Bitcoin halving and the efficient market hypothesis in one article

As Bitcoin’s May 2020 halving date approaches, there is a heated debate among Bitcoin traders over whether the market is anticipating the change in Bitcoin issuance.

Those who downplay the impact of this issuance change often cite market efficiency. As a result, the concept has attracted a great deal of hatred and debate. Disagreements are often difficult to resolve, with straw man versions of the EMH (Efficient Market Hypothesis) already being proposed, and parties unable to agree on a shared definition. Mutually understood concepts are a prerequisite for healthy debate. Since this concept is widely misunderstood, I thought I should explain it from the beginning.

Origins of the Efficient Market Hypothesis

The efficient market hypothesis is credited to a number of thinkers, including Benoit Mandlebrot, Louis Bachelier, Friedrich Hayek, and Paul Samuelson. Hayek's The Use of Knowledge in Society is useful background reading on the concept, although it never specifically mentions the efficient market hypothesis.

In a seminal article, he argued for the development of a distributed, market-based economy over a centrally planned one. Key insight: Markets are an information aggregation mechanism that no central planner, no matter how skilled or well-resourced, can rival. Consider the following passage (emphasis mine):

"There is undoubtedly a very important but unorganized body of knowledge which cannot possibly be called scientific in the sense of general rules of knowledge: the knowledge of the particular circumstances of time and place. It is precisely in this respect that each person has some advantage over the others, because he possesses peculiar information which can be used beneficially, but only if the decision is left to him or is introduced with his active cooperation.

…and the shipper who makes his living by the empty or half-full sailings of tramp steamers, or the real estate agent whose whole knowledge consists almost entirely of temporary opportunities, or the arbitrageur who profits from local differences in the prices of commodities, are both performing very useful functions based on special knowledge of fleeting circumstances unknown to others.”

In the highlighted section, you can begin to see how Hayek viewed markets: forces that aggregate a large number of different opinions and expectations into prices. Hayek understood market-derived prices as information—a particularly high-information signal source. The beauty of markets, in Hayek’s view, is that individuals participating in economic activities send signals in the form of prices simply by selfishly acting in their own self-interest. The efficient market hypothesis focuses specifically on financial assets, arguing that investors collectively provide relevant information, which is incorporated into prices through the trading mechanism.

Following Samuelson’s 1965 work that proved that stock prices could reasonably be expected to move randomly, legendary finance scholar Eugene Fama finally codified the efficient market hypothesis in 1970 (you may have heard of the Fama-French model). In a paper titled “Efficient Capital Markets: A Review of Theoretical and Empirical Studies,” Fama defined efficient markets as markets where “prices always fully reflect” available information.

The EMH is not a mysterious statement. It just holds that market prices reflect available information. That’s why academics often call them “information efficient markets.” Efficiency refers to the diffusion of information.

What does this really mean? It simply means that if there is new information relevant to an asset being traded, that information tends to be incorporated quickly into the price of that asset. If you can reasonably imagine future events that will affect prices, they will be incorporated into the known prices. Markets don’t wait for (knowable) events to occur – they anticipate them. This means that if weather forecasts predict a hurricane will appear and devastate sugar plantations next week, speculators will bid up the price of sugar today, anticipating the supply shock. Now, of course, when there are unpredictable external shocks (imagine a hurricane that hits without warning), then prices can only react in real time because the information is known. The speed with which information is incorporated is one of the tests of efficiency.

Despite its simplicity, the EMH tells us a lot about how markets work. Markets are efficient if prices incorporate new information quickly. Predictable, future market-moving events tend to be incorporated into prices in advance. Importantly, one of the consequences of the EMH is that once all relevant information is incorporated into prices, all that remains are random fluctuations, or so-called “noise.” This means that, although asset prices will still fluctuate in the absence of new fundamental information, these fluctuations themselves contain no information.

Finally, the difficulty of presenting unique new information (not yet incorporated into the price) often varies depending on the sophistication of market participants and the liquidity of the asset. This explains why you might be able to find an edge in an obscure micro-cap stock, but not necessarily when predicting Apple's stock price.

