The Nordic Crisis of 1992
The Nordic crisis of 1992 refers to the series of bank runs and currency crisis that shook Finland, Sweden as well as Norway in the early 1990’s. This was the first major national banking crisis since the 1930’s (if wars are not taken into account). Thus, an important belief that the fractional reserve banking system […]
China’s Predatory Lending
The Chinese government has a bad reputation when it comes to finances. Most countries including the developed ones like the United States believe that the Chinese government regularly manipulates and outsmarts them. Now imagine if the strong Chinese government went up against smaller nations like Sri Lanka, Nepal, Pakistan, and Bangladesh! There would be no […]
Intermediaries to a Credit Card Transaction
In the past couple of decades, banks have started providing a new type of product called the credit card. The credit card is a revolving line of credit which is offered to customers. Customers can use the card to borrow money to make purchases. They are then offered a credit free period. If they are […]
Elasticity of Taxes
In the previous article, we have studied the concepts of the tax base and tax rate individually. Now, it is time to see how the two react. We already know the basics to some extent. We know that the tax base and the tax rate move in opposite directions. Hence, ideally, if we increase the […]
Is Corporate Tax Progressive?
Taxes can be classified based on which class of the population pays the most. The purpose of taxation is to redistribute wealth from the rich to the poor. Taxes that help the government do the same are called progressive taxes. The corporate tax has been levied on the premise that it is a progressive tax. […]
Algorithmic trading was considered to be a bookish concept developed by geeks. Less than a decade ago, mainstream traders at Wall Street laughed at the idea that they may have to compete against machines. However, they have been proven wrong. The rise of algorithmic trading is no laughing matter.
In about a decade, financial markets have come to be dominated by machines which are rich in artificial intelligence. The number of people been employed as traders has gone down drastically. Instead, people with advanced degrees in statistics are employed to help develop such algorithms.
In this article, we will have a closer look at the concept of algorithmic trading.
Algorithmic trading has become much more commonplace than one would imagine. The numbers prove this claim. Close to 75% i.e. three fourths of all trades that are happening on Wall Street are originated by algorithms.
The image of Wall Street has undergone a complete transformation. From being a place filled with humans and chaos, it is now full of silent rooms which house servers. The chaos does still happen on Wall Street, but it happens in the realms of the machine world. As humans, we only get to witness the output i.e. the rise and fall in prices.
The flash crash refers to a drastic collapse in the stock market due to the trading done by algorithms. On the 6th of May, 2010, in a matter of minutes, the New York Stock Exchange and NASDAQ dropped by close to 10%. Investigations found no particular cause for this drastic fall. In fact, most of the losses caused by the fall were reversed in the first few days of resuming trading itself. The huge fall was largely a mistake made by the machines, a mistake that proved to be extremely expensive as trillions of dollars of market capitalization were wiped out within seconds.
The flash crash has not deterred companies from building bigger and faster algorithms. The newer algorithms can bring the entire financial world to its knees even faster. The trades now happen in micro seconds as compared to milliseconds earlier. This means that an algorithm can now execute more than a billion trades in a matter of about 10 minutes!
Critics have compared these algorithms to weapons of mass destruction. Once these algorithms start placing trades, they are virtually unstoppable in the short run.
Financial trading has become all about speed. A lag of even microseconds can cause people to lose and gain billions. Companies like Goldman Sachs are building arbitrage models that are based on the speed of their superior trading systems. Hence, latency of any kind is simply unacceptable. Therefore even though the data travels at the speed of light, companies still want to move their servers as close to Wall Street as physically possible. The trading game is now a race wherein even a lead of microseconds makes a huge difference.
Exchanges have also been welcoming algorithmic trading. This is because their basic nature has undergone a change. Exchanges were earlier not for profit institutions whose sole objective was to create conditions that were appropriate for raising capital.
Now, their objectives have changed. They now work to maximize revenue. Exchanges generate revenue when they sell data and when they charge a commission on the trades. Algorithms consume lots of data and make lots of trades. Hence, they are extremely beneficial to the exchanges.
Investors used to take pride in the eye that they have for value stock. They would talk about holding the stock for years. Warren Buffet calls himself a “decade’s investor”! However, algorithmic trading has changed all that. These algorithmic investors simply aim to exploit the price differentials. They are often programmed with human behavioral patterns to enable them to make better buy and sell decisions. The average time that algorithms hold the stock for is 22 seconds! The focus has completely shifted from value to price.
In the modern world, everyone has algorithmic trading systems. Hence, there is no advantage to having one. Advantage arises when the one that you have works faster than the ones the others have. Remember that trading is now a speed game.
Therefore, modern algorithmic trading systems also create junk data along with trading data. They dump this junk into the marketplace. This junk is then picked up by others who spend time in processing it. The system that originates the junk can simply disregard the additional data. Hence, they can compute faster and make more appropriate trades!
Strategies aimed at slowing down the competitors have flooded the financial markets with useless data. This has raised ethical and regulatory questions that cannot be answered as of now since trading has far surpassed the regulatory environment.
The question that arises now is whether we want to live in a world where our finances, our retirement funds and even our lives are dominated by algorithmic trading systems. These systems have the potential to go out of control. The glimpses of this were seen in the flash crash. Hopefully, the world never has to experience the full scale malfunction of these algorithmic trading systems.
Your email address will not be published. Required fields are marked *
