The efficient market hypothesis seems easily disproven with a number of modern examples. Climate change for example - there is significant information available, but markets act as though the information is fake. Leading investors and corporations have for decades denied the risks associated with economic growth backed on non-renewable, polluting and greenhouse-effect-causing energy sources.
The hypothesis does not account for common irrational behavior among people; that real news is considered fake, or real crises considered non-crises.
There is also a matter of weighting. Some facts are known but viewed as uncorrelated or unimportant to the stock price. Facts may be obvious, but wrongly discarded as irrelevant.
I think of markets as a real-time implementation of information theory. There are certain facts that exist, and they are not all known although they may be discoverable. As they become known, or are considered more heavily, those facts bleed into market prices.
In this view, the market is a collective model of the world and thus it is not reflective of all true information.
The model overvalues the confidence and beliefs of people who have money. Sometimes, these people trade stock of companies that deal more with lower-income individuals. Their knowledge of those companies is limited, but over time they may converge toward a better understanding.
Also, sometimes there are errors in interpretation of easily discoverable facts. After 9/11, interest rates went down, but the market didn't price that into auto sales despite 0% interest auto loans being offered to the market.
The market is a model that perpetually converges to a set of facts that are constantly shifting. There is always a gradient (like osmotic pressure) between the model and the reality it represents, so there is always some motion in the market.
And there is always a set of expectations about the future that must be reflected in the model. These expectations have a wide variety of distributions, some are gaussian, others are bimodal, etc. That adds another layer of complexity in getting the model to converge to an appropriate expected value.
Not only that, but several different assets are interlinked. For example, if you buy a large block of call options on a high-volatility name, the market-maker will probably buy stock as a hedge. But in the absence of an upcoming event, he will buy patiently over the course of several trading days in order to minimize the price change resulting from his purchase ("delta impact"). So the market knows that the market-maker traded options, but he has an incentive to hide his hedging activity from other market participants so that they don't front-run him. As a result, it takes time for the purchase of the delta via options to be reflected in the underlying stock -- even though the options trade was printed on the exchange immediately and publicly.
Even if markets were efficient to known information, their price moves do not arrive at equilibrium instantaneously. There is an information gradient -- a kind of osmotic pressure between what is truly happening and what is reflected in the price -- that takes time to normalize itself.
You are thinking about what is logically efficient, but the market is also concerned about what is emotionally efficient.
A certain proportion of people believe climate change is a hoax, a certain proportion stand to make a lot of money shaping policy as if it were a hoax. With the coronavirus, merited or not the panic is real and the markets are reflecting that panic.
In a world economy driven by consumer spending, how people feel is more real than what is actually real for the market. Therefore, the market is always at its most efficient.
They were down slightly, marking the public's general consensus that while the news was worrying, that there was still a good possibility of containment. If you feel like you have a better understanding of risk than the markets do, it's pretty dang cost effective to buy puts, and you can make a LOT of money with very well understood downsides.
In November 2002, when SARS was first identified S&P was at ~909, it dropped to 846 in March 2003, and was back up as the virus was shown to be under control. Obviously lots of factors in play, but we're very susceptible to hindsight bias as a species.
The human lifespan is too short to distinguish between luck and skill for most low frequency traders. You'd have to see dozens of potential pandemics as severe as this one to know if you were "right". But it's empirically true that the average active trader underperforms the market. I build short-term trading strategies at my day job, but at home I just buy and hold some boring vanilla index funds. One nice thing about higher-frequency trading is that you have enough statistical power to quickly see lots of "obvious" ideas fail miserably. It teaches humility.
That is a misunderstanding akin to saying price differences by location cannot exist. It factors in all /available/ knowledge and the abilities aren't perfect either. Even if everyone was omniscient there is time to converge to the inevitable end state and perfect knowledge doesn't exist.
Expecting walking or driving around to provide free money wouldn't be workable. The closest precedent are the venerable professional of the poor - urban scavenging for discarded valuables like recycling. And this goes to well before the industrial revolution. To say a tradesman it wouldn't be worth taking their bones from a meal to sell to a gluemaker and just discarded it in the street. To the desperately poor it was input they could turn to money and was sort of a proto street cleaner to a society lacking modern waste disposal infastructure and institutions.
Walking around with the same strategy and constraints as everyone else won't work.
Lots of the money in the market is being traded by people who are managing over a billion dollars. They have to find investments that can absorb hundreds of millions of dollars. Your example of people collecting bottles is a perfect analogy of how anyone not moving millions of dollars can find good investments.
Also, it assumes that information is basically the same as 'news'. It's unlikely you will happen to be set up to respond to news as fast as whoever is fastest. However, to use information requires knowledge and comprehension, which is not considered at all. Most money on the market is being moved around by robots using fairly basic statistical models.
The efficient market hypothesis is that markets are efficient to present public information.
If markets were efficient to the present value of the future price at all times, then there would be no such thing as insider trading and hedge funds would all lose money.
You can make money by making inferences about present facts, or taking views on future occurrences.
Exploiting inefficiencies for gains is the mechanism by which EMH is supposed to work, so you're right that some people must be making money by trading intelligently.
But professionals have advantages that are difficult to match for small-time investors like: single-digit millisecond latency with exchanges, specialized hardware, sophisticated back-testing systems, proprietary data sources (market data, weather, retail data, etc. any data source you can thing of, some hedge fund is buying it), 60+ hours a week to work on their strats, qualified peers to bounce ideas, volume-discounted broker fees, etc.
Even then, professionals beat the market pretty inconsistently. Many people, including professionals, mistake luck for skill. So I think skepticism is justified when people online claim to have strategies that beat the market.
If you are one of the few who can actually consistently come up with strategies that beat the market, unless you are already rich, it might be worthwhile to work at a hedge fund and take a cut of the profits from trading large sums of other people's money instead of trading your own.
You can't say there are inefficiencies for institutions to exploit, but no inefficiencies for anyone else. Choose a consistent framework for how you view markets.
There are fast alphas, and there are slow alphas.
If you're an institution making markets on index ETFs, you can make money by having more accurate spot prices for the basket. Fast alpha.
If you're a vol trader, you are more worried about convexity of gap moves and the shape of the vol surface. For me, this means following the story of the name and thinking about where the vol surface doesn't properly reflect tail risk. Slow alpha.
I just assign very low prior probability that "this hobbyist investor I've just met on the internet can beat the market" is true. Not zero, but low. And I think it's a pretty well justified prior.
As a corollary to that, I don't think it's good advice to tell the average retail investor to try their hand at trading because most of the time it will not work out.
If you have managed to do it, more power to you.
The advantages I mentioned was what I saw at a not particularly large hedge fund with short to medium term trading strategies. They didn't do just market making, hedge funds do vol trading too.
Well, there are (small) inefficiencies for everyone to exploit. For example, a stock is mispriced and you expect it to return an additional 1% when the mispricing disappears. The difference between an institutional investor and a retail investor is that the institutional investor can invest $100 million in the stock and make $1 million of profit, while a retail investor with $100,000 will make only $1,000. As a result, institutional investors can afford to spend a lot more money on research, hardware, data, etc. It's very hard to compete with that as a retail investor.
I'm not clear why you mention insider trading here? Insiders have access to information that is not present public information, and so is not priced into the current value of the stock.
Yes, but no one claims that the market is strong form efficient. The question is rather whether the U.S. stock and bond markets are weak form (prices include all past trading data) or semi-strong form efficient (prices include all publicly available information).
