An Introduction to the Effective Market Hypothesis for Bitcoiners

What the hypothesis of an effective market is talking about and what it is not talking about.

As you approach the third halving, among bitcoiners, debate aboutwhether the reduction in emissions is already included in the price or not. Those who are inclined to doubt the significant effect of halving on the price usually refer to the hypothesis of an effective market. So this concept has become a source of enormous bitterness and controversy for the crypto community. Disagreements often turn out to be insoluble, since skeptics operate on an extremely inaccurate view of the efficient market hypothesis, and as a result, the parties cannot even agree on definitions. Meanwhile, a mutual understanding of the concepts is necessary for a fruitful discussion. Seeing how often people misunderstand this concept, I decided to explain it from scratch, expecting from readers only minimal knowledge in the field of finance.

The origin of the efficient market hypothesis

The authorship of the effective market hypothesis (GER) is attributed to several scholars, including Benoit Mandelbrot, Louis Bachelier, Friedrich Hayek and Paul Samuelson. Essay Hayek “The use of knowledge in society” sets the basis for understanding the concept,although the GER itself is not mentioned in it. In his work, Hayek speaks out in favor of a distributed market economy, contrasting it with a centralized planned arrangement. The basic idea is that markets are information aggregation mechanisms that no central planner can compare with, no matter how qualified it is or what resources it has. I will quote:

[Even] a moment's thought will show thatundoubtedly there is a mass of very important, but disorganized knowledge that cannot be called scientific (in the sense of knowing universal laws) - this is the knowledge of the special conditions of time and place. It is in this respect that almost any individual has a certain advantage over everyone else, since he possesses unique information that can be advantageously used. However, it can be used only if the decisions depending on this information are provided to the individual himself or worked out with his active participation.

[...] A living shipperusing cargo voyages that would otherwise remain empty or half full, or a real estate agent whose knowledge almost exclusively comes down to knowing temporary opportunities, or arbitrageur <speculator (fr.)>, playing on the difference in local prices for goods, all of them perform extremely useful functions, based on a special knowledge of fleeting circumstances unknown to other people.

From the fragment in italics you can understandhow Hayek looks at markets: as forces that accumulate many different views and expectations and put them into prices. Hayek understands market prices as information, as a particularly powerful source of information. The beauty of the markets, according to Hayek, is that, simply acting selfishly in accordance with their interests, people participating in the economy create signals in the form of prices. GER directs the same optics precisely to financial assets, based on the fact that investors collectively reflect relevant information that is transmitted to prices through the bidding mechanism.

After a series of studies on stock returns, such as “Evidence of erratic fluctuations in correctly forecasted prices” (Proof that Properly Anticipated Prices FluctuateRandomly, 1965) Samuelson, GER was finally formulated by the legendary financial scientist Eugene Fam (you may have heard about the Fam-French model) in 1970. In a document (PDF, English) entitled Efficient Capital Markets: A Review of Theory and Empirical Work (“Effective capital markets: review of the theory and empirical research ”) Fama defines an effective market as one in which“ prices always fully reflect the available information ”. Even stopping at this place and not reading further, you will already have a better understanding of what is meant by efficient markets than the authors of numerous caricatured replicas on Twitter. GER is not something mysterious. This is simply a statement that market prices reflect the information available to market participants. That is why scientists often call such markets “informationally” effective. Efficiency here refers to the dissemination of information.

But what does this mean? It simply means that if new information arises regarding the asset being traded, this information is usually quickly reflected in the price of the asset. And if there are any future events about which it can reasonably be assumed that they can affect the price of an asset, then, as a rule, this information is laid down in the price immediately, as soon as it becomes known. Markets do not wait for the onset of predictedevents - they react ahead of schedule. This means that if the weather forecast predicts a hurricane next week that threatens to destroy sugar cane plantations, then speculators, in anticipation of a supply crisis, will wind up the price already Today. Of course, there are unpredictable externalshocks (imagine a hurricane crashing into a plantation all of a sudden). In this case, the price can respond to events only in real time, when information about the hurricane becomes known. The speed with which information is embedded in the price is one of the criteria for the effectiveness of markets.

Despite the simplicity of the idea, the hypothesis ofMarket efficiency tells us a lot about how markets work. Markets are effective if prices are quickly adjusted based on new information. Predicted events that can affect the market are usually priced in advance. What is important, one of the consequences of the GER is that after all relevant information is included in the price, only random fluctuations called “noise” remain. This means that although asset prices will continue to change even in the absence of new fundamental information, these fluctuations in themselves carry no information.

