First time investors often get bedazzled by tall claims of “20%” returns in direct equities. All they need to do is subscribe to an “exclusive” telegram channel or advisory service and mint their way to millions. Even if these claims were true, gross returns – the number often marketed – has little to do with the net returns that the investor finally realizes at the end of the year.
Very few know that a high-churn portfolio that delivers 20% gross returns is equivalent to a mutual fund that delivers 14% net. So, who ate your cheese?
Layers of Transaction Taxes
Securities Transaction Tax (STT)
The STT is an automatic tax collected by the government on all transactions irrespective of whether you made money on it or not. On equities, it is currently set at 0.1% – if you bought & sold 1 stock worth Rs. 100, then the government collects 20p on it. This is one of the biggest drags on high-churn strategies.
Last year, the government collected ₹16,927 crore in STT.1
Exchange Transaction Charges
The trading venue, typically the NSE (National Stock Exchange) or the BSE (Bombay Stock Exchange,) levies a transaction charge for allowing you to trade through them. This varies by exchange and they are know to give rebates to high volume brokers to keep them loyal. The last time I checked, it was around 0.00345% on the NSE.2
Stamp Duty
When the Central Government is skimming off through STT, why should State Governments be far behind? The states too have their hands in the till through “stamp duty.”
Stamp duty is a state levy paid to register a document, typically an agreement or transaction paper between two or more parties, with the registrar. In an era where all transactions are electronic and registering transactions is just flipping some bits in a database, this is basically free money to the states.
Before 2020, every state had its own rate but thankfully, the Modi Government rationalized it to a common rate of 0.015% on the buy-side of equities.3
SEBI Turnover fees
If you though that SEBI was an arm of the government and should be entirely funded by the general budget, the joke is on you. If you have a look at your contract note that the brokers sends you on the days that you trade, you’ll find a “SEBI Turnover Fee.” This is 0.00015% on both buys & sells. While its one of the smaller taxes/fees on transactions, it is still a percentage of total volume, so it adds up over time.4
During 2019-20, the total amount of fees and other charges collected by SEBI was Rs. 608.26 crore.5
Short-term and Long-term Capital Gains Tax
The rationale behind STT, introduced in 2014, was to replace the long-term capital gains tax. It was said that there was a lot of “leakage” in collecting LTCG and that a tax on transactions collected directly by the exchanges would plug it. However, the 2018 budget saw the re-imposition of LTCG.6
However, if your strategy demands churn, then you need to be worried more about STCG (15% on profits) than on LTCG (10% on profits.)
A High Bar of Direct-Equity
After all these taxes, levies and charges, when the numbers are tallied up at the end of the year, most direct-equity investors would be better off with a mutual fund.
The napkin math (sheet) above doesn’t consider brokerage – since those are mostly zero – and DMAT charges – those charged by CDSL – since those are flat fees charged only on sales.
Direct-equity investing strategies need to walk a fine line between optimizing for lower transaction costs, risk management and taxes. This is where we find advisory disclosures lacking. Most advisors do not disclose portfolio churn rates and nor do they indicate what the net, after-tax, returns would look like.
Also, a mutual fund’s NAV includes all of these charges and your portfolio compounds tax-free until you redeem. So, if you have a 5+ year time horizon, then compounding the 15% STCG adds significant tailwinds to your portfolio.
Conclusion
While comparing different strategies, investors should also consider portfolio churn and try and back into what the net, after-tax, returns would look like at the end of the year. Know that mutual fund NAVs are net of transaction costs and can compound tax-free.
Direct-equity strategies should clear a high-bar.
Looking for a sensible way to invest? Here’s how to get started.
or: How I Learned to Stop Worrying and Love Nation State Attacks.
Bitcoin’s secret sauce, and how it works, was on full display these last few weeks. Bitcoin was designed to work against the most powerful of adversaries, and boy – did the adversary show up!
The China Syndrome
A few months ago, 45% to 75% of Bitcoin mining happened inside China. Then the Chinese government banned it.
