5 To what extent has the dot com bubble changed investor behaviour in the USA? Ethan Morse

This article was completed as part of the Churcher’s to Campus (C2C) courses

Ethan Morse Upper Sixth

The ‘Dot Com bubble’ describes the period from 1995 to 2002 where the share value of technology companies on the NASDAQ stock exchange skyrocketed, eventually creating a bubble 200 times the size of the underlying earnings of these companies. Over five years (1995-2000), the NASDAQ Composite Index rose over 500% to a value of 5,048.62 and then plummeted to 1,114.11, losing 77.9% of its value within only 2 years (NASDAQ Composite Index, 2020).

The main area of blame when it came to the creation of this technology bubble was focused around investor behaviour and how these investors ignored underlying issues in technology-centred companies such as profitability or longevity and, as a result, pumped money into these firms causing the creation of a bubble.

When this bubble finally burst, many large tech companies went bankrupt; this included even those who had been worth hundreds of millions a couple of years previous such as ‘Pets.com’ or ‘eToys. com’. This crash shook many investors who thought the market would continue to grow and believed the companies irms would bring in huge long-term profits and shows why it is important that investors change their behaviour when evaluating a company’s worthcompany’s worth. If investors ignored the effects of this bubble then there is reason to believe that the cycle of bubbles will continue, which could have disastrous effects on the world economy such as recessions, unemployment and deflation and this is more likely to affect individuals negatively rather than the investors themselves. impact on markets and public/private companies so the importance of that behaviour changing as a result of market crashes such as the dot com bubble is critical.

One crucial area of change likely to affect investor behaviour is the US regulation of the equity/debt markets. An example Unemployment, homelessness, crime, of regulation affecting investor behaviour increased debt and unavailability of cheap was the J.O.B.S (jumpstart our business credit are all factors that a crash can have start-ups) Act 2012 which was intended on individuals, while to encourage small most investors and [T]he chief cause business funding in the investment banks may feel few consequences. of the dot com bubble was the US by easing regulation, therefore encouraging more companies to issue In the future, the focus rapid investment initial public offerings of investing is likely to move from ‘day traders’ to artificial in newly created public (IPOs) and go public. One way this Act achieved this outcome was by intelligence which companies ‘easing requirements can make intelligent decisions, considering all information without through their IPOs. for companies with less than $1 billion in annual revenue for up to 10 years, the impact of investor up from the five-year time bias. This change is already occurring. span that was previously in place’ (Sinéad ‘Machines are likely to take up to 10 per Carew, a journalist, writing in 2018). cent - 25 per cent of work across all bank functions with AI and automation’ (HCL, A likely increase in IPO creation shows 2020) which should reduce the effect of that investor behaviour has not changed investor behaviour completely. However, significantly, as the chief cause of the dot investor behaviour still has a significant com bubble was the rapid investment in newly created public companies through their IPOs, which funded the bubble. This can be shown as: “In 1999, there were 457 IPOs and over 25% doubled in stock prices. But within two years, the infamous dotcom crash erased much of that progress. The number of IPOs plummeted to just 76,” (Bryan Martin, chairman of 8x8, a technology company, writing in 2008). This suggests that investor behaviour has not changed significantly as the regulation guiding it is directly encouraging the type of behaviour that created the dot com bubble by easing the process of firms issuing IPOs.

However, other regulation controlling investor behaviour tries to ensure a repeat the dot com bubble does not occur including the Sarbanes-Oxley Act (2002) which ‘is a law the U.S. Congress passed on

July 30 of that year to help protect investors from fraudulent financial reporting by corporations’ (Will Kenton, 2020) offering protection by forcing chief executive officers (CEOs) to sign off on the accuracy of their financial records. This regulation was passed to combat directly fraudulent behaviour by companies during the dot com bubble such as Enron Corporation, Tyco International plc, and WorldCom who manipulated numbers to encourage investors to inflate the stock price well above intrinsic value (Will Kenton,2020).

This regulation is evidence about changes in investor behaviour, as it allows investors to make more intelligent decisions about newly issued public companies, reducing the chance of stock price bubbles like the dot com bubble. With this in place, investors will see a potential bubble forming earlier and sell stocks, hence reducing the stock value before it becomes a meaningful drop. Overall, although the Sarbanes-Oxley Act demonstrates a change in regulation, aiming to change investor behaviour after the dot com bubble, the J.O.B.S Act is a more significant piece of legislation that encourages no change in investor behaviour.

Another area where investor behaviour could have been seriously impacted as a result of the dot com bubble was behaviour biases and heuristics. To evaluate the change as a result of these biases and heuristics, we must analyse the effect human bias had before the dot com bubble and after it.

Before the dot com bubble, investors showed two key examples of bias and heuristic, one being representativeness bias. It can be described as ‘when investors … label an investment as good or bad based on its recent performance.’ (Melissa Lin, 2020). Stocks such as Pets.com had a great initial performance as ‘The shares debuted at $11 and quickly went as high as $14.’ (Andrew Beattie, 2020). Investors saw the initial success and assumed that the in 2016 to 55% in 2019 (Statista, 2019).

business was sure to be a big titan in the technology industry; yet the company filed for bankruptcy nine months after its initial IPO.

Investors’ behaviour suggested they were influenced by representativeness bias since they used Pets.com’s incredibly successful initial IPO as an indicator of the firm’s long-term performance, resulting in them buying up the stock until it crashed. We can compare the impact of the repetitiveness bias after the dot com bubble to see the change in investor behaviour by looking at the 2008 financial crisis and specifically the housing market crash. Technology has aided the increase of casual investors entering the stock market who are untrained, and so may reflect investor behaviour before the dot com bubble. These untrained investors are more likely to be affected by biases, such as the representativeness bias discussed in the previous paragraph and so resembles investor behaviour before the dot com bubble suggesting that the overall behaviour of investors has not changed significantly.

However, there is evidence to suggest that technology has had a huge improvement in investor behaviour, enabled by the use of A.I. and complex algorithms. Technology has played a major part in equity research for major hedge funds and investment banks. Equity research is a far more efficient and reliable way of collecting data on potential investments.

Before the crash, many investors bought CDOs (collateralized debt obligations) A branch of A.I called Natural Language and other bond packages and assumed Processing is designed to make sense of that because the housing market had been human language via machine learning and on a strong rise in this gives hedge funds an the early 2000s these [T]he largest advantage as they have more CDOs would continue to generate returns on their investment. The area of change in investor information and can detect major trends beginning and old trends fading (Timothy influence of this bias is behaviour after Vasilyev, 2019). The market clear as these investors ignored the underlying issues which existed, the dot com bubble was due for acquisitions and takeovers has also been remarkably transformed by technology. such as the mortgage to the massive An example of this is Axial programmes these bonds were built on or the increasing default advancement in technology. Network which is a platform that connects start-ups with potential buyers/investors rates. Comparing these and has facilitated $25bn behaviours before and after the dot com worth of deals since its launch in 2010 bubble suggests that investor behaviour has (Timothy Vasilyev, 2019). This demonstrates not changed significantly and that biases that investors can have access to more such as the representativeness bias have information and so make more intelligent plagued investor behaviour in the USA. decisions when allocating capital and are therefore less likely to make uninformed Technology is an area which has changed and unwise investments, like the ones significantly since the dot com bubble and happening during the dot com bubble. This which has had a critical impact on investor overall improvement in technology suggests behaviour. The availability of technology retail traders and investors can make far has increased significantly due to lower more informed choices, removing the effect prices and an increase in advertising. The of human bias and showing a significant percentage of adults owning a laptop has change in their behaviour due to the change increased to 74% in 2019 (Statista, 2019) in technology. and the percentage of adults invested in the stock market has increased from 52% One significant way investor behaviour 4

helped to create the dot com bubble was the 2015) a common metric used is use of financial metrics to value companies called the ‘Contribution Margin’ and this influenced how investors behaved. which shows the profitability During the rise of the dot com bubble, of individual products. The investors chiefly used sales growth and Contribution Margin is used to stock price as a key indicator of a successful determine whether variable costs company; this allowed companies such as for a product can be reduced, or Pets.com and eToys.com to raise millions if the price of the end product at their IPOs with Pets.com raising $82.5 should be increased. This is a million in a February 2000 IPO (Andrew more accurate metric to use than Beattie, 2020). The issue with investor sales growth as it highlights the behaviour is that these metrics were invalid potential profit that a firm will when assessing the potential success make both in the present and in of a company. For example, ‘Pets.com’ the long-term and would have spent millions in advertising to attract highlighted ‘Pets.com’s inability consumers, including £2.2million for a to make a substantial long-term Superbowl commercial, profit. This designed to attract more customers.consumers. Sales grew from [T]he dot com bubble crash example highlights the change in the use of metrics to govern $1,776,000 in 3rd Quarter significantly investors and shows how 1999 to $11,570,0000 in 4th Quarter 1999 (Erika Matulich and affected investor the dot com bubble crash significantly affected investor behaviour by Karen Squires, 2008), behaviour. introducing more inand investors began to depth metrics to ensure purchase more equity causing the stock that investors take informed decisions price to inflate from $11 to $14 (Andrew when purchasing equity in companies. Beattie, 2020) even though the net losses increased from $15,852,000 thousand Overall, the largest area of change in to $42,423,000 thousand in those same investor behaviour after the dot com bubble quarters (Erika Matulich and Karen Squires, was due to the massive advancement in 2008). technology, as the development in A.I programmes has allowed investors to This evidence shows how the poor assess volatility and transformed risk use of metrics led to poorly informed almost into a security of itself. This investment choices. We can compare this shows a more significant change in their information to how metrics are commonly behaviour compared to the change in used, post dot com bubble, to evaluate metrics as while metrics have changed whether investor behaviour has changed and become more representative their significantly. According to (Jenna Taylor, implementation is down to technology and changes in A.I. Overall, technology is a bigger area of change in investor behaviour after the dot com bubble. The most significant factor that suggests that investor behaviour has not changed since the dot com bubble has been the lack of change in substantial regulation. Although the Sarbanes-Oxley regulation enforces the policing of companies who forge financial numbers, this act does not necessarily improve investor behaviour and allowed a significant asset bubble, the housing market in 2008, to occur and devastate the global economy.

In conclusion, there has been significant improvement in investor behaviour, mainly due to the improvement in technology, as A.I. not only removes any effect of human bias but can also compute information at greater speeds and higher amounts.