And finally, the difficulty of finding a unique newinformation (not yet included in the price), as a rule, depends on the sophistication of market participants and the liquidity of the asset. This explains why you can gain an advantage in stocks of little-known microcapitalization companies, but probably not in predicting the value of Apple shares.

After Fam's article and thanks to popular books on the subject, such as “A Random Walk Down Wall Street"(" Random walk on Wall Street ") BurtonMalkiel, heated debate has flared up over the feasibility of active investment management. Indeed, since the hypothesis of an effective market suggests that it is very difficult to find reliable advantages, many investors are wondering if there is any sense in actively traded instruments such as mutual funds or hedge funds. Over the past decade, trillions of dollars have been withdrawn from such “active” stock selection strategies and transferred to passive investment tools tied to the effectiveness of the entire market or a particular sector. This is one of the most heated debates in the world of finance to date, and this is mainly due to the growing awareness that markets are generally effective.

Description of the hypothesis of an effective market

If it depended on me, I would call it model efficient markets, not a hypothesis. Because in reality it does not contain a hypothesis, being more likely a concrete and verifiable statement about the world. As I wrote above, the GER says that market prices reflect available information (which, as we have already noted, is the main purpose of markets as such). Interestingly, Fama, in her 1970 article, also calls this an effective market model, not a hypothesis. It seems that his vision coincided with mine.

In my opinion, the “efficient market hypothesis”it even sounds somewhat tautological. From Hayek’s work, we know that (free) markets serve as a measure of society’s net information position regarding various assets. So, replacing “market prices” with “concentrated informational conclusions”, we get the following statement:

“Concentrated informational findings reflect available information.”

It definitely sounds like a tautology. However, the model does not become less useful from this.. On the contrary, that means challenging the ERT is everythingequal to questioning the very nature of markets. Indeed, most criticisms of the GER (I will discuss a few of them later in this article), as a rule, cover cases where market equilibrium is not achieved for one reason or another. So if you recognize the wording “hypothesis of an effective market” as tautological, then “efficient markets” also begin to sound redundant. (Free) markets should be effective by default, because that's what we need markets for. Markets reward those who find valuable information relevant to them. If they were not effective by default, we would not waste time and attention on them.

Treating this as a model allows you toclearly understand that this is just an abstraction of the world, a description of how markets should work (and usually work), but not an immutable law. This is just a useful way to think about markets.

I will say directly: I do not believe in the “strict form" of the effective market hypothesis (its radical interpretation), like no other finance professionals familiar to me. The strict form says that markets reflect all information all the time. If that were the case, there would be no hedge funds or active capital managers. No one would study Apple’s quarterly reports or evaluate the prospects for discovering oil fields in the Perm basin. Given the scale of the active capital management industry, in which many bright and educated professionals are constantly looking for new information about various assets, the strict form of GER hardly stands up to criticism.

Frankly, the efficient market hypothesis isthis is not what you “believe” in or not. The choice here is that you either understand markets as useful mechanisms for detecting information, or completely reject the usefulness of markets.

Of course, there are conditions in which marketsbecome ineffective. Fama in her 1970 work also acknowledges this, noting that the cost of transactions, the costs of finding relevant information and differences between investors can potentially reduce market efficiency. Here I will focus on two of these factors: the cost of detecting significant information and the barriers to actually expressing views on markets.

If the ERT is generally true, then how are the funds spent on finding information offset?

So what explains the fact of the existence of the wholea large (albeit declining) industry active in investing despite the fact that markets are generally efficient? If market-related information is usually already priced, then there is no benefit in finding new information and trading in accordance with it. However, it is clear that many people and companies are actively trying to discover new information. This looks somewhat paradoxical.

And that brings us to another one of my favoritesarticles, “On the Impossibility of Efficient Markets” (English, PDF) (“On the impossibility of efficient markets”) by Grossman and Stiglitz. The authors point out that the collection of information is not free: it also has a cost, and sometimes high. They then note that, since the ERT states that all available information is immediately expressed in prices, the costs of finding new information under this model will not be covered. Consequently, markets cannot be completely efficient: there must be an information asymmetry that provides compensation for informed traders. Grossman and Stiglitz introduce a new useful variable into the standard market efficiency model: the cost of obtaining information. It follows from the model that if information becomes more expensive, then markets become less efficient, and vice versa. How markets reflect their fundamental factors, at least in part, depends on the difficulty of finding relevant information.

The authors come to the following conclusion:

We have argued that since information isexpensive, prices cannot fully reflect the available information, because otherwise, those who spent the resources to find it would not have received any compensation. There is a fundamental conflict between the efficiency with which markets disseminate information and the incentives for information.

Grossman and Stiglitz come to pretty prettyconclusion: to bring prices back to the level at which this type of activity will be profitable, there must be a cohort of traders that constantly knocks prices out of equilibrium. Fisher Black (from the Black-Shoals formula) gives us the answer in a beautiful article called Noise (Eng. Noise), published in the Journal of Finance. He identifies a group of inexperienced traders who make trading decisions based on "noise" rather than information. Noise can be found anywhere. Just go to Tradingview and take a look at the many indicators that people rely on. Black divides market players into two cohorts:

People who trade based on noise are readytrade, although objectively for them it would be better not to do this. Perhaps they take the noise, on the basis of which they make trading decisions, for information. Or maybe they just like to trade.

With a sufficient number of "noise traders",the market can offset the costs of those who have information for trading. Most of the time a group of traders working with noise will lose money, and those who work with information will earn.

Noise, according to Black, “makes financial marketspossible. " Noise traders provide professional companies such as hedge funds with liquidity and are valuable counterparties against which they can trade. If we draw an analogy with poker, then those who trade on noise are “fish”. They make the game profitable for sharks, even if there is a rake (commission charged by a poker club from each bank). Ask any former poker player - as soon as the environment has become more competitive and inexperienced players are gone, poker has ceased to be so profitable as to continue to play.

Noise Theory Resolves “Apparent Impossibility”effective markets - Grossman and Stiglitz write about this. The existence of noise created by inexperienced traders creates a sufficient financial incentive for professional players to lay information in prices. So you can thank the simpletons who over-trade on BitMEX with an excessive leverage - they are the ones who compensate other market participants for allocating resources and finding relevant information.

If the GER is true in general, how do you explain cases where markets do not achieve equal supply and demand?

Another good question. There are many examples in which the possibilities for arbitration were easy to identify, but for some reason the arbitration could not be closed. The best-known example of this is probably the deal that caused the decline in long-term capital management. It was a double deal on bonds that were almost identical, but priced differently by the market (partly due to the 1998 Russian default). Long-term capital managers relied on bond prices converging to a single value. However, many other hedge funds made the same leverage bet, and when bond prices did not meet on time and some fund investors began to withdraw their funds, funds began to receive margin calls and were forced to liquidate these positions. This marked the beginning of the feedback cycle, provoking new liquidations: cheaper bonds were sold, and more expensive instruments continued to grow, as short positions on them were covered. Long-term managers relied on market efficiency and convergence of these instruments, but due to unfavorable market conditions and reduced accumulated leverage, they were unable to complete the transaction, and the fund burst.

This phenomenon is investigated in a 1997 article by Schleifer and Cherry, entitled "The Limits of Arbitrage" (“Limitations of Arbitration”). The authors point out that arbitration is usually not carried out by the market, but rather is a task delegated to specialized agencies (usually foundations). Arbitration is an expensive operation requiring free capital. There is a paradox: the best opportunities for arbitrage arise when the market is under pressure (for example, when many stocks are traded with a low price / book value ratio). But in times of market stress, capital least available. Thus, arbitrageurs who need capital to work are the worst offers when they are most needed. This creates restrictions for arbitration. According to the authors:

While arbitration requires free capital,arbitrageurs can become the most limited precisely at those moments when the best opportunities are opened before them, i.e. when the wrong score against which they are betting is further exacerbated. Moreover, the fear of this scenario will make them more cautious when opening their initial positions, and therefore less effective in ensuring market efficiency.

Take a simple example of a value hedge fund,which attracted external capital. They will inform the partners (hedge fund investors) of their intention to play against the crowd - for example, to buy valuable stocks when they are cheaply valued. Suppose the market falls and they buy a basket of stocks with a lower rating and low P / E ratios (price / return). Now imagine that after this the market drops another 40%. Fund investors suffer losses and want to withdraw their funds. This is the worst time possible: the fund is forced to sell shares at a loss, even if the managers are absolutely convinced that they will earn on them in the long term. They would rather buy stocks, the valuation of which has now become even more attractive. But even worse, liquidating positions further increases bearish pressure on stock prices, forcing other funds to make similar deals.

Therefore, Shleifer and Cherries believe that:

Performance based arbitration, especiallyineffective in conditions of market instability, when prices are significantly reduced, and arbitrageurs have already invested all the capital available to them. In these circumstances, arbitrageurs may be forced to leave the market when they most need their participation.

Refinement to the hypothesis of an effective market aboutthe limitations of arbitration can in fact be explained by many situations where people describe market conditions and complain that the information is not reflected in prices. This statement is often perceived as somewhat contrary to the hypothesis of an effective market. But, of course, you cannot expect malfunctioning markets to work properly. Therefore, when the alleged multi-billion capitalization of Dentacoin is presented as an example of market inefficiency, it should be borne in mind that the number of tokens in free circulation was probably scanty, the concentration of ownership was extremely high, and obtaining a loan to open a short position was impossible. This means that market participants are not able to meaningfully express their opinion about the asset.

More complete concept

Given these limitations (featuresmarket structure, cost of information and limitations for arbitration), we can develop a more complete version of the effective market hypothesis, which will include these refinements. A modified GER could sound something like this:

Free markets reflect available information to the extent that pricing entities are willing and able to act in accordance with their information.

• Free markets - because state-controlled marketsmay not achieve a balance of supply and demand (for example, currency markets with capital restrictions do not give reliable signals, since sales can be effectively restrained).
• Pricing entities - because small players in most cases are not critical. A small number of participants with significant capital is enough to include significant information in the price.
• To the extent that they are ready to act - this relates primarily to costreceiving information. If the cost of obtaining information is higher than the benefit of its use (for example, in the case of the detection of unfair accounting in public companies with microcapitalization), then it will not be reflected in the price.
• Have the ability to act - this applies to emerging restrictions forarbitration. In the event of a liquidity crisis, or if for some reason the markets do not function properly and funds cannot express their vision of the situation by market means, markets may lose effectiveness.

So when most professionals from the fieldfinance talk about the ERT, they usually mean a modified, somewhat expanded version of it, similar to the one presented above. And almost never do they talk about the "strict form" of the GER.

It is interesting that, only slightly clarifying the GER, we stumble upon a completely alternative concept. The model I described here is somewhat reminiscent of adaptive market hypothesis Andrew Law. In fact, although I’m happy to claim thatmost (liquid) markets are efficient; in most cases, the adaptive market model much more accurately reflects my views on markets than any of the formulations of the original GER. Many current financial managers that I know are at least familiar with Law's work.

In short, Luo is trying to reconcileconclusions from a behavioral economy that reveals obvious irrationality in investor behavior, with orthodox GER. He calls this the adaptive market hypothesis because he relies on an evolutionary approach to markets. Developing Black's ideas, Law divides market participants into “types”, creating a different, different from the dominant, idea of ​​market efficiency:

Amount of information reflected in prices,dictated by a combination of environmental conditions and the quantity and nature of the “species” present in the economy, or, if you use the appropriate biological term, ecology.

Law describes the possibilities of profit from information asymmetry as “resources”, which leads the author to formulations such as this:

If many species (or members of oneof numerous types) compete for relatively scarce resources in one market, this market is likely to be highly efficient, such as the market for 10-year US Treasury bonds, which really responds very quickly to the appearance of the most relevant information. On the other hand, if a small number of species compete in the market for fairly abundantly represented resources, this market will be less efficient - such as the Italian renaissance painting market.

Law's contextualism and pragmatism are consistentwith the experience of most traders who intuitively feel that market participants are rather heterogeneous, and well understand the concept of "table selection" borrowed from poker. Here I will not go into Law's theory, but I would highly recommend reading his book.

What does this mean for bitcoin in the context of halving

As we have seen, most markets are effectivemost part of time. This is not something that markets do just occasionally; this is their main task. I have already mentioned some exceptions: restrictions on arbitration, unfree markets, the influence of some behavioral prejudices and situations in which market participants may not be sufficiently motivated to find relevant information. The question is, are any of these reservations applicable to Bitcoin markets? At the moment, it seems not. We do not have a liquidity crisis. There are no apparent limitations to arbitration. In the era of “pre-financing” (I would say, until 2015) it was possible to speak convincingly of such restrictions. In fact, the subject with big capital did not have an easy way to express an optimistic outlook on Bitcoin's prospects. But today there are such ways.

As for freedom, Bitcoin is definitelyIt is a very free market, one of the freest on the Earth (given that the asset itself is extremely portable, easily concealed and traded all over the world). Unlike most currencies, it is not secured and not guaranteed by any sovereign, and is not subject to control over the movement of capital, which could impede its sale. Market participants can open large short positions in bitcoin, so that they have every opportunity to express a full range of views. Thus, opposite the graphs of “functioning markets”, you can safely tick the box. Now, is Bitcoin a large enough asset for a significant number of highly professional funds to make an effort to discover the essential information related to it? With a capitalization of $ 150 billion, I believe that this is absolutely true. And the last test for market efficiency is whether the market-relevant information is included in the price right away or with some delay. It would be nice to see a study on the impact on the price of external shocks, such as hacking exchanges or sudden regulatory changes.

