The advent of digital technologies has renewed and reshaped the financial landscape. Today, securities are bought and sold mainly through computer programs that react in nanoseconds (faster than a person can) to the smallest fluctuations in the market.
On the selling side, the formation and liquidation of securities portfolios has undergone tremendous changes due to the computerization of processes over the past 50 years, and more recently the advent of big data. Famous scenes in which a crowd of brightly dressed stockbrokers crowd one another, frantically waving their hands and shouting their orders on the floor of the house. Stock tradingalthough it is still sometimes produced for marketing purposes, it is now a thing of the past.
Two new technologies
Electron stock market operations rely on at least two types of technology. First, exchanges have automated the process of matching buyers and sellers of securities. Say, for example, that you want to buy 1,000 shares of L’Oréal. The bank or broker will then place your order via Euronext, one of L’Oréal’s listed marketplaces. Euronext constantly receives, buys and sells such orders, matching them using computers and algorithms.
This is indeed a profound change, but you should know that Euronext also collects massive amounts of data about orders placed and transactions executed…which can then be resold to other brokers and investors. In this respect, trading platforms are increasingly similar to others platforms Platforms, such as Facebook, Google or Twitter, and the share of their income from selling data is growing exponentially (+13% approx annually since 2012).
The second type of technology relates to the automation of decisions to buy or sell securities by players in the sector. The use of algorithms to make portfolio decisions is called Algorithmic trading. In a single day, the asset manager can thus buy or sell millions of shares of a given security in response to the inflows of investors in and out of his fund. This automation process is the same as that seen in other industries, where humans are replaced by machines.
Some companies specialize in High frequency trading Using algorithms that rely on extremely fast access to information (less than milliseconds), especially market data sold through electronic trading platforms. With their privileged access to this data, these companies can take advantage of small price differences for the same stock between two platforms. Some of them even pay to host their own computer servers near the trading platforms, or even rent space in the same room to save a few precious nanoseconds, which can make a huge difference in the transmission of information.
The impact of these developments on the trading costs of other market participants is a controversial topic, and raises many issues that are today at the center of policy discussions in the European Union and North America.
Regulations to be drawn up
The European Securities and Markets Authority (ESMA) and several national bodies, such as the Autorité des marchés Financiers (AMF) in France, are the main regulators of stock markets in the European Union. the Securities and Exchange Commission (SEC) f Commodity futures trading commission (CFTC) covering the US markets.
A number of issues related to the effect New technologies They must be examined by these authorities. For example, does the electronicization of financial markets actually reduce the cost of creating and liquidating portfolios for investors? Thus investors can get much higher returns on their savings. Does algorithmic trading make financial markets more or less stable? Do trading platforms have significant weight in pricing their market data?
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in our recent work Article In research, we also ask the question whether trading should be slowed down. The problem is that high frequency traders can make excessive profits, at the expense of other participants.
Some platforms also have less stringent transparency requirements than the major exchanges, which can cause concern. The volume of so-called “dark trading” (private trading networks) is on the rise, and now accounts for about 40-50% of stock trading in the EU, which leads to the need to regulate “dark pools” more strictly. Finally, there is also the question of how far algorithms risk destabilizing financial markets and leading to strong price swings.
What the future holds
In the coming years, the economic model of stock exchanges must increasingly rely on the monetization of data generated by trading. There may then be a certain competition between the trading platforms to attract users, who generate this data, like what the tech giants do.
This trend, which has accelerated during the Covid-19 pandemic, if continued, will put strong competitive pressure on brokers and ultimately lower trading costs for investors. Perhaps at some point, the data generated by the transactions will pay more than the transactions themselves. So it could be the case that at some point trading platforms have to do more to attract users, for example by paying you to put your trades out there, only for you to use them and generate more data !