There are anecdotal accounts from people on the ground are seeing Bitcoin mining operations being shut down by law enforcement agents. And there are similar accounts from people on the ground elsewhere in the world where containers full of mining hardware are being shipped to, lock, stock and barrel.
And then there is the Bitcoin blockchain – the source of absolute truth.
I have a copy of the Bitcoin blockchain on my computer, and could actually run the numbers myself and see that the production of Bitcoin blocks slowed down dramatically. Here’s a plot of how long it took, on average, to find 2016 blocks from 12-May-2014 to 18-July-2021.
Bitcoin blocks, on an average, are supposed to be generated once every 600 seconds. But you can see the spike in this number on the graph towards the end, going all the way up to 832 seconds. This means that during that period, the total number of active miners went down dramatically, and that led to the inter-block average-gap increasing equally dramatically from 600 seconds to 832 seconds.
Putting the anecdotal and canonical sources of data together, we can be reasonably certain that the Chinese mining ban lead to a global drop in Bitcoin mining.
Does it matter?
Not really. Miners come, miners go – Bitcoin chugs along. That is what it is designed to do. Bitcoin targets a block production rate of 600 seconds per block. If Bitcoin’s design had been naïve, whenever its dollar value went up, more miners would enter the system to make more money, and blocks would arrive faster than 600 seconds. Similarly, if its value went down (or if governments kicked them out), miners would leave the system, and blocks would arrive much slower than 600 seconds. The block production rate on either side of 600 would persist, and reflect the total number of miners in the system.
But no, that’s not what happens. No matter how many miners are in the system, it always takes around 600 seconds to mine a block. This is done through the difficulty adjustment algorithm, also known as Satoshi’s stroke of genius.
Before we get to the difficulty adjustment algorithm, we have to first understand why keeping the inter-block interval of 600 seconds is important. Bitcoin works because everyone can check whether their perceived ownership of their own Bitcoin is fact or fiction. To check this, you need access to Bitcoin’s data? Where is this data? How big is it? How do I access it? Bitcoin’s data is not held by some central custodian, or a bank. It’s held by everyone who is interested. It includes all transaction from the genesis block onwards – from January 2009. But storing everything with everyone sounds crazy – and to be honest, it is crazy. But the more you think about it, the more you realize that there are no other easier ways of doing self-validation, other than offloading the “do I control my money or not?” question to someone else – and trusting them. Bitcoin prefers the opposite: self-validation.
So, if we accept the crazy idea that everyone stores a copy of the blockchain, we have a fundamental tradeoff – the blockchain cannot get very big (by growing very fast). It also cannot stay static: new transactions need to be added every so often to facilitate economic activity. Currently, the blockchain is around 377 GB, and growing at around 50 GB per year. If it grows too fast, not everyone will be able to hold their own copy. If it doesn’t grow fast enough, there is not enough transaction space to accommodate the demand for transactions. Under these constraints, Satoshi decided that a 1MB block every 10 minutes is a good tradeoff. To keep this tradeoff constant, blocks cannot be generated slower or faster.
What happens if Bitcoin’s value skyrockets and everyone wants to be a miner? Remember that a miner who generates a new block gets to keep the newly minted Bitcoin that comes out of each block. So, if the value of Bitcoin goes up, expect more miners to materialize. To accommodate this, Satoshi designed a simple algorithm that makes mining harder or easier depending on how long it takes to generate the previous 2016 blocks.
The Bitcoin protocol contains a positive number called “difficulty”, whose value is currently 13,672,594,272,814. This number controls how hard or easy it is to mine a block. Let’s say the total time taken to mine the previous 2016 blocks was greater than 2016 times 600 seconds, by a factor of X. This difficulty number is then adjusted lower by the same factor X. If the time taken to mine the previous 2016 blocks was lower, the difficulty number is adjusted upwards – again by the factor X. That’s it.
As far as “algorithms” go, this is as simple as it gets. It’s middle school level arithmetic. Other than combining existing ideas from cryptography and distributed systems, Satoshi’s only novel contribution was this middle school level formula. The genius, as they say, is in the simplicity of it.