The only prerequisitesmarket efficiency, for which some questions still remain, are the lack of a common assessment model for market participants, according to which they would measure their decisions, and the development of financial infrastructure. There are still several classes of subjects for which getting bitcoins is quite problematic. Of course, overcoming these problems will make Bitcoin's prospects more rosy.

But as for the halving, is it already included inprice or will it be a catalyst for growth? If you read up to this point, then you must understand how absurd it seems to me that the pricing entities could somehow lose sight of the planned reduction in the rate of issue of coins. Anyone who is at least a little interested in Bitcoin knows about the limitation of the total volume of emissions, and the gradual reduction of output. The total volume of the issue was registered in the first version of the code, which Satoshi published in January 2009. Planned changes in release rates are not new information. Any expected demand side reactions to halving are expected for professional funds that have a strong incentive to play ahead of investors.

But can the price of bitcoin rise from the currentlevels? Of course. I do not believe that the growth of the exchange rate, if it occurs, will be associated with an absolutely predictable change in the rate of emission (reduction from 3.6 to 1.8% in annual terms), but, of course, I believe that there are other factors that can have a positive effect on the price, and most of them are difficult to predict. Is this consistent with the efficient market hypothesis? It is consistent. GER allows for information shocks (imagine, for example, that rampant inflation has occurred in a large world currency). It is also possible that pricing entities take an overly conservative position regarding the future of Bitcoin or act on the basis of a weak fundamental model. This fits into a broader understanding of the ERT.

Regulated securities markets have structuralbarriers to efficiency in the form of prohibitions on insider trading. As Matt Levin likes to say, insider trading is a form of theft: when someone is trading in information that does not belong to them. Since insider trading is banned nearly everywhere, pending catalysts, such as acquisitions, usually do not affect share prices until they are announced. However, in virtual goods markets such as Bitcoin, insider trading standards generally do not apply. If a catastrophic bug is detected, you can expect that the information will be reflected in the price immediately. So in this sense, it’s entirely possible that the Bitcoin market more informationally effective than, say, the American stock market.

General objections

Next, I will examine some common objections to the efficient market hypothesis. It is likely that here you will find answers to your questions.

I discovered a case of inefficiency. This indicates the inefficiency of the markets as a whole.

It's like throwing a ball into the air andto claim that his temporary separation from the earth disproves gravity. Few practicing finance professionals will argue that all markets remain effective 100% of the time. If the information is distributed unevenly or the information holders do not have enough funds to express their views on the market, then prices may not reflect the information. Brief periods in which markets do not explicitly reflect information are simply an excuse to wonder why market participants were unable to put relevant information into the price. Such cases do not indicate the weakness of the GER, but rather enhance its usefulness as an explanatory tool.

Markets cannot be truly effective due to the irrational behavior of market participants driven by their own biases.

Researchers have really discovered a numberconstant behavioral errors, and I believe it is likely that, to one degree or another, in the medium term, they systematically affect asset prices. However, the question here is whether they are related to the case under consideration - the alleged effect of changes in the rate of issue of coins on the price of an asset - and how much this alleged irrational behavior can really affect the price formation of a highly liquid 150 billionth asset. You can say: “But there is a prejudice among bitcoiners that promotes an increase in asset prices with a sharp decrease in the output rate, even if this information has long been known to everyone.” If you can prove in the style of Kahneman and Tversky that such a universal human perception is that affects asset pricing and contradicts the prevailing market models, then you will not only win the argument, but you can also safely claim the Nobel Prize. In this situation, I would once again refer you to the hypothesis of Luo adaptive markets.

The Bitcoin market cannot be effective, because this asset has no fundamental factors affecting price formation.

Some people believe that cryptocurrencymarkets are driven solely by the emotions of participants, and the fundamental factors for these assets simply do not exist. This is a convenient misconception. Meanwhile, there are quite obvious fundamental factors, with the significance of which, I think, everyone will agree. Here is a short non-exhaustive list:

• The quality of financial infrastructure,providing people with access to bitcoin and allowing them to own it. In 2010, it was almost impossible to buy bitcoins, and the only options for storing them were Bitcoin-QT or a paper wallet of our own manufacture. Today you have access to one billion dollar bitcoins and you can either store them yourself or rely on someone from the world's largest asset managers or custodians. This is a fundamental change.
• Bitcoin software quality (compare the current version with the first Satoshi client). The protocol itself and the software tools around it have been improved, redesigned, and become more useful.
• Actual stability and functionalitysystems - imagine a situation in which Bitcoin could not produce new blocks within a month. Of course, this would affect the price. If you agree with this statement, you acknowledge the existence of fundamental factors, and not just investor sentiment.
• The number of people in the world who know about Bitcoin andcreating demand for it. In the cryptosphere, this is often called "acceptance." And it's not just about moods; this is an indicator of which sources of capital are actively seeking access to bitcoin.

