Effects of Markets 2.0

In markets 2.0, I refer to the data that is generated as part of normal market transactions. The 2.0 references web 2.0, where the ‘social data’ generated by web interactions and transactions has acquired a kind of life of its own. I make no super-special claims that markets now are wholly different from markets in the past. But some of their properties have become increasingly visible and important.

Let’s take the basic case. In a financial market, if Gordon Gecko and I make a trade, a couple things happen. First, money goes in one direction, and a commodity or security goes in the other direction.

I’m playing a bit fast and loose here, but you get the idea. Let’s call this markets 1.0. Exchanges like the occur all the time in lots of different places. And if you wanted to generate outwards, I interact with all kinds of people in ‘markets 1.0’ mode – iTunes when I listen to a song, colleagues when I ask about a job, my bank when I enter into a transaction. I have in mind a particular case (capital markets) of what I think is a more general phenomenon.

When our transaction is ‘seen’ by others, in the form of posting it publicly or trading in a public forum, an additional piece of data gets generated by our transaction. It is this generated piece of data that I want to offer some more sustained analysis.

This puff of data – the reporting of a transaction between traders in a stock exchange or Board of Trade – was itself contentious back in the day. When, at the turn of the 20th century, the Chicago Board of Trade was trying to distinguish speculation from gambling (no mean feat even then) one tool in its arsenal was to prohibit the distribution of its quotations to so-called bucket shops. If Gordon Gecko and I were to wager on the daily closing prices of the NYSE by betting each other $50 that it would be higher or lower than its opening, that would be gambling. If we bought or sold daily futures contracts based on the NYSE’s daily closing prices, that would be speculating. But without access to the NYSE prices, it would be impossible for us to bet on its opening or closing prices. This is what the CBOT was trying to do. It was arguing that it could restrict Western Union from distributing its quotes to some organizations, based on what those organizations were doing with the quotes. And the Supreme Court, in 1905, confirmed their right to do so.

Contracts under which the Board of Trade furnishes telegraph companies with its quotations, which it could refrain from communicating at all on condition that they will only be distributed to persons in contractual relations with, and approved by, the Board, and not to what are known as bucket shops, are not void and against public policy as being in restraint of trade either at common law or under the Anti-Trust Act of July 2, 1890.

– Board of Trade v. Christie Grain & Stock Co., 198 U.S. 236 (1905)

This kind of restriction would be surprising today. Especially since there are places like InTrade where the point of the thing is to wager on the future prices of the NYSE. Now, imagine if the NYSE just decided to no longer distribute the time & sales data for stocks traded on their exchange. We know that, like private equity arrangements that happen all the time, transactions would continue. But that piece of extruded market information – that signal – has become central to our conception of what the stock market is and how it works. It has become an indicator of our society’s health, even of popular sentiment towards US foreign and domestic politics.

More specifically, this information-bit has become central to the work of other traders in figuring out how to act within the market itself. How do we know this? At Eurex, the dominant European futures exchange, quote traffic has increased pretty dramatically in just the last few years.

And it is not just an increase in trading, but an increase in the desire for more and faster information about the trading in which other people are engaging. As Voyles notes in the article, in 2000, Eurex had 1.2 quotes per contract. In 2004, it was 2.16 quotes per contract. In 2005, 7.88 quotes per contract. And in 2006, it had climbed to 17.09 quotes per contract. People are taking the quotes and using them in real-time for analysis of their potential trades, to inhabit and back-test models, and to seek patterns in the noise that is the market.

This is my point: that the quotes themselves have come to have a value both within the context of trading, but also outside the immediate decision to engage in a market transaction.

In a now-classic 1981 article, Harrison White suggested that the appropriate way to think about production markets was less about supply-meeting-demand and more that production markets are “tangible cliques of producers observing each other. Pressure from the buyer side creates a mirror in which producers see themselves, not consumers” (White 1981: 543-4). I think we might be seeing something similar in financial markets, with quotes, time & sales, trends, and the like acting the part of the mirror.

And derivative to this, once the data becomes identifiable not just as a time & sales transaction, but as a transaction tied to someone they know already? Well, the importance of the data deepens and its effects on trading increases. In one of my favorite examples, Georges Harras and Didier Sornette created simulations to model traders acting independently, with some amount of shared information, and with a large amount of shared information. It turns out that the largest price swings in response to both news and market events comes when (simulated) agents enact a high level of copying among traders.

Information about the market and generated by the market become vital as you trade on price changes rather than on anything particular you want or need from the transaction itself. (As an aside, I think this is intimately related to the shift from trading issues to trading generalized, objectified risk, but alas there is only so much to put in a post).

Some of the broader consequences of markets 2.0 are pretty remarkable.

Fragmentation of Liquidity via Dark Pools
We’re seeing something remarkable in the world of finance, an attempt in the name of ‘not affecting the market’ to minimize the market signal thrown off by trades by institutional investors. Because so many people are on the lookout for big traders making big trades, these big traders have begun disguising their activities and hiding their tracks. This is not new – when I worked on a trading floor, there was a shotgun-pumping hand signal for ‘reload’, meaning that someone is buying 5000 contracts 50 at a time. Big ‘paper’ (institutional investors) often were ‘lurking in the tall grass’, meaning that they were buying or selling little bits but everyone knew they had lots more trading to do.

But the phenomenon of dark pools is more significant because in the equities markets, institutional investors are opting out of the main trading markets in favor of private trading systems. These systems are literally parasitic on the prices of the larger trading exchanges – trades in these ‘dark pools’ are not made public, actors are not identified. This produces a ripe opportunity for fraud, of course, but it also is a way of saying that it is in at least some peoples’ interests to minimize the market signal their trading throws off.

And the pools of dark liquidity are large, and growing. Currently, about 10% of all equity trades are made through dark pools. Think about it this way: the market signal from trading is both increasingly relied upon to make trades and at the very same time, it is being masked by an increasing number of traders.

Monetizing (and transforming) the signal
A second consequence of markets 2.0 is the transformation of this signal from something ‘epiphenomenal’ to something both more central and having properties and value in its own right. Information markets fall broadly into this category, including my favorite, the Hollywood Stock Exchange. You pretend to buy or sell ‘movie stocks’ and the subsequent signals generated by these fake transactions are then used by the HSX as a product to sell:

HSX syndicates the data collected from the Exchange as market research to entertainment, consumer product and financial institutions and as original content to radio, television and print media. Founded in 1996, HSX is now a subsidiary of Cantor Fitzgerald, L.P. HSX is headquartered in Century City, California.

In and outside the financial arena, this emphasis on the formerly unmined bits of market slag – which refers to the byproducts produced when smelting ore into metal – have been transformed into marketing and market gold. Take a look at last.fm, or mint.

It’s time to get on top of this stuff, economic sociologists. Time past, in fact.

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