When these erstwhile Chinese miners turned down their mining hardware around end of June/beginning of July 2021, Bitcoin’s mining difficulty dropped from 19 trillion to 14 trillion, by around 5 trillion – which is around 28%. The reduced difficulty made it easier for the remaining online Bitcoin miners to start generating blocks every 10 minutes again. The next 2016 block average was 630 seconds. Voila!
As Bitcoin’s value increased from 0 to wherever it is today, miners have only entered the system – and have rarely left. Difficulty has always gone up – to accommodate this increase in value. So, how does this difficulty number actually make it easier or harder to mine a Bitcoin block?
The Proof of Work Function
Bitcoin, famously, relies the “partial hash-preimage puzzle” to build its Proof of Work function:
You double hash data from the block you want to generate, and check if that hash value is less than the target on the right hand side of the equation. If it’s not, you change the block data, and try again, and again, and again, and again.
For example, if I double hash make-believe block-data, say the string “Bitcoin forever!”, I get the number:
So, it doesn’t work. I need to keep trying the function again and again with different block-data to hit gold. The actual previous Bitcoin block’s hash was 888160945014446794317532755205888398236464272495427689, which is under the required target, and that miner struck gold – so to speak.
If the difficulty number goes up, the mining target goes down, and finding block-data that double-hashes to a number lower than that target gets harder. It’s like tossing a 6 sided dice and wanting to hit a number less than or equal to 1. It happens only once every 6 times. If difficulty were to reduce, the target would move to a number less than or equal to 2. That happens every 3 times – mining just got easier.
Why go into the nitty gritty details of this function, with all the associated arithmetic and probability? I want to get into the properties that this unique function has, that makes it ideal for Bitcoin mining – and resisting nation state attacks.
Parameterizability: The function provides very fine degree of control over how much harder or easier we want the function evaluation to be. If you increase or decrease the difficulty number, the function becomes easier or harder to evaluate, respectively.
Memorylessness or Progress-free ness: Even if you have already run the function a million times, it still doesn’t give you any advantage over the next run. Each run of the function is what is called a Bernoulli trial – with the odds of hitting gold the same no matter how many times you have tried in the past. This makes sure that larger miners have no other advantage than just the larger chance of producing a block. If this property weren’t there, the largest miner would *always* win, even if they had just 0.0001% more power than the next largest miner.
The other incredible advantage of Memorylessness is that a miner can be turned off, put in a container, shipped elsewhere and plugged back in. The only loss the miner incurs is the Bitcoin that could have been mined in that interim time when the machine was turned off. Most physical objects being built, or even computations that are being performed on computers rely on previous data or “progress” that has been done, stored and retrieved, so that we can continue the process further. Shutting down something abruptly, without needing to store any state of progress, and starting elsewhere without any extraneous loss is not that common. This allows Bitcoin miners to be incredibly mobile and seek out the cheapest electricity wherever it exists. They are, in the true sense, plug-and-play.
Hard to compute, but easy to verify: To get the double-hash value which is under the target needs millions of trials of the function. But once someone finds it, the rest of us can verify it immediately with just a single iteration of the function. This, again, makes decentralization possible – where all of us can run the Bitcoin software on our computers and check that the miners are doing the right thing.
Replacing this function is not that easy. Most attempts have kept the general idea, and have tinkered with the specifics.
Conclusion
A nation state the size of China attacked Bitcoin where it’s supposed to hurt: Bitcoin Mining and all they managed to get in return was a giant shrug of indifference by the protocol. Yet another instance of Bitcoin living up to its promise of being designed to last forever. This self-adjusting nature of Bitcoin – that makes it change itself based on market conditions, with no one central entity being in charge – separates it from all other forms of money. Fiat money always has a central planner. Bitcoin has a protocol.
There are quite a few reasons why Indians would want to invest overseas. Education, retirement and emigration are frequently cited as top priorities. In the past, the only way to do this was through the Liberalised Remittance Scheme (LRS) route. However, with Indian mutual funds finally waking up to increasing demand from investors, does investing in international public market securities through this process still make sense?