There are many other fundamental factors aboutwhich I will not speak here. Bitcoin trading funds seek to track the trajectories of these variables and find out how overrated or, conversely, underestimated bitcoin relative to these indicators. This is called "fundamental analysis."

Again, if I have not convinced you, just thinkabout the contrast between the state of Bitcoin in 2010 and 2020. During this time, it has become orders of magnitude easier to buy, sell, use and store. This is a change in fundamental factors. Of course, these are not the fundamental factors that apply to stocks with cash flows, but bitcoin is not a security either. The Bitcoin unit is the right to claim a place in the register that gives you access to the specific transactional functionality of the network. I admit that the fundamental factors here are not as obvious as stocks. But the concept of fundamental factors is not exclusively limited to capital or instruments with cash flows. Global macro-investors consider currencies based on macro variables or an assessment of political risks. Commodity asset traders look at the pace of production and the ups and downs of supply. Here we can draw some analogy.

All this suggests that the funds have significantmarket information on the basis of which they can make their decisions, and not just moods or hype cycles. Just getting an accurate fundamental assessment of Bitcoin is not easy.

The efficiency of the bitcoin market is impossible due to its volatility.

Volatile markets may well be effective. Efficiency implies that the information available should be reflected in the price. Think about the value of a call option with an expiring term and the price of the underlying asset, fluctuating around the strike price. Here the option is “in the money”, and the next minute is completely useless. In this situation, volatility and efficiency are combined.

Or another example: the reaction of the price of the Argentinean state. bonds for the political crisis. The fundamental factor here is the desire and willingness of the Argentine government to pay off its debts. Efficiently functioning markets will continually review debt repayment prospects. During a period of change, the main fundamental factor becomes volatile, as, therefore, the value of bonds.

Bitcoin volatility comes in part fromthe fact that market participants are quickly reviewing the prospects for its growth, in terms of both pace and trajectory. Even small changes in expectations regarding growth rates have a significant impact on implied fair value. (Indeed, in discounted cash flow valuation models of stocks, the results are extremely sensitive to long-term growth rates.) Market participants often revise their expectations for growth and their forecasts differ (because there is no one dominant bitcoin price model), which leads to increased volatility, especially against the background of inelastic supply. If expectations for future growth are fundamental factor, the rapid reassessment of these expectations generates constant price volatility. So volatility does not refute and does not exclude effectiveness.

If the GER really worked, then the price of bitcoin would initially have to be at current levels.

It doesn’t work like that. The world is different. As I said above, Bitcoin was not as mature and stable from the first days as it is now. He had to grow to the current grade. In the early period, there was considerable uncertainty as to whether he could even achieve success at least to some extent. Bitcoin had to go through many adversities and trials in order to be where it is now. So, it didn’t make sense to place large funds in Bitcoin from the very first days (although in hindsight, of course, this meaning is quite obvious), because no one had any confidence that it would grow, and because in many cases people just did not have the opportunity to invest in it. Think about how you would acquire Bitcoin in 2012, two years after it appeared. You would have to use something like Charlie Shrem's BitInstant or Mt.Gox (which has gone bankrupt since then), which, as we now know, worked literally on parole. Bitcoins could be mined, but it was a difficult technical task.

And that brings us back to the subject of arbitration restrictions. Many investors, even wishing buy bitcoins from 2009 to this day,simply could not do this for regulatory reasons, due to emerging operational risks and the lack of a functioning market infrastructure. Even if they were sure that Bitcoin would one day cost $ 100 billion, they did not have the opportunity to express this point of view by market means. In addition, investors did not start right away with a firm conviction. They needed to see how successfully Bitcoin would work in real conditions in order to decide to invest significant funds in it. If you agree that Bitcoin’s continued success in itself also represents new information entering the market, then you understand that the ERT does not require the asset to appear on the market immediately fully formed and with an initial valuation of more than $ 100 billion.

What is influenced by the popularity of Ponzi schemes such as Plustoken cannot be effective.

