaction due to the prevailing liquidity condition. It varies by transaction size and depends on outstanding orders.

9

Short interest is the number of shares that have been sold short but have not yet been covered or closed out.

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define: ethereum

0

an alternate parallel digital universe

A 17-year old boy looks at bitcoin and sees the possibility of creating a world computer that can run an alternate universe. His name: Vitaly Dmitriyevich “Vitalik” Buterin.

Vitalik dropped out of school in 2014 when he was awarded with a grant of $100,000 from the Thiel Fellowship to work on Ethereum full-time.

To understand Ethereum, one needs to first understand massively multiplayer online role-playing games (MMORPGs.)

Games, Networks and Virtual Universes

Parents have been yelling at their kids since the days of Atari’s Pac-Man about spending too much time in front of the screen.

It will melt your brain! Why don’t you go out and play like normal kids!

Over the last four decades, games got progressively realistic, immersive, networked, multiplayer, and pervasive. People started spending more on games, gaming rigs, and consoles. Video game makers moved away from a one-time, hit-based production system to creating virtual spaces where gamers can write their own story. The metaverse was born.

The metaverse is to game makers that SAAS is to enterprise software. Once a metaverse crosses a tipping point, network effects kick in and revenue explodes. Some gamers, the whales of the metaverse, spend an obscene amount of real money buying virtual goods. Everything is for sale – avatars, dresses, weapons, skills – inside the metaverse.

Globally, recent estimates for annual virtual-goods revenues have totaled over $52 billion.

Gaming evolved into a sub-culture onto itself.

Boredom Kills

Metaverses have a big problem: they can implode if they get boring.

Back in 2003, Linden Lab launched Second Life – an online virtual world. By 2013, it had about one million regular users. Users, or residents, as they are called, can login using client software and create virtual representations of themselves, called avatars, and are able to interact with places, objects and other avatars. They can explore the world (known as the grid), meet other residents, socialize, participate in both individual and group activities, build, create, shop, and trade virtual property and services with one another.

The platform principally features 3D-based user-generated content. Second Life also has its own virtual currency, the Linden Dollar, which is exchangeable with real world currency (wikipedia.)

At the peak of its hype-cycle in 2006, American Apparel had a virtual store and even IBM had set up a “property.”

And then it died.

While media articles on its failure focus on buggy software, missing the switch to mobile, etc, the biggest reason was that it was owned by a company (centralized decision making,) that had to host and pay for the servers themselves (centralized scaling,) and there could be only one Second Life.

Ethereum is a platform on which another Second Life can be created on a distributed network not owned by a single corporation.

Ethereal

In a nutshell, the Ethereum platform allows programmers to write code that runs on a distributed network. To incentivize miners to run the code, they are paid in Ether (ETH.)

The code is called a smart-contract and to run it, you need to supply it with ETH. The code will do the work and consume the Ether. Both the code, and the ledger keeping track of ownership of the Ethers, are on a blockchain.

Technically, the code runs on many computers across the world, computing and storing data locally, but networking globally, to create a distributed ledger which is sometimes also called “a blockchain”.

With these basic building blocks, one can construct self-contained virtual worlds with virtual goods, etc.

Cryptokitties

CryptoKitties was the first mainstream use case for Ethereum’s blockchain. It operates as a non-fungible token (NFT), unique to each CryptoKitty. Each CryptoKitty is unique and owned by the user, validated through the blockchain, and its value can appreciate or depreciate based on the market. These virtual kittens (tokens) are also traded on crypto exchanges.

What is fascinating is not just the technology but the storytelling that made it real. The kittens are unique, supply-constrained, have traits (some of which are rare) that can be passed on through breeding, etc. There is an ecosystem of tastemakers and specialists around it that keep the story alive. And consumers willing to part with real money for virtual kittens.

DeFi – Decentralized Finance

Imagine a global, open alternative to every financial service you use today — savings, loans, trading, insurance, and more — accessible to anyone in the world with a smartphone and internet connection.

There are DeFi dapps that allow you to create stablecoins (cryptocurrency whose value is pegged to the US dollar), lend out money and earn interest on your crypto, take out a loan, exchange one asset for another, go long or short assets, and implement automated, advanced investment strategies.

This is a nightmare for regulators like SEBI and the RBI who are tasked to protect consumers. Who are you going to sue and who are you going to jail when there is no “owner” as in the real world?

For better or for worse…

Ethereum is the biggest crypto-currency after Bitcoin. There is a large ecosystem around the infrastructure breathing life into this alternate parallel virtual universe. It is here, it exists, and it is growing.

Some think that the current economic and political order is an accident of history. What if we had the opportunity to evolve an alternative? What would it look like? Don’t we owe it to ourselves to find out?

We leave you, dear reader, with these thoughts and a recording of our fascinating conversation with someone who is working on a PhD in crypto-currencies and who also happens to be a dear friend of mine. Enjoy!

Further reading: An Economic Analysis of Ethereum

Previously: define: bitcoin

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