Since Fama’s paper was published, coupled with popular books on the subject like Burton Malkiel’s A Random Walk Down Wall Street, a fierce debate has raged over whether active management is worthwhile. In fact, because the efficient market hypothesis has had such a hard time finding a consistent edge, many investors have begun to question whether actively traded investment vehicles like hedge funds and mutual funds make sense. Over the past decade, trillions of dollars have flowed out of such “active” stock picking strategies and into passive investment vehicles that simply seek to track the performance of the market as a whole or a specific sector. This is one of the most critical debates in finance right now, and it’s driven largely by the growing recognition that markets, in general, are efficient.

Description of the Efficient Market Hypothesis

I have a slight quibble with the “assumption” part of the EMH. If it were up to me, I would call it the efficient market model, not the hypothesis. That’s because it doesn’t contain an assumption. It doesn’t make a specific testable claim about the world. As mentioned earlier, the efficient market hypothesis assumes that market prices reflect available information (which, as we’ve noted, is the primary purpose of markets). Interestingly, Fama called it the efficient market model, not the hypothesis, in his 1970 paper. He seems to have had the same intuition.

I also think the EMH is a bit tautological. Looking back to Hayek, we know that (free) markets measure society’s net information position about various assets. So if we replace “market prices” with “centralized information output” in the EMH structure in bold above, we get the following:

Centralized information output reflects available information.

This certainly sounds tautological. But this does not make the model any less useful. Rather, it means that to object to the EMH is to question the nature of markets themselves. In fact, most criticisms of the EMH (which I will cover in a few posts later in this article) usually cover situations where markets do not clear for some reason. So if you accept that the EMH is tautological, then "efficient markets" sounds redundant. In fact, the default state of (free) markets is that they are efficient, because that's why we have markets. Markets compensate people for finding relevant information. If they weren't efficient by default, we wouldn't bother with them.

It is a useful way to think about markets, to think of it as a model, an abstraction of the world, a description of how markets should (and typically do) work, but by no means an iron law.

Let me be clear, I do not believe in the “strong form” of the efficient market hypothesis. No financial professional I know does. The strong form holds that markets reflect all information at every moment. If that were true, there would be no hedge funds or active money managers. No one would bother to study Apple’s quarterly report or to evaluate the prospects of an oil discovery in the Permian Basin. Obviously, the strong form is untenable given that we have a large active asset management industry with many very smart individuals constantly seeking new information on a wide range of assets.

To be honest, EMH is not something you "believe" or "don't believe". The choice is whether to understand markets as a useful information discovery mechanism, or to reject the usefulness of markets altogether.

There are certainly conditions that lead to market inefficiency. Fama acknowledged this in his 1970 paper, when he named transaction costs, the cost of obtaining relevant information, and disagreement among investors as potential harms to market efficiency. I will discuss two here: the cost of surface material information, and the frictions inherent in actually expressing market opinions.

If the efficient market hypothesis is generally true, how are funds seeking information compensated?

So how do we explain the fact that despite markets being generally efficient, there is still a large (albeit shrinking) industry involved in active investing? If market-relevant information is generally encoded in prices, then there is nothing profitable about seeking out new information and trading on it. Yet it is clear that many individuals and firms do actively try to provide new information. This is a bit paradoxical.

This brings us to another of my favorite papers, on the impossibility of efficient markets, by Grossman and Stiglitz. The authors point out that gathering information is expensive, not free. They go on to point out that since the efficient market hypothesis assumes that all information is immediately expressed in prices, the cost of revealing new information is not compensated under this model.

Therefore, markets cannot be perfectly efficient: information asymmetries must exist because there must be ways to compensate informed traders. Their model introduces a useful information cost variable into the standard model of market efficiency. According to their model, if information becomes more expensive, markets become less efficient, and vice versa. Therefore, whether markets reflect their fundamentals depends, at least in part, on how easily this relevant information is available.

The researchers concluded:

“We argue that because information is expensive, prices cannot perfectly reflect the available information because if it did, those who expended resources to obtain the information would receive no compensation. There is a fundamental conflict between the efficiency with which markets can disseminate information and the incentives to acquire it.”

