The Gap-Old Navy Breakup
Economies of scale provide a significant advantage in the retail industry. This is the reason why all retail companies try to become bigger. However, to the surprise of many American retail giant GAP Inc has decided to reduce its size. GAP is home to many famous brands like GAP, Banana Republic, Old Navy, Athleta, Intermix, […]
The Deepening Insolvency Theory
Timing is everything when it comes to bankruptcy claims. Any company facing the threat of bankruptcy has a duty to ensure that it maximizes the enterprise value. This means that the company, its lenders, and its managing officers have an inherent duty to ensure that one particular group of stakeholders is not benefitting at the […]
Bears in the Bond Market
If certain high profile fund managers and bond investors are to be believed, then the bond market has just slipped into a bear market. They are not talking about the usual tightening of the Fed’s interest rates. Interest rates have risen several times over the past few years. However, every time they return to normal. […]
Types of Capital Rationing
As discussed in the previous article, capital rationing is a form of capital budgeting. In capital rationing we change the unlimited capital assumption of capital budgeting and we try to choose projects with the finite capital that we have on hand. This finite capital may be in the form of capital that the firm already […]
Self-Control Bias
Investors who have been in the market for a long time know that investing is an emotional activity as much as it is a financial activity. This is the reason that people who have a higher degree of self-control generally tend to do better than their peers. Self-control bias may seem like an obvious and […]
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 *
