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Rational revolutions: Understanding tech stock bubbles
The widespread adoption of new technologies – from the automobile to the Internet – tends to be accompanied by stock market booms and busts. Why do the stock prices of innovative firms tend to exhibit apparent “bubbles” during technological revolutions?
Issue Date - 24/11/2011
During technological revolutions, stock prices of innovative firms tend to exhibit bubble-like patterns. After an initial surge, stock prices usually fall in the presence of high volatility, as they did during the “biotech revolution” of the early 1980s and the Internet craze of the late 1990s.

While the bubble-like stock price behaviour is commonly attributed to the irrationality of overenthusiastic investors, why would investors make the same mistake over and over again? In our recent study titled “Technological Revolutions and Stock Prices,” we propose the first rational explanation for why stock prices should be expected to exhibit a bubble during a technological revolution – a period concluded by a large-scale adoption of a new technology. Our explanation for the bubbles is that the nature of risk associated with new technologies changes over time.

Uncertainty about productivity gains is a natural feature of innovative technologies. At first this uncertainty, or risk, is mostly “idiosyncratic,” because the new technology is initially developed on a small scale and the probability of large-scale adoption is low. For new technologies that become widely adopted, the uncertainty gradually changes from idiosyncratic to “systematic.” When systematic risk increases, prices decline. These increases in systematic risk can be expected in hindsight, by researchers who look back knowing that the revolutions took place, but they are unexpected by real-time investors who do not know whether the new technology will eventually be adopted on a large scale or not.

The “bubbles” should be most pronounced in revolutions characterised by high uncertainty about, and fast adoption of, the technology – such as the recent Internet revolution.

We developed an economic model to provide a rational explanation for stock price movement during technological revolutions. To test our model, we examined stock prices in 1830–61 and 1992–2005, the respective periods when railroad and Internet technologies spread in the United States. Bubbles are not merely possible in a rational world, but should be expected during technological revolutions.

the changing nature of risk

In order to explain how stock prices should behave during technological revolutions, we developed what economists call a “general equilibrium model.” In the model, investors study the productivity of a new technology, and must decide whether adopting this new technology on a large scale would be worthwhile. Large-scale adoption would constitute a technological revolution. We determine the optimal time for adopting the new technology and show that when the technology is optimally adopted, there should be bubbles in stock prices.

The problem we solve resembles the problem of making an irreversible marriage decision. It is generally sub-optimal to marry a new acquaintance immediately because of substantial uncertainty regarding the quality of the personality match. Instead, it seems advisable to first develop the relationship on a small scale, by dating without any commitment, and then to marry if we learn that the relationship is likely to work in the long run. The model has two sectors: “new economy” and “old economy.” In the new economy, small-scale production uses new technology. In the old economy, large-scale production initially uses old technology and switches to new technology if the latter appears to provide additional productivity gains. When this switch occurs, the inherent risk of new technology becomes systematic in nature, since it affects mass-scale production and aggregate economic growth. However, if the new technology turns out to be faulty, it may stall aggregate economic development.

Stock prices initially rise during a revolution because of good news about the productivity of the new technology. As the probability of large-scale adoption increases, the systematic risk in the economy increases as well, because it becomes more likely that the risk of the new technology will affect mass production. There are two measures of systematic risk that increase during technological revolutions: the stock volatility of the old economy and the “beta” of the new economy. A “beta” captures the sensitivity of the stock price to the aggregate stock market. If a stock has a beta of 2, and the aggregate stock market goes up by 1 percent, this stock’s price will typically go up by 2%.

Breaking it down into these two pieces, we show that systematic risk increases in both the old and new economies; thus it should be expected that stock prices fall after a run-up in both economies. New economy stocks are expected to fall more than old economy stocks shortly before the adoption of new technology.

The model produces the following empirical predictions that should apply to technological revolutions: (1) the bubble in stock prices should be more pronounced in the new economy than in the old economy; (2) stock prices in both economies should reach their lowest levels at the end of the revolution; (3) the new economy’s market beta should increase sharply before the end of the revolution; (4) the new economy’s volatility should rise sharply and exceed the old economy’s volatility; (5) the old economy’s volatility should rise, but less than the new economy’s volatility; (6) the new economy’s beta and both volatilities should all peak at the end of the revolution; and (7) the old economy’s productivity should begin rising at the end of the revolution.

The internet and railroads

We found substantial support for our empirical predictions in evidence from railroad and Internet technology stock prices. For both technological revolutions, we considered the key quantities in the model, such as the new economy’s market beta and the level and volatility of stock prices. Today, Internet technology is an indelible part of the economic landscape. However, in the mid-1990s, it was not clear that the Internet would play a dominant role in the economy. The predictions of the model, however, were all supported by empirical evidence from the Internet revolution.

We used the technology-loaded NASDAQ stock index to represent the new economy and the NYSE/AMEX to represent the old economy. NASDAQ’s beta doubled between 1997 and 2002, which is highly statistically significant. There was a clear “bubble” in the new economy, whose market value increased five times over, and then fell by more than half. The bubble pattern was much stronger in the NASDAQ index than in the NYSE/AMEX, with stock prices in both reaching bottom in 2002. The NYSE/AMEX’s return volatility doubled and NASDAQ’s volatility tripled over the same period. NASDAQ’s beta and both volatilities peaked in 2002. These patterns also support other predictions of the model.


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