A rather delightful implication of Grossman and Stiglitz is that in order for the arbitrage price to return to where it “should” be profitable, there must be a group of traders who perennially disrupt the price. The answer came from Fischer Black (author of the Black Scholes option pricing model) in a paper he published in the Journal of Finance titled “Noise”. He identified the unsophisticated “noise” traders: those who trade on noise rather than information. Noise is heard everywhere. Just hang out on Tradingview and look at the plethora of indicators that people trust. The Black Market divides market participants into two categories:

1. People who trade based on noise are willing to trade even when, from an objective standpoint, they would be better off not trading. Perhaps they believe the noise they are trading is information. Or perhaps they just enjoy trading.

2. There are many noise traders in the market now, and they pay for those who trade with information. Most of the time, noise traders as a group will lose money from trading, while information traders as a group will make money.

Noise “makes financial markets possible,” Black said. “Noise traders exist to give professional firms like hedge funds liquidity and valuable counterparties.”

As Grossman and Stiglitz point out, noise theory addresses the “apparent impossibility” of efficient markets. The presence of noise introduced by unsophisticated traders provides a considerable economic incentive for sophisticated traders to introduce information into prices. Thus, you can thank degens for overtrading on BitMEX — they are the compensated funds that allocate resources to Bitcoin and provide relevant information quickly.

If the efficient market hypothesis is generally true, how can we explain market uncertainty?

That’s another good question. There are plenty of examples where arbitrage opportunities were easy to spot, but for some reason the arbitrage could not be closed. Arguably the most famous of these examples was the trade that led to the demise of Long Term Capital Management.

This was a pair of bond trades that were effectively the same, but at different prices (partly due to the Russian default in 1998). LTCM was betting that the bond prices would converge. However, many other hedge funds made the same bet with leverage, and because the bonds failed to converge in time, some of the limited partners of the redeeming hedge funds faced margin calls and were forced to close their positions. This started a feedback loop that created a further squeeze: the cheaper bonds were sold off, and the more expensive instruments continued to rise as shorts were covered. LTCM was betting on market efficiency and the convergence of these instruments; but due to market pressures and a gradual reduction in pent-up leverage, they were unable to complete the trade and the fund collapsed.

Shleifer and Vishny studied this phenomenon in a 1997 paper titled "The Limits of Arbitrage." Shleifer and Vishny point out that, in general, arbitrage is not usually done by the market, but is a task delegated to specialized institutions (usually funds). Arbitrage is therefore expensive: it requires freely available capital. Here is a paradox: when markets are under stress, great arbitrage opportunities arise (for example, many stocks have low price-to-book ratios). But during times of market stress, capital is most scarce. Therefore, arbitrageurs, who need capital to operate, are least able to make the necessary arbitrage when they are most needed. This is the limit of arbitrage. As the paper states:

“Arbitrageurs have their best opportunities when capital is required for arbitrage, which is when the mispricing they are shorting becomes worse. Fear of this happening will make them more cautious in making their initial trades, and therefore less effective in making the market more efficient.”

To take a simple example, a value-based hedge fund has raised money from outside sources. They will tell their limited partners (investors in the hedge fund) that they intend to make a contrarian bet - for example, buy value stocks when valuations are low. Suppose the market falls, and they buy a basket of stocks that have shrunk their valuations and have low price-to-earnings ratios. However, imagine that the market then falls another 40%. Their limited partners are now staring at losses and demand redemptions. This is the worst possible moment: the fund has to sell these stocks at a loss, even though they have high confidence in profiting in the long term. They would rather buy (now heavily discounted) stocks that are trading at even more attractive valuations. Worse, liquidating these positions will force them to fall further, punishing other funds that make the same trade.

Thus, Shleifer and Vishny found that:

Performance-based arbitrage is particularly ineffective in extreme situations, where prices deviate significantly from their normal range and arbitrageurs are fully invested. In such situations, arbitrageurs may exit the market just when their participation is most needed.

The EMH’s arbitrage limits warning actually explains a lot of situations where people will describe market conditions and lament that information is not being incorporated. This is often taken as a slight to the efficient market hypothesis. But of course, we can’t expect dysfunctional markets to function properly. So, therefore, when Dentacoin’s multi-billion dollar putative market cap is touted as an example of market inefficiency, given that it likely has a very small float, ownership is very concentrated, and obtaining short-term borrowing is impossible. This means that market participants cannot meaningfully express their views on the asset.