Liberalised Remittance Scheme
The Indian Government, through its various regulatory and enforcement arms, have traditionally tried to keep Indians from sending money abroad. The problem has always been that populist policies used to win elections end up choking growth and stoking inflation. This leads to investors pulling funds away from India – aka, capital flight. One way to stem the tide is to try and trap Indian capital within India.
We use the word “try” because we are all aware about the hawala network that thrives to this day because of these policies. Thankfully, the process of liberalization has slowly, in baby steps, opened the doors for Indians to legally remit funds abroad.
The Reserve Bank of India (RBI) sets the rules governing these fund transfers that banks need to follow. And banks are supposed to report and track these transactions both at the individual and aggregate levels. Given the paperwork involved, most banks require you to make a trip to a “designated” branch office and execute the instruction in-person. The whole process is cumbersome, requires paperwork and takes an hour or two to complete.
Not only is LRS is painful, it is also expensive.
Most people fixate on bank fees and GST but that’s only part of the story. The biggest scam is the exchange rate given by the bank – it is the worst possible rate that they can give you while still being compliant with rules & regulations. If you compare the “google” rate with the final transfer rate, you’ll find that the drag is about 3%
So, why do it?
More Choice, Less Cost
The US ETF market went through a decade-long price war that drove vanilla cap-weighted fees to almost zero.
For example, if you want to invest in the S&P 500 index, then Vanguard’s VOO ETF charges you 3bps for the privilege whereas Motilal’s index fund charges 50bps. If you consider the tax differential and the transfer knee-cap, you break-even by year 7. So, if you are a passive, buy & hold investor with a long enough time horizon, LRS makes more sense.
While costs are important, so are choices. You can access strategies beyond what Indian mutual funds deign to offer in the local market. For example, there are a ton of factor strategies available through ETFs that are probably never going to be launched in India.
Indian policy makers love to ape Western European policies without giving a second thought to its appropriateness given our stage of growth. One such self-goal has been the STT – Securities Transaction Tax – that taxes transactions rather than profits. And yes, we tax both short-term and long-term capital gains. Sort of like a dare: We’ll see how you’ll make money trading.
Fortunately, the US has avoided shooting itself in the foot so far.
Lets say, you fall in the 30% income tax slab. You have a trading strategy that makes 20% returns in both markets. The strategy turnsover the portfolio “x” times. Given 0.01% STT in India and zero brokerage in the US, what is “x” for you to be indifferent in Year 1?
If you turn over your portfolio more than 60 times, you would be better off deploying that strategy in the US rather than India.
If you set the gross returns to zero, the required turnover drops to 30.
However, if you only trade infrequently, then LRS may not the best way to go. For example, a 40x turnover strategy will need 3 years to be indifferent.
Basically, if you are going to trade frequently, doing it in the US makes a lot more sense.
Caveats
LRS ensures that you will need a Chartered Accountant to do you taxes. You need to account for the dividends you have received, report your net personal assets, etc. So this route doesn’t make sense for small accounts.
If you don’t share your trading and banking passwords with your next-of-kin, then you need to be worried about US Estate laws. The U.S. has jurisdiction over U.S.-situated assets and requires executors for nonresidents to file an estate tax return if the fair market value at death of the decedent’s U.S.-situated assets exceeds $60,000. Directly investing in U.S.-situs assets as a non-U.S. investor creates potential U.S. estate tax liabilities.1
Conclusion
We feel that the LRS route is attractive both for a buy & hold investor as well as an active investor with an edge. However, one should get into it knowing the trade-offs involved.
If you are looking for simple, pre-canned investment strategies to invest in the US, check out freefloat.us
For the longest time in the US, actively managed mutual funds ruled the roost. Then came Jack Bogle with his index fund and the ceaseless mantra of “costs and taxes matter” and the dynamic shifted, slowly at first and then suddenly, in favor of indexing. It was only a matter of time before people figured out the tax loophole of ETFs and now, there are over 2500 ETFs listed in the US.