I agree that investors in Plustoken who bought(and then sold) about 200,000 BTC, were an important bitcoin price driver in 2019. But this is not related to efficiency. If in the West it was known that all these coins were at Plustoken, they were about to sell them, and the price of Bitcoin would remain unchanged, then I would agree that there are big questions regarding efficiency. However, information about the Plustoken bitcoins leaked west much later, when most of these coins were already sold out. Remember: efficiency is not about the fact that the price should be fixed; efficiency implies that price must respond to new information.

The market value of small-cap assets soars hundreds of percent on dubious news. This indicates market inefficiency and refutes the GER.

Again: local or temporary evidence of alleged irrationality does not refute the efficient market hypothesis. You either think that markets are good mechanisms for evaluating information or not. Of course, many of these microcapitalized altcoins are structurally poor. They can be traded on unregulated or illiquid exchanges. And this means that the prices you see do not necessarily reflect reality. Thus, episodes of pumping and depreciation of illiquid assets prove little for both points of view, except for the poverty of the market environment in which they are traded.

Generally speaking, most GER proponentsrecognize the presence of a positive correlation between the size of the asset and the professionalism of market participants. It will be very difficult to gain an information advantage in large publicly traded stocks. Most likely, if you find some relevant information about Apple or Microsoft, then someone else will also find it. But in smaller, less liquid asset classes, the return on discovering relevant information is much less, and therefore, analysts who actively put information into the price of assets become smaller, and this increases the likelihood of finding unique information. This is due to the fact that large multi-billion dollar funds simply cannot realize their strategies by trading assets with microcapitalization.

It is easy to conclude that the scale of the market affectsits effectiveness. Bitcoin is not a micro-capitalization token, it is a globally traded asset worth more than $ 100 billion. This provides a high return on finding relevant information and expressing it in the form of transactions. Thus, there is a big difference between inefficient altcoins with microcapitalization (where the income from the detected information is small and the markets are weak) and a mature asset with many analysts seeking informational advantage.

The price of crypto assets with low capitalization does not decrease during 51% attacks or against the background of negative news. This indicates the inefficiency of cryptocurrency markets.

Here I would again refer to Lo (seriously -read about responsive markets!). From the point of view of the adaptive markets hypothesis, this could be explained by the fact that owners of low-capitalization assets are usually supporters of the project or, even better, are in close contact with like-minded members of the founding team. In these conditions, cartel models of behavior may well arise. You could see similar discussions in Reddit and Telegram: coin owners urge each other not to sell them, especially in the absence of bad news, despite the fact that the crypto community briefly paid attention to the project. Buying amid bad news is the way issuers try to mitigate the effects of the negative catalyst. But this can only work in small markets where property has not been widely distributed.

In addition, it is worth considering that practicallyno one owns these assets because they like the underlying technology or they find it interesting that particular version of the code copied from Bitcoin Core or Ethereum. Microcapitalization crypto assets are held in order to capitalize on a likely future pump. Therefore, the problems of the protocol itself are not for these assets fundamental factors. The fundamental thing is rather the willingness of the issuing team to ensure “acceptance”, or at least its visibility, through favorable press releases and partnership agreements. Until the basic protocol breaks up completely, the “fundamental” ability of the issuing team to create excitement may remain unchanged.

Since some bitcoiners mechanically buy BTC on a regular basis (read: pay tithing), and the volume of the new offer will decrease, this will automatically lead to an increase in the rate.

This is an example of first level thinking. GER refers to the second level. For me, the main idea of ​​the ERT is that any information that you have is also a professional market participant. Since professional participants have a strong financial incentive to find relevant information, you can bet that they will actively express their attitude to this information as soon as they find it. If the hypothesis that the static pressure from the side of the purchase while halving the rate of output could have a positive effect on the price were plausible, then the funds would have long expressed this positive vision in the form of a deal. This is called "laying in the price." If it is discovered that something substantial should happen tomorrow, then this information will be included in the price today. It can be difficult to perceive the first time.

And the question then is probably not “isIs this specific information in a vacuum a driver for the price? ”, but,“ Do I have information that the most talented and resource-rich analyst from a large hedge fund does not have? ” And if the answer to the second question is negative, then we can safely expect that this information is already included in the price (to the extent that this information is significant).

Why am I focusing so much on funds? Because these are specialized companies that are aggressively looking for new information and expressing it in the form of transactions. They are the subjects that keep the price in accordance with the "fundamental factors". It is important to remember that no one on the market works in isolation from the rest of the world. The market is like the digital equivalent of a jungle with predators hiding around every corner. These predators are skilled, fast and resourced.

