During the 2010 Flash Crash, the market briefly lost nearly $1 trillion in value. Institutional and individual investors saw massive declines in their holdings.
For example, Accenture’s stock fell from approximately $40 to just a penny before rebounding.
Procter & Gamble’s shares also dropped nearly 37% within minutes, significantly affecting investors’ portfolios and causing widespread panic among stakeholders reliant on market stability for their operational strategies.
Algorithmic Trading Dynamics
The effect of the Flash Crash of May 6, 2010 had an essential impact on the effects of algorithmic trading. The situation on the market caused the fall of the Dow Jones Industrial Average by 1,000 points in ten minutes.
Trading automated programs reacted to the data from the market and the presence of the already made orders by the dramatic and massive sales of large amounts of stocks. As the reports note, high-frequency trading algorithms were selling the stocks and supplies in milliseconds and maintained the level of sales at extreme volumes that the market could not withstand.
The massive response to the downward trend with the market by the increasing amount of orders volume contributed to the imbalance of the market and affected the stocks falling rate even worse. The decision to sell is always made by the algorithm according to the presence of the stopping orders, and the order of the stops is determined by the computer’s algorithm. The enormously fast speed of the selling orders combined with advanced volumes that the market could not hold and resist affected the situation.
As the famous British economist John Maynard Keynes once said, “Market can stay irrational longer than you can stay solvent.” The decision making on selling and buying has no human factor of taking into account their emotional stability and presumes the sales or investments based on the calculated data produced by the algorithm.
Technical Glitches and Their Impacts
In many instances of trading platforms, there is rapid and unintended financial occurrence due to a technical glitch. One such occurrence transpired on August 22, 2013, when a glitch in Nasdaq’s trading system stopped transactions for three hours. Consequently, the fiasco seeped into over 2,000 stocks like Apple and Microsoft. Typically, markets open at 9:30, though in that particular day, it was different. Additionally, the glitch delayed trading as many financial organizations and analysts could not ascertain the extent of the financial risk. Therefore, a technical glitch causes rapid unintended financial consequence.
Consequently, the trading volume dropped by approximately 40% of what it was during the preceding week. This action reflects the tremendous financial risk that characterizes a system glitch. Therefore, financial analysts and regulators require ensuring that market systems are well tailored and strong uncontrollable systems. “We must devise a method which will bring all the facts to light.” Joseph P. Kennedy.
Market Manipulation Tactics
Making use of market manipulation tactics can trigger serious disturbances, as shown by the case of 2010 Flash Crash. On this day, trader Navinder Singh Sarao used a tactic of “spoofing” to influence the prices . Specifically, he posted multiple large orders of E-mini S&P future to sell, which he later cancelled.
Although the orders were fake, they created an image of the market-moving down among other traders and algorithms, which began to sell aggressively. The modified minimum quantities of orders only accelerated the process.
As a cumulative effect, these actions resulted in a 9% plunge of the Dow Jones Industrial Average, causing the market value of nearly $1 trillion to be wiped out within minutes.
Therefore, the relevance of unethical tactics in the context of flash crashes illustrates that both regulators and the technology developed to facilitate fair trading should be incredibly alert and robust to detect and eliminate any threats to fair trading at once. As a former U.S. President Theodore Roosevelt said, “Every man holds his property to serve the general welfare; … every man holds his time, his talents, and his labor to use to support the advent of some good cause” . In other words, it demonstrates that every representative of the industry is obliged to support the waste management or another organization fighting to improve sanitation conditions in his sphere.
Regulatory Gaps and Challenges
Regulatory gaps often serve to augment the severity of flash crashes. Outdated and/or insufficient regulatory mechanisms are not prepared to handle technological rise in trading in general, and high-frequency trading in particular. 2010 Flash Crash is one of the most striking examples.
The regulatory frameworks were unable to deal with the complexities of ultra-high frequency trading. Existing mechanisms failed to promptly address the problem of trading that is too fast. Market crash was just as quick if long-lasting and deep. It shows how real-time monitoring systems and adaptive regulation are needed . After this crash, the US Securities and Exchange Commission imposed more stringent rules surrounding algorithmic trading. They also introduced more powerful market circuit breakers, which could halt the trading process during extreme volatility. The results of their efforts so far were the absence of the similar crash and an ample buffer from similar precipitous drops in the future.
There is a quote from John F. Kennedy, which goes well with this process: “There are risks and costs to action. But they are far less than the long-range risks of comfortable inaction.” It is especially valuable in the cases of financial market regulation where action has to happen to prevent massive and costly inaction.
Historical Precedents of Market Anomalies
It is evident that learning from history helps to prevent the prospect of repetition. Historical precedents of market anomalies provide a clear way to understand the root cause of flash crashes, while also weighing the various tools and instruments available to trigger or stop the occurrence of a flash crash.
A case in point can be the Black Monday crash that occurred on the 19th of October, 1987.
The Dow Jones Industrial Average crashed by 22.6% in a single day. The main reason behind the crash was the use of portfolio insurance by institutional investors. This investment strategy was particularly dependent on the automatic sell orders generated by computers. The use of these then-innovative tools led to a major crash in the stock market. The devastating effects of these then-innovative tools show the need to heed the advice of philosopher George Santayana : “Those who cannot remember the past are condemned to repeat it.”