A complete concept

Given these constraints (issues with market structure, costly information, limits to arbitrage, etc.), we can design a more complete version of the EMH that includes these considerations. Thus, you can design a modified EMH that sounds a bit like this:

Free markets reflect, to the extent that information is available, pricing entities are willing and able to act mechanically on that information.

Free markets: because state-controlled markets can be unclear (e.g., currency markets with capital controls do not give reliable signals because selling is effectively restricted).

Pricing Entities: Because small companies are ultimately unimportant in most cases, a small number of well-funded players is enough to incorporate important information into prices.

To the extent they wish: This includes the “expensive information” caveat. If the cost of acquiring information is higher than the value of the instrument (e.g., in the case of uncovering accounting fraud in micro-cap stocks), then the information is not incorporated into the price.

Mechanical capacity: This covers situations where there are limits to arbitrage. If there is a liquidity crisis, or the market is not functioning properly for various reasons, and the fund is unable to operate its view of the market, inefficiencies may occur.

Thus, when most finance professionals talk about the EMH, they are usually referring to a modified, slightly more empty version of the hypothesis, such as the one described above. They almost never refer to the “strong form” of the EMH.

Interestingly, by breaking down the EMH, we stumble upon an entirely different concept. The model I describe here is somewhat similar to Andrew Lo’s Adaptive Markets Hypothesis. In fact, while I’m happy to argue that most (liquid) markets are efficient most of the time, the Adaptive Markets Model reflects my view of markets better than any general EMH formula.

In short, Lo attempts to reconcile the findings of behavioral economics that found apparently irrational investor behavior with the orthodox Efficient Market Hypothesis (EMH) school of thought. He calls this the Adaptive Market Hypothesis because he relies on an evolutionary approach to market research. Building on Black’s insights, Lo divides market participants into “species,” which gives us a different view of market efficiency than the mainstream:

Prices reflect as much information as is possible from environmental conditions and the number and nature of the "species" in the economy, or in proper biological terms, the ecology.

Lo described the profit opportunities brought about by information asymmetry as "resources", thus deriving the following formula:

If multiple species (or members of a highly concentrated species) compete for a fairly scarce resource in a single market, then that market may be efficient, such as the market for 10-year U.S. Treasury bonds, which does reflect the most relevant information very quickly. On the other hand, if a few species compete for a fairly abundant resource in a particular market, then that market may be less efficient, such as the market for Italian Renaissance paintings.

The contextualism and pragmatism presented by Lo's model is consistent with the experience of most traders, who intuitively understand that market participants are quite diverse.

What this means for Bitcoin and the halving

As we have seen, most markets are efficient most of the time. I have discussed some exceptions: situations where arbitrage is limited, non-free market situations, situations where behavioral biases apply, and situations where market participants may not have sufficient incentive to provide relevant information. The question is, do these conditions apply to the Bitcoin market?

Now, that doesn’t seem to be the case. We are not in a liquidity crisis. There are no apparent limits to arbitrage. You could have made a convincing case for this in an era before Bitcoin was financialized (I’d say any time before 2015). It really wasn’t easy for a well-capitalized entity to express a positive view on Bitcoin. But today it is.

As for free markets, Bitcoin is clearly a very free market, one of the freest in the world (because the asset itself is highly portable, easily concealed, and can be traded globally). Unlike most currencies, it is not backed or guaranteed by a sovereign state, nor are there capital controls to limit sell-offs. Participants also have the ability to take large short positions on Bitcoin, so they can express different views.

So we can examine "markets in action". Is Bitcoin now large enough for a large number of sophisticated funds to engage in a coordinated effort to reveal important information? At $150 billion, I think it is definitely large enough. The ultimate test of market efficiency is whether market-moving information is incorporated into prices immediately, or with a lag. An event study covering the impact of exogenous shocks (such as exchange rate shocks or sudden regulatory shifts) on prices would be welcome.