Unlike in India, where mutual funds are “pass through,” US mutual fund investors pay capital gains tax on assets sold by their funds. When there are large-scale redemptions, say, during a market melt-down, funds are forced to sell their holdings. This generates capital gains taxes, meaning that investors have to pay tax on assets that had fallen sharply in value1.
ETFs, on the other hand, don’t have to subject their investors to such harsh tax treatment. ETF providers offer shares “in kind,” with authorized participants serving as a buffer between investors and the providers’ trading-triggered tax events.
A Plethora
Of the ETFs that survive today, the number of launches every year has trended higher.
While Equity ETFs dominate launches, the share of fixed income, alternatives, etc. has increased as well.
Most of the AUM resides in “vanilla” strategies – typically market-cap based.
The winner HAS taken all
Plot the assets of each ETF, in billions, in log-scale and you can tell that this is a game of scale.
Of the total 2577 ETFs, 2022 (78.5%) have less than a billion dollars in assets. You need to filter for $10 billion and up to just see the x-axis.
The top 3 issuers: Blackrock, Vanguard and SSGA manage ~80% of all ETF assets.
Where there is an ETF, there’s an Index
Until last year, ETFs were supposed to be a “passive” entity. There were no “actively managed” ETFs. In order to be passive, an ETF needed to follow an index. And indices had to be rules based – however convoluted the rules. And issuers needed a third-party to provide the index.
The rise of ETFs (and passive investing, in general) put index providers in the middle of all the a action. They became a crucial cog in world finance that can make or break entire economies. So powerful, in fact, that China blackmailed MSCI to include its domestic stocks in its Emerging Markets Index, which is tracked by close to $2 trillion in assets2. And India has been working on inclusion of Indian sovereign bonds in global bond indices3.
We can see industry consolidation here as well. The top 5 index providers control ~75% of ETF AUM (more if you include index funds.) S&P Global and MSCI are as close to “pure-play” index providers as you can get and their stock market performance is off-the-charts.
Fee Squeeze and Innovation
The problem with index ETFs/funds is that buyers only care about two things: expense ratio and tracking error. This resulted in a massive fee war that saw the vanilla-passive industry consolidate around Blackrock and Vanguard. For example, Vanguard’s S&P 500 ETF’s expense ratio is 3bps.
So, what next?
International ETFs
The first wave was ETFs providing international diversification. However, the “home-bias” is pretty strong with AUM under international ETFs barely making a quarter of the total.
On a weighted average basis, these ETFs charge about 30bps. However, since these are mostly cap-weighted, the fee-war is just as intense here.
Leveraged/Inverse ETFs
Many investors have mandates that prevent them from trading derivates outright. This is especially true for Indian investors taking the LRS route to invest in the US. However, Wall Street has your back.
Leveraged ETFs give you 2x or 3x the daily returns of a benchmark index like the S&P 500 or the Nasdaq 100. Feeling bearish? Inverse ETFs do the opposite.
Caveat: These are NOT buy-and-hold investments and are more suitable for day-traders. The discussion requires a separate post.
On a weighted average basis, these ETFs charge about 100bps. While lucrative, they are mostly niche.
Active ETFs
An ETF’s tax-free wrapper make it an order of magnitude more attractive than an identical mutual fund. New issuers/managers have taken advantage of this and launched actively managed ETFs.
On a weighted average basis, active ETFs charge about 50bps. These are still early days for this category – they barely make 5% of total ETF assets. Liquidity and tracking errors during market crisis are yet to be tested.
Conclusion
There is a plethora of choices when it comes to ETFs in the US. If you plan to wander away from the plain-vanilla stuff, please take the time to read the prospectus and understand how it works.
If you are looking for simple, pre-canned investment strategies to invest in the US, check out freefloat.us
Define Governance: the act or process of governing or overseeing the control and direction of something (such as a country or an organization).