In the context of stock markets under predators, II mean funds whose managers have personal relationships with executives and financial directors - they have dinner with company executives and find out how optimistic they are about the next quarter. Funds in which dozens of analysts operate with sets of such data that you did not even suspect existed. They will track the movements of corporate jets to predict the conclusion of an agreement. They will launch a machine learning model to evaluate Jerome Powell’s emotional state from his eyebrow movements when he announces the actions of the Federal Reserve. They use satellite imagery to gauge congestion in front of supermarkets to see if Walmart’s quarterly performance will exceed forecasted values. Public markets are incredibly competitive. Some of the most talented people make a career on them, and the ability to act on the basis of available information is limited only by a ban on insider trading. Anyone who believes that he has gained an information advantage can freely express his vision with the help of market tools.

So if you believe that you haveMarket-related information (such as the expectation that a reduction in the rate of emission will become a driver of price growth), the most sophisticated market participants also have this information. And they already appreciated the prospects and took appropriate action.

Also, do not forget that markets do notdemocratic. They are weighted by capital. A “whale” can express its vision much more weightily than a small fish. Hedge funds simply have a lot more capital (and, as a rule, have access to cheaper leverage). And when they develop a certain position regarding any asset, they have the opportunity to express their vision in the market. This is how information is embedded in the price. Thus, most of the time only pricing entities matter.

Plustoken collected 200 thousand BTC (~ 1% of the totalaffordable offer), and their sale has become an important driver for the price of bitcoin in 2019. Is it not logical to expect a similar effect from halving (affecting 1.8% of the output)?

First of all, the rise and fall of Plustoken was not an expected event. This was really new information - so much so that most investors only knew about the scope of this ponzi scheme. after of how most of the bitcoins were alreadysold out. In addition, as far as we can tell, Plustoken BTC-wallets were liquidated in a relatively short period: it should be about 1-2 months. This is a large number of BTC for such a period in any market. A decrease in the rate of output leads to a decrease of 1.8%, but on an annualized basis. This means that ~ 24,800 BTC less will be mined each month. This is a fairly large figure, but not at all the same as the 200,000 BTC being liquidated in a short time. And unlike the Plustoken sale, this reduction is known in advance.

Halving will increase demand for bitcoin, inspiring investors and through media coverage. Due to this, halving will in any case be a positive catalyst for the price of bitcoin.

The same logic works here as in the answer above. Using the example of Litecoin, you can clearly see how the price rose sharply in anticipation of a halving, and then plummeted immediately after the event itself. It is likely that just in this case, investors hoped for halving as a positive catalyst. Here you can see how investor assumptions about the behavior of other investors affect the price. You find yourself in a recursive game where everyone watches everyone and everyone tries to predict how the others will behave. Thus, even if there is a lot of pressure on the demand side by the halving date - due to press coverage or just the anticipation of investors - this will not come as a surprise to pricing organizations and will probably already be included in the price months before.

If markets are efficient, then investing in Bitcoin is pointless.

It's not like that at all. Some of the informational aspects of Bitcoin - such as the emission schedule - are absolutely famous and transparent. However, as I mentioned, many of the fundamental drivers of Bitcoin prices are not so easy to analyze or even just discover. For example, no one knows the real number of bitcoin holders in the world. If you are able to predict such factors more accurately than others, you will get a certain advantage. In addition, there are many likely unpredictable shocks - such as currency crises - that can have a positive impact on Bitcoin's prospects. Critics of the GER are often overlooked that it only provides expression by the markets affordable information. It is obvious that the so far unknown future catalysts do not belong to the available information. They have not occurred yet.

After all, if you predict growthBitcoin is more accurate and better than other pricing entities, then you can use your excellent understanding to make a profit. And I think this is a plausible prospect. So I do not completely exclude the possibility that bitcoin can be attractive to an active financial manager, even taking into account the GER. I myself am very optimistic about the future of Bitcoin. And, of course, I believe that specialized knowledge in the field of Bitcoin can be of great value. If I were a supporter of the strict form of GER, I would not be engaged in active asset management. In fact, active managers are almost most interested in finding ways to completely abandon GER. And the fact that I am giving arguments in support of it already speaks volumes.

As an example of how a demand-oriented fundamental model for Bitcoin might look, I can offer you a translation of an interesting article by Byrne Hobart.

With a moderate form of GER, fundamental analysisquite possible and even necessary. In the end, someone has to analyze the data and find information that will ultimately be laid down in the price. This work has been left to the active financial manager. So maybe these nasty hedge funds and their managers also have some benefit.

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