The issues that remain necessary for Bitcoin market efficiency are the divergence between market participants (i.e., the lack of a consistent shared valuation model for price-setting entities), and the development of more financial pipelines. There are still several categories of entities that find it difficult to gain exposure to Bitcoin. Of course, overcoming these challenges will make Bitcoin's prospects brighter.

So is the halving "priced in" or will it be a catalyst for appreciation? If you've read this far, you'll understand that I think changes in issuance will be ignored by pricing entities. Anyone interested in Bitcoin has known the supply trajectory of Bitcoin since the beginning. The supply was encoded in the first implementation released to the world by Satoshi in January 2009. Long-planned changes in the issuance rate do not constitute new information. Any expected demand-side reaction to a "halving catalyst" can also be predicted by established funds that have strong incentives.

Now, can Bitcoin appreciate from here? I don't believe in appreciation because if the halving happens, Bitcoin will be issued by a completely predictable change in rate (from 3.6% to 1.8%), and of course I feel there are other positive factors that can affect the price, most of which are difficult to predict. Is this consistent with the EMH? Very good. The EMH allows for information shocks (e.g., imagine if we suddenly had hyperinflation of real-world currencies). It's also possible that the pricing entities hold overly conservative views about the future of Bitcoin, or that they are acting according to a weak fundamental model. These are consistent with the weak form of the EMH.

Regulated securities markets have structural barriers to efficiency, such as prohibitions on insider trading. As Matt Levine likes to say, insider trading is a form of theft where someone trades on information that is not theirs. Rather than discovering the information from a public source, they participated in discussions about, say, a merger and acted on it. Because insider trading is prohibited, stock prices generally do not reflect upcoming catalysts, such as acquisitions, until they are publicly announced. However, in markets for virtual commodities like Bitcoin, the insider standard does not generally apply. If a catastrophic bug were discovered, you can expect that information would likely be incorporated into the price immediately. So in that sense, the Bitcoin market is likely to be more information efficient than the U.S. stock market.

Common objections

I'll consider some objections. Chances are, your answer is covered.

I found an example of inefficiency. This is evidence of widespread market inefficiency.

This is a bit like throwing a baseball into the air and claiming that its temporary deviation from the Earth proves that gravity is wrong. Few financial practitioners believe that all markets are efficient all of the time. If information is not evenly distributed or if the owners of information lack the means to instrumentalize their views, then prices cannot reflect information. Short-term instances in which markets do not clearly reflect information simply call into question why market participants are unable to price in relevant information. These failures are not evidence that the efficient market hypothesis is weak, but rather reinforce its validity as an explanatory tool.

Behavioral biases exist, so market efficiency does not hold

The researchers did find some persistent behavioral biases, and I think it is plausible that they systematically affect asset prices to some extent in the medium term. However, the question here is whether they are relevant to the question at hand - the effect of a supposed change in supply rate on asset prices - and whether these alleged biases actually affect price formation in an extremely liquid $150 billion asset.

You might respond by saying, “Well, Bitcoin traders have a bias that causes them to bid up asset prices when the asset issuance rate is significantly reduced, even when this information is already known.” If you can prove, as Kahneman and Tversky did, that this is a pervasive human bias that affects asset pricing and goes against the prevailing market models, you will not only win the argument, you may also win a Nobel Prize. In this case, I would also like to refer to Lo’s adaptive markets again.

Efficiency is impossible in Bitcoin because it has no fundamental principles

Some people believe that everything in the crypto market is driven by sentiment and that fundamentals don’t exist. This is a fallacy. There are some obvious fundamentals that everyone agrees on. Here is a short, non-exhaustive list:

1. The quality of the financial infrastructure that enables individuals to access and hold Bitcoin. In 2010, it was nearly impossible to buy Bitcoin, and your only custody options were the Bitcoin QT "Satoshi Client" or a homemade paper wallet. Today, you can get exposure to $1 billion worth of Bitcoin, and you can either keep it yourself or rely on some of the largest asset managers and custodians in the world. This is a fundamental change

2. The quality of the Bitcoin software (compare the current version to Satoshi’s first client). The protocol itself and the tools around it have been improved, refined, and become more useful

3. The actual stability and functionality of the system - Imagine a situation where Bitcoin cannot generate blocks for a month. This will definitely affect the price. If you admit this, you admit that there are "fundamental factors" besides pure emotions.

