- Exciting new technologies and the companies that create them seem like obvious
investment opportunities. Why wouldn't you want to invest in the companies leading a new world changing technological paradigm. Each past technological
revolution has changed the world in profound and distinct ways. But their relationship
with financial capital has been remarkably consistent. While we can't predict
how emergent technologies will change the world, we can draw insight from how financial markets have behaved through past technological revolutions. I'm Ben Felix, in this episode
of common sense investing, I'm going to tell you what to expect from investing in
technological revolutions. (upbeat music) A technological revolution is a big deal. It modernizes all existing industries. Increasing the full spectrum
of economic productivity. It is easy to get caught believing that today's most successful industries and companies are unlike anything that we've seen in the past. But within the social and
technological paradigms of their time, past technological
revolutions have resulted in unprecedented surges in
productivity and growth. The relationship between these
technological revolutions and financial capital has
followed a consistent pattern. This pattern was summarized
in a model proposed by Carlota Perez in her 2002 book, "Technological Revolutions
and Financial Capital." First, there is an
eruption of the revolution resulting from incremental advances and innovations that
culminate in a technology with the capacity to increase
the economy's productivity and the financial capital to support it. This is followed by two or three decades of the new technology being
installed in the economy. The installation phase can be turbulent as the new technology
divides the economy into old and new creating social
and economic divisions regulatory turmoil, and wealth inequality. The installation period has
historically been accompanied by what Perez calls a
major technology bubble, centered on the new
breakthrough technologies and spurred by the extraordinary
profits produced by them. The major technology bubble
is as with any bubble, followed by a collapse, the collapse leads to a re-composition of the regulatory framework
that sets the conditions for the final deployment
period of this new technology. The final phase consists
of more organic growth in financial assets that
lasts until the limits to productivity and growth from
the technology are reached. Setting the stage for the
eruption and financing of the next technological revolution. The major technology bubble
tends to happen midway in the process of a simulation of each technological revolution. Affecting primarily the companies engaged in those technologies. This bubble like behavior
of technological revolutions ultimately results in low
returns for investors. These bubbles are an empirical fact in the historical data
that cannot be ignored when we're talking about in
technological revolutions. The surge of development
in canal mania was followed by a canal bust. Railway mania was followed
by a railway bust. The infrastructure boom of
the late 1880s was followed by several busts. The roaring 20s ended
in the great depression and the surge of IPO's in the internet bubble
ended in the tech crash. The lesser known British bicycle mania followed a similar path. The concept of a bubble
used by Perez is convenient and easy to think about. Investors get into an irrational
frenzy about the potential for high profits from the new technology, irrational exuberance as
Robert Shiller describes it. This results in prices that
exceed any notion of fair value. While there is likely a contribution from irrationality to
these bubble like patterns, I don't think that it would
be intellectually honest to assume that investors have
been consistently irrational through all past
technological revolutions. I'm not saying that investors
are perfectly rational, but perfect irrationality is
arguably a bigger assumption. In the 2004 paper, "Was There A NASDAQ
Bubble In The Late 1990s," Lubos Pastor and Pietro
Veronesi show mathematically that higher uncertainty about
the average profitability of the companies creating new technologies leads to higher prices or else equal. When an exciting new technology
company is being tested there is a huge range
of potential outcomes. Maybe it's the next
Microsoft, but maybe not. The concept that uncertainty
about average profitability leads to higher prices,
is counter-intuitive, but it's important. We're going to do some
math pay close attention. using the Gordon growth
model for stock valuation where stock price is equal
to expected dividends, divided by the discount rate
minus the dividend growth rate the price has a convex response to changes in the dividend growth rate. This means that as the
dividend growth rate increases or decreases, changes in
the price are not linear they are convex. There's a special case in mathematics for convex functions
called Jensen's inequality. For the Gordon growth model it implies that when dividend growth
rates are modeled as uncertain, the expected growth rate required to explain a given price drops. The larger, the uncertainty
about the dividend growth rate, the larger the drop in the
expected growth rate required to justify a given price. Assume a discount rate of 11% and an expected dividend of a $1. If we take a stock trading at $56 the implied no one dividend
growth rate is 9.2%. If on the other hand we allow for two possible dividend
growth rates, 2% or 10% with equal probabilities,
the expected growth rate, the average of the two equally
likely possible growth rates needed to justify the
$56 price is only 6%. This inequality tells us that for an expected dividend growth rate increasing uncertainty increases the price without requiring the assumption
of irrational behavior. Uncertainty increases the
fundamental value of a company. As the market learns about the
profitability of businesses in a new technological paradigm, the uncertainty about
their growth rate decreases causing their prices
to fall or else equal, Pastor and Veronesi argued
that in the late 1990s there was high uncertainty
about the average profitability of technology firms. And that this uncertainty helps explain the high level of technology
stock prices at the time. They find that the level
of uncertainty implied by their model to justify the high prices in the dot com bubble, matches up well with the realized volatility
of technology stocks over that time period. They conclude that the high
prices of the internet boom were not necessarily detached
from fundamental values when the high levels of
uncertainty are accounted for. In another Pastor and Veronesi paper, "Technological Revolutions,
And Stock Prices," the authors build a model where
there exists a new economy and an old economy. The new economy is small and experimental until it becomes no one that it could meaningfully
increase productivity in the old economy. Before the technology in the new economy is adopted by the old economy, the risk of the new
economy is idiosyncratic. It is specific to the small new economy. If the new economy starts
to become profitable there is a point where
the combination of profits and a relatively low discount
rate results in high prices. As the chances of the
new economy being adopted by the old economy increase, the rise in systematic
risk in both the old and new economies result
in decreasing stock prices and increasing volatilities. The risk in the new
economy is becoming tied to the systematic risk of the old economy. Well risk in the old
economy is also increasing based on the potentially risky undertaking of adopting the new technology. When this happens, the new
economy stock prices drop more and are more volatile than the old economy due to an increase in the
new economies market beta. They test the predictions of their model against the dot com bubble
and the railroad bubble. The dot com bubble
pattern was much stronger in the NASDAQ index, their
proxy for the new economy than in the old economy. Proxy by the NYSE AMEX. NASDAQ's beta doubled
between 1997 and 2002. The volatility of the old
and new economies increased but the new economies
volatility always exceeded the old economies. NASDAQ's beta and both
volatilities peaked in 2002 followed by an acceleration
in productivity growth in the U S economy. In the 1830s and forties there was substantial uncertainty about whether railroad technology would be adopted on large scale. Pastor and Veronisi found
that all stocks fell before and during the year 1857 with a railroad stocks falling more than non railroad stocks. The railroad stock volatility
and relative prices consistently exceeded their
non railroad counterparts. The volatility of all stocks Rose in 1857. The railroad stock beta
increased sharply in the 1850s before falling right after 1857. Which was soon after railroads began their
large scale adoption. It is important to note that the bubble like pattern
in stock prices arises at least it's in part
due to a selection bias. We are more likely to study
technological revolutions. Once we know that they've taken place. The investors living through
them on the other hand are not aware of whether
the new technologies are going to be adopted
into the old economy or continue as small and experimental. One of the practical
implications of this insight in the context of the model is that when the stock prices associated
with a new technology rise as their profitability
potential becomes known, betting that they will be
adopted on a broad scale is similarly a bet that
their prices will decline. Taken together when a technology begins to
revolutionize the old economy the market learns about its profitability reducing uncertainty and stock prices due to the convexity on growth
rates in valuation theory. And risk in the new economy transitions from
idiosyncratