The Dot.com Bubble

The mid-1990s marked the beginning of a new form of market environment that one could do business through the Internet. This was also the beginning of the so-called dot.com boom in the Spring of 1995 and it would later go bust in the fall of 2000. A year after the bubble burst, 327 companies remained but every one of them experienced the stock price slide beginning in September of 2000 (Becker, 2006, p.34). Amazon.com is the first major company that attempted to use the Internet to offer and sell products. In addition to the companies that sell online, companies that provided telecommunications and Internet support were also born such as Cisco Systems and Lucent Technologies (p.34). Other companies entered the market to provide web browsers such as Netscape. Another segment in this market is the service providers that provided users access to the Internet such as America Online and CompuServe (p.34). Finally, there are websites that offer web content and information for sale (p.35).
These online companies, in order to raise capitalization either approached venture capitalists for financing or offer their stocks to the public. Becker (2006) cited that nature of these IPOs from online companies as “examples of speculative bubble” (p.41). A bubble or boom results from assets being over valued and they continue to rise for an extended period (p.41). In bubbles or booms, there is also the element that involves behavior – crowd or herd. Although many were initially were sceptical about the viability of these new companies, the rush of many willing to take the risk causing a stampede and throwing sensible investing down the drain prevailed.
Westerhoff (2003) posited that crashes are forms of extreme shocks to financial markets. However, post-analysis on crashes showed inconclusive evidences that new information predicting crashes may be inconsistent with the efficient market hypothesis stating that value of stocks are reflected by their fundamental values (p.829). Upon closer scrutiny, crashes more often than not are caused by inherent market instabilities. Westerhoff (2003) mentioned two types of investors – fundamentalist and chartists. Fundamentalists primarily “bet on mean reversion” while chartists “extrapolate past price changes into the future to predict prices” (p.830). Callahan and Garrison (2003) traced the events that comprised the boom and bust episodes of dot.com companies to new money making its way “from the Federal Reserve, through the banking system, and finally to the dot-com start-ups. This liquidity led them to bid up the price of capital goods that were complementary to their business plans” (p.68). However, as the market prices rose, it also became evident that most dot.com companies’ business plan would not work. Another factor influencing market reaction is consumer behaviour. Many investors during those periods invested unwisely thus inducing artificial booms.
The combination of “trend extrapolation and optimism stimulates bubbles” (p.830). In dot.com companies, bubbles were consequences of “meteoric rise in the prices of Internet stocks, unexplainable in terms of fundamental value, and their equally spectacular fall” (Taffler & Tuckett, 2005, p.1). The Internet sector comprised of 6 percent of the market capitalizations of all US public companies. It also took up 20 percent of the publicly traded equity volume (p.1). The Dow Jones Internet Price Index posted a 500 percent increase from October 1, 1998 to March 9, 2000. Unlike the S&P 500 where it could only obtain a 35 percent increase for the same period (p.1). The dramatic increases in valuation of dot.com companies were to some extent “driven by investor mania” and “investor irrationality” (pp.3-4). Internet stock pricing deviated from the standard of referring to previous performances, trading history, revenues, profits or dividends to justify their valuations. Internet stocks’ “reported profits are positively valued, losses are negatively priced, i.e. the larger the losses the greater the market value” (Taffler & Tuckett, 2005, p.5). These shortcomings proved to be a costly lesson for the sector. Post-bubble era mandates the “return of “real” valuation measures” and significant structural and valuation changes were implemented (p.5). To some degree, it was difficult to explain the valuation methods of dot.com companies. Taffler and Tuckett (2005) offered an alternative way of viewing the valuation process. According to them, the dot.com valuation experience could be best explained using psychoanalytic traditions where, asset valuations may be driven more by emotion than cognition, knowledge of the subtle and complex way emotions and affects determine psychic reality will be of ongoing use in understanding stock valuations more generally and complement the contribution of conventional normative valuation models (p.21). Hong, Scheinkman and Xiong (2006) explored the relationship between asset float and stock price bubbles. The authors rationalized why the Internet bubble burst in 2000.
First, the optimism effect due to heterogeneous initial beliefs suggests that as float increases, the chance of optimists dominating the market becomes smaller, which leads to a smaller bubble. Second, a larger float corresponds to a smaller resale option, and again a smaller bubble. Finally, after the expiration of lockup restrictions, speculation regarding the degree of insider selling also diminishes, yet again leading to a smaller internet bubble (p.1076).
Citing the three studies indicated that extreme events had little to do with the bubble bursting for the Internet sector in 2000. Majority of the authors pointed to endogenous factors and human behaviors that pushed the stocks to their limits. For Hong, Scheinkman and Xiong (2006), “investors [can] have heterogeneous beliefs due to overconfidence and that they are short-sales constrained” (p.1101).
Taffler and Tuckett (2005) proposed psychoanalytical model to explain the dot.com bubble burst. The authors believed that Internet stocks presented an alluring view for would-be investors through incessant bombardment of information coming from financial journalists and analysts. The authors call this phase “emerging to view.” After clearly dangling the bait, the investors are in a mad “rush to possess.” The Internet stocks “stimulate a headlong euphoric craze among investors because of their particular power to generate further compulsive behaviour driven by unconscious intergenerational as well as intragenerational rivalry” (Taffler & Tuckett, 2005, p.7). The third phase would be a slow realization that the impulse was unwise as conventional methods to valuation are applied to the Internet stocks. The authors referred to this as the “psychic defense” mode. Realization sinks in and “panic phase” sets in as reality competes with the ideal (p.7). The final phase is the “learning from experience and maturation” phase where investors reflect on their actions.
The fundamentals of the Dot-com bubble were quite alarming and most of the new public companies were not making profit at all. The IPOs were skyrocketing and the business model was not portrayed no profit at all. These red flags were seen early on as the investors were aware that a crash was imminent so that they were able to do some remedy to the situation. However, the rest were left to fight and sell their devalued stocks (Lessons from the Dot-com Bubble).
Indeed, whatever positive thing they saw for the Dot-com bubble was supported by the belief that internet business was making it big time and that going to retail stores was a thing of the past. There were issues that were not taken into consideration and the customers had to pay heavy shipping fees which were seen as not important at all. There were unrealistic projections which did not materialize (Lessons from the Dot-com Bubble).
During this time, astuteness for business was eschewed in favor of operating at a net loss so that it could capture market share and at the same time build brand awareness. The assumption then was that moving quickly in order to capture the market share will spur solid foundation. That was not what happened though because even if the plan was sound, there could only be only one network effects winner in each field or sector (The Dot-com Bubble). Efficient market hypothesis asserts that market efficiency is reflected in the quality of information provided and how that information is incorporated and replicated in the market prices. For crashes, boom and bust cycles, it would take more than a single event for them to affect the market’s behaviour and performance. In crashes, several consecutive events build over time. In bubbles, they also take both endogenous and exogenous situations for the market to feel the direct impacts. Extreme events do occur but several studies all concur that extreme events alone do not necessarily cause markets to behave erratically. Overall, the extreme events will always pose a challenge for investors to overcome. With the right information, the investor can make wise decisions and avoid the path of dot.com companies whose bubbles burst after it was apparent that they could not live up to their promises. While a third of the companies that began during the dot.com bubble failed, majority managed to stay afloat and showing that cyber economy is plausible.

References
Becker, W.H. (2006). The dot.com revolution in historical perspective. Entreprises et Histoire, 43, 34-46.
Callahan, G. & Garrison, R.W. (2003). Does Austrian business cycle theory help explain the dot-com boom and bust? The Quarterly Journal Of Austrian Economics, 6(2), 67–98.
Hong, H., Scheinkman, J. & Xiong, W. (2006). Asset float and speculative bubbles. The Journal of Finance, 61(3), 1073-1117.
Lessons from the Dot-com Bubble. Retrieved December, 2009 from: http://www.theinvestorsjournal.com/lessons-from-the-dot-com-bubble/ Taffler, R.J. & Tuckett, D.A. (2005). A psychoanalytic interpretation of dot.com stock valuations. Retrieved December, 2009 from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=676635#PaperDownload
The Dot-com Bubble. Retrieved December, 2009 from: http://www.econport.org/content/handbook/Internet-Economics/dotcom.html Westerhoff, F. (2003). Bubbles and crashes: optimism, trend extrapolation and panic. International Journal of Theoretical and Applied Finance, 6(8), 829-837.