In this article, I will focus on whether any organization can have decentralized governance, and what does that even mean? And how is this related to cryptocurrencies. Let’s start with a very basic organization, and see whether it can be governed in a decentralized way.
What is an organization anyway?
Say some people want to pool their money and use it for charity. We have ourselves a rudimentary organization. During the organization’s inception, the founders make some bylaws – for example: for any charitable donation to happen, say 2/3rd of the remaining capital in the pool has to approve it. These bylaws are written down formally in a “human language” (the language being a “human language” is important). The organization will register itself with the government of that geographical area (let’s say, a country). In case disputes arise in the future, the courts of that country will interpret the bylaws of the organization, apply the relevant common laws of that country, and with the threat of force, ask the members of the organization to abide by the court’s judgment. We kind of get how this works.
I will call this “centralized governance”, because the dispute resolution is adjudicated by a centralized authority. In an ideal world, this centralized authority is fairly appointed by representatives of the people who were fairly elected by the people to carry out such appointments.
Enter Smart Contracts
If the bylaws were precisely written down in an unambiguous computer language, and deployed on a distributed computer that could not be stopped, or taken over by any single authority – we have a decentralized organization. It’s governance is encoded in the program that was deployed on the distributed computer. Ideally, once deployed, the program cannot be changed, and can be arbitrarily run by anyone forever. Who are the members of this organization? Let’s say the program has a function that accepts money as input, and gives out an equivalent valued token – anyone who makes such a function call is a member of this organization, as they have a stake in the program. Do disputes arise in such an organization? No. To see why the answer is “no”, we have to understand that this system adheres to the maxim: “Code is Law”. The program does exactly what it was programmed to do – there is no randomness or discretion or uncertainty in the execution. This faithful execution of the program obsoletes the idea of dispute resolution.
Ethereum smart contracts are such programs. They are deployed and run on Ethereum, which is a distributed network of computers that ideally cannot be censored or stopped. Ethereum has a richer programming language, along with the notion of a smart contract having monetary deposits, and other arbitrary data. Using this setup, one can write a smart contract that represents the charitable organization that we saw earlier. In fact, back in 2016, when Ethereum was still in its infancy, exactly such an organization was deployed as a smart contract on it. It was called The DAO, or the decentralized autonomous organization. It could accept funds from anyone, and with token holders voting for projects, would fund these projects from the collective pool of funds. Venture capitalists thought that the DAO would disrupt the VC industry itself, and added their own funds into the pool. At its peak, the DAO had 14% of all of ETH pooled inside it (ETH is the native currency of the Ethereum system). I didn’t read the code of the DAO, and am not sure how a project got actual funding – was some ETH moved to the recipient’s address? How would the DAO verify that the recipient actually produced something of value, if that artifact was not native to the blockchain itself? In the cryptocurrency space, it’s important to ask these questions – as the answers are not obvious, and often times hide red flags that indicate possible scams.
But as it turned out, this DAO program itself had a software bug, and that allowed a clever hacker to drain the uninvested funds into their own control. To “fix” this “hack”, people who had enough social clout in the Ethereum ecosystem managed to undo history, and start an alternate timeline where this hack never happened.
What?!?!
How does one undo history and make alternate timelines?
Let’s start with an example. Let’s say your credit card is stolen, and is used to buy strange things in strange lands. You call your credit card issuer and ask them to undo history, and start an alternate timeline where the theft never happened, and you have a clean slate of your own previous transactions and new transactions. Where did the thief’s transactions go? Turns out that they were never “settled”. In the traditional finance world, very very few transactions are actually “fully settled”. Transactions between countries, or between large banks, or those that are brokered by central banks are considered settled for good, and are truly irreversible. The rest of the world’s transactions can be reversed, if the right people are convinced.
In Ethereum, where code is supposed to be law – alternate timelines should not have been possible. The hacker took out the pooled funds from the DAO because the smart contract allowed that to happen. That’s the bylaws of the contract, and the hacker is playing by the rules. There shouldn’t be a discretionary voice that says “But that’s not the spirit of the law”. Smart contracts are only supposed to respect the word of the law, and not the spirit of the law. Ethereum, in its early days at least, believed that the spirit of the law mattered more than the word of the law, and allowed the DAO hack to be “bailed out”.
Ethereum is just one such “network computer” (blockchain, to keep up with the times) that runs such code-is-law smart contracts. There are other blockchains that claim to do the same, and have varying degrees of centralization that allows the powers-that-be to “bail out” certain contracts if shit his the fan. On the other hand, Bitcoin doesn’t even allow such powerful smart contracts, and the rudimentary smart contracts that it does allow, have never been reversed because some people lost their money. I think it’s an important distinction that makes Bitcoin the most (if not the only) credible blockchain in existence, but that’s just me.
Governance, through code
Coming back to Ethereum smart contracts which act as decentralized autonomous organizations, how can governance rules be changed if all token holders agree to it? We now get into some of the more sophisticated governance models for smart contracts, which can all be coded into the initial smart contract itself. Here’s one popular model:
In our original charity smart contract, we had the initial bylaw that 2/3rds of the total pool had to apply every new donation. Let’s say we want to change this rule to have 3/4 instead of 2/3. While writing the initial smart contract, this particular constant (2/3) is delegated to a different smart contract that is deployed first, and the main smart contract calls this other smart contract to perform it’s actions. In software programming, this is either called “delegation” or “forwarding” or “a pimpl – pointer to an implementation”. The difference between a classic software program that does this, vs a smart contract that does the same thing – is that in a smart contract with decentralized governance, the change in implementation of a functionality has to be voted by token holders. This is how it looks:
The initial smart contract is written in such a way that the following steps are supported.
Someone (doesn’t matter who) codes a new piece of functionality and deploys it on the blockchain. For now, this is dead code, as no one is executing it. But everyone can see what it does.
Someone (again, doesn’t matter who) makes a proposal in the original contract that they would want to call a vote for this new functionality from step (2) to replace the equivalent step in the original code.
There is a timeline for token holders of the smart contract to vote for this proposal. Votes are tallied. The result is known.
If the governance change is approved, there is an additional time window before it comes into effect. Token holders who are unhappy that this change was made can withdraw their capital from the pool by returning or burning the tokens.
The governance change is affected by changing the smart contract implementation of this functionality from the original to the new.
Many smart contracts on Ethereum have the so called “governance token” that allows token holders to change the rules of the smart contract if enough such token holders vote for it.
Uniswap, the popular decentralized exchange on Ethereum, has its own governance token UNI, which allows UNI holders to vote for governance changes like increasing or decreasing the fee taken by the protocol per exchange trade.
Compound, a smart contract for credit issuance on Ethereum, has its own governance token COMP, which allows COMP holders to affect governance changes – like how they recently voted to change their price oracle.
MakerDAO, the smart contract behind the stable coin DAI, has its own governance token MKR, which allows MKR holders to change the parameters of the DAI stablecoin, and how it maintains its 1:1 peg against the USD.
In my naïve unqualified opinion, these governance tokens can sometimes pass the Howey test, and could qualify as securities under some regulatory regime.
What’s in it for me?
Many tokens/coins are available to buy on many cryptocurrency exchanges.
Some are native coins of their own blockchains – like BTC/ETH. Many of these native coins are centralized, issued to investors first, and dumped on the general public later.
Some are ERC-20 tokens on the Ethereum blockchain. They represent governance rights on protocols, and thereby generate cash flow.
Some are tokens on other blockchains. Most blockchains’ native currencies themselves are worth nothing. Tokens that are launched on these blockchains are even trickier.
Some are even more complex tokens issued by smart contracts that govern other smart contracts.
Some tokens are blatantly pointless, and are valuable just as collectibles: remember NFTs?
Some tokens have a point, but are still worth nothing.
Some tokens have a point, and might be worth something.
To keep life simple, one can just buy Bitcoin. If that’s too conservative (it’s not), maybe add ETH to the mix (don’t).