4. The number of individuals around the world who know and need Bitcoin. This is “adoption.” This is more than just sentiment, it is a measure of which sources of funding around the world are actively seeking exposure to Bitcoin.

There are many other fundamentals that I won't go into here. Funds that trade Bitcoin try to track the trajectory of these variables and determine whether Bitcoin is overpriced or moderately priced relative to their growth. This is "fundamental analysis."

Again, if you don’t believe me, think about the contrast between the state of Bitcoin in 2010 and 2020. It is many orders of magnitude easier to use, acquire, buy, sell, and store. That is a change in fundamentals. Granted, these are not the “fundamentals” that apply to cash-flowing stocks, but Bitcoin is not a stock. The unit of Bitcoin is ownership of ledger space, which gives you access to a specific transactional utility of the network. I admit, fundamentals are not as obvious as they are with stocks today. However, the concept of “fundamentals” is not limited to stocks or cash-flowing instruments. Global macro investors think about currencies in terms of macro variables or political risk assessments. Commodity traders focus on the rise and fall of production and supply. There are similarities here.

All of this suggests that funds have meaningful information relevant to the market to trade on, not just sentiment or hype. It’s just that it’s difficult to get an accurate fundamental assessment of Bitcoin.

Efficiency is not possible in Bitcoin because it is unstable

It is entirely possible to have a volatile and efficient market. Recall that all efficiency requires is that the available information is included in the price. Consider the value of a call option nearing expiration, with the underlying price fluctuating around the strike price. One minute the option is in the money, the next it is worthless. This would be a situation that is both volatile and efficient.

Or, consider the value of Argentine government bonds in response to political turmoil. The fundamental here is the willingness of the Argentine government to repay its debts. Effectively functioning markets will continually reassess the prospects for creditors to be repaid. In times of turmoil, fundamentals are unstable, and so is the value of bonds.

Bitcoin's volatility stems in part from market participants rapidly reassessing its growth prospects, both in terms of pace and trajectory. Even small changes in expectations of future growth rates can have a significant impact on the implied present value. (Indeed, in DCF models of stock valuation, output is very sensitive to long-term growth rates.) Market participants frequently revise their growth expectations, and expectations vary (because there is no single dominant model for Bitcoin's price), leading to increased volatility (especially if supply is inelastic). If future growth expectations were the root cause, then the rapid appreciation of those expectations would lead to price volatility. Therefore, volatility does not affect efficiency.

If the efficient market hypothesis is correct, then at current valuations, Bitcoin is only just getting started.

That’s not how the world works. As I explained above, Bitcoin didn’t have the mature, solid foundation it has now when it was created. It had to grow into its valuation. There was considerable uncertainty in the early days about whether it would have any success at all. It had to go through all of these trials and tribulations to get to where it is today. So it didn’t make sense for large funds to allocate money to Bitcoin on day one (although, in hindsight, it obviously made sense) because they didn’t know Bitcoin would grow, and in many cases, because they were structurally unable to invest in Bitcoin. Think about how you would have acquired Bitcoin in 2012, two years after its creation. You would have had to use something like Charlie Shrem’s BitInstant, or the (defunct) Mt Gox, which we now know was a mess. You could have mined Bitcoin, but that was a difficult and technical task.

This brings us back to the “limits of arbitrage” point. From 2009 to the present, many investors wanted to buy Bitcoin, but simply couldn’t due to regulation, operational risk, and lack of effective market infrastructure. Even if they believed Bitcoin would be worth over $100 billion at some point, they didn’t have the ability to capitalize on that view. Furthermore, investors didn’t have strong conviction at the outset. They needed to see Bitcoin operate successfully “in the wild” and not shut down before choosing to store wealth in it. If you believe that Bitcoin’s continued success represents new information being brought to the market, then you understand that the EMH doesn’t require it to emerge fully formed from the womb at an initial valuation of $100 billion.

Something like Plustoken that is subject to Ponzi-related purchases is invalid

I agree that the massive buying (and then selling) of around 200,000 Bitcoins by investors was a major driver of the price action in 2019. However, this does not affect efficiency. If it had become known in the West that Plustoken had all these Bitcoins and was preparing to sell them, and the price of Bitcoin had not moved, then I agree - there would be questions about efficiency.

However, it was not until much later, after a large number of coins had been sold, that information about Plustoken BTC spread in the West. Remember, efficiency does not require that prices never change, on the contrary, it suggests that prices move based on new information.

Small-cap assets have seen their prices rise by hundreds of percentage points on dubious news. This is evidence of market inefficiency and proves that the efficient market hypothesis is wrong.

Likewise, localized or temporary evidence does not invalidate the EMH. You either believe that markets are good clearing mechanisms for information, or you don’t. Granted, many small-cap altcoin markets are pretty bad from a structural perspective. These assets may trade on unregulated or illiquid exchanges. This means the prices you see don’t necessarily reflect reality. So, temporary injections and dumps of illiquid assets don’t prove much of a two-way street, other than the poor market environment in which they trade.

Generally speaking, most EMH proponents will acknowledge that efficiency varies positively with asset size and the sophistication of participants, and that it is difficult to find an edge in large, publicly traded stocks. Chances are, if you find some market-relevant information about Apple or Microsoft, someone else will find it, too. But in smaller, less liquid asset classes, the returns to revealing relevant information are much lower, so there are fewer analysts actively injecting information into the assets, which means that opportunities are likely to exist. This is because large, multi-billion dollar funds simply cannot implement micro-cap asset trading strategies.

Simply put, efficiency has an effect of scale. Bitcoin is not a micro-capital, it is a globally traded asset worth over $100 billion. This ensures that high returns can be obtained by providing relevant information and expressing it in the form of transactions. Therefore, there is a clear difference between the inefficient micro-market “altcoins” (the return on finding information is low and the market is weak) and the mature assets that a large number of analysts look for advantage.

When small crypto assets are hit by 51% or bad news comes up, they don't drop. This suggests that the crypto market is inefficient

Here I will follow Lo's explanation of adaptive markets, where small-cap assets are usually held by hardcore believers, or better yet, closely held by allies of the founding team. In this case, you may have seen a conversation on Reddit and Telegram where coin owners urge each other not to sell, especially in case of bad news, as the crypto community will be watching the project for the time being. In the face of the bad news, bond issuers try to weaken the negative catalyst by repurchasing. However, this only applies to small markets, as ownership is not widely distributed.

Furthermore, it is worth considering that no one actually holds these assets because they like the underlying technology or find it interesting to have a specific code stolen from Bitcoin Core or Ethereum. The holding of small-cap crypto assets is an expectation of the "pump" that may arise in the future. Therefore, the damage associated with the actual protocol itself is not the most basic. The most fundamental thing is that the issuing team wants to get "adoption", or at least pretend adoption by obtaining favorable press releases and partners. As long as the underlying protocol is not completely broken down, the "base" - the hype power of the release team - can remain the same.

As some Bitcoin buyers mechanically buy bitcoins regularly, and new supply will decrease, this will mechanically lead to currency appreciation

This is an example of first-order thinking. The efficient market hypothesis exists in the secondary market. For me, the key insight into the efficient market hypothesis is that any information you have is that a experienced market participant has the same. Since experienced market participants have a strong incentive to find relevant information and trade in reverse, you can bet that they have expressed the information the moment they get it. If this is indeed a reasonable assumption (i.e., static buying pressure will have a positive impact on the price as the circulation drops halved), then these funds have expressed this positive view in the form of trading. This is called "pricing." "If there is a major discovery tomorrow, it will be included in today's price. This is one of the trickiest characteristics of EMH, and you really need to take some effort to understand it.

So the question becomes, not, “Will this information affect the price in a vacuum?” but, “Do I have information that the smartest and most resourceful hedge fund analysts don’t have?” If the answer is “no,” then you can expect that this information is currently included in the price (in some way, it is actually important information).

Why focus on funds? The reason is that they are professional companies, they actively seek information and express it in the form of trade. They are entities that align prices with "fundamentality." "You need to remember that you are not acting in isolation. You are like a jungle in the digital world, lurking predators everywhere. These predators are skilled, quick to act and rich in resources.

In the stock market, we are talking about funds that have private relationships with CEOs and CFOs, having dinner with them and interpreting whether they are optimistic about the next quarter. There are dozens of analysts analyzing funds that you don’t even know exist. They will track the movements of corporate private jets to determine if acquisitions are possible. They will run a machine learning model that evaluates his emotional state through the trembling of his eyebrows when Jerome Powell announced the Fed’s action. They will get images of satellite data from the parking lot to predict whether Walmart will exceed quarterly earnings guidance. The open market is extremely competitive. They are some of the most talented and there are no real restrictions on taking action based on information (except insider trading). Anyone who thinks they have an advantage is free to express their opinions in the transaction.

So if you feel you have information related to the market (such as this expectation that a supply contraction will push up prices), then the most experienced participants will also have it. They have evaluated it and acted on it.

Also, you need to remember that the market is not democratic. They are weighted by capital. Giant whales can express stronger opinions than fish. Hedge funds just have more capital (and they tend to get cheaper leverage!) Then, when they form an opinion about a certain stock, they have a way to express that. That's how "pricing" happens. So, in reality, only the pricing entity is the most important.

Plustoken's accumulation of 200,000 BTC (about 1% of the supply) and selling it is the main driving factor for the price trend in 2019. Why would the halving (affecting 1.8% of the issuance) not have the same effect?

First, the rise and fall of Plustoken was unexpected. This is really new information—so much that most investors only know its size after the Ponzi scheme is basically over. Furthermore, as far as we know, the trapped BTC wallet was liquidated in a relatively short period of time, about 1-2 months. For any market, this is a large amount of BTC to absorb. The change in circulation combined is down by 1.8%, but this is the figure after the annual rate. Mechanically, this means that the monthly BTC mining will be reduced by about 24,800. This is a big number, but it does not equal the liquidation of 200,000 bitcoins in a short period of time. And, unlike Plustoken, this reduction is known.

Half will affect Bitcoin from the demand side, arouse investors' excitement and get media coverage. Therefore, halving will remain a positive catalyst for Bitcoin

The same logic as the response above applies here. If you look at the case study of Litecoin, you will see that the price rises significantly with the expected halving and then falls again after the halving. This is likely an example of an investor expecting the halving to be a positive catalyst. You can see how investors position themselves (betting on how they think other investors might react) affects the price. You get into a recursive game where everyone is looking at others, and they are all trying to predict what others are doing. So even if there is a shock in demand on the day of the price cut (whether through media coverage or just the enthusiasm of investors) a price-setting entity will have expectations and may be included in the price a few months ago.

If the market is effective, investing in Bitcoin is meaningless

This is not the case. There are some information aspects of Bitcoin that are completely known and transparent, such as supply schedules. However, as I mentioned above, many of the basic drivers of Bitcoin price are difficult to quantify or even unaware. For example, no one knows exactly how many Bitcoin owners there are in the world. If you can predict these factors better than others, you can find an advantage. In addition, there are many unpredictable shocks that may have positive impacts on Bitcoin in the future, such as currency crises. EMH critics did not see that, it only stipulates that the market expresses available information. Obviously, unknown catalysts in the future are unavailable. They have not happened yet.

Ultimately, if you do better than other pricing entities in predicting Bitcoin’s growth, you might want to trade with your strengths. I think that’s a completely reasonable prospect. So even if there is an efficient market hypothesis, I definitely won’t underestimate the potential appeal of Bitcoin to active distributors. In fact, I’m personally optimistic about Bitcoin. So it’s clear that I think it’s good to have a specific expertise in the Bitcoin space. If I were a firm EMH believer, I wouldn’t be actively managing. In fact, there is a very strong incentive for active managers to find ways to negate the efficient market hypothesis. So I’m here to defend it.

In the presence of the weakly effective market hypothesis, basic analysis is possible and indeed necessary. After all, someone must do the analysis to reveal the information that is ultimately expressed in price. This work is left to active managers. So, at the end of the day, those annoying hedge fund investors are still useful for something.

Original link:

https://medium.com/@nic__carter/an-introduction-to-the-efficient-market-hypothesis-for-bitcoiners-ed7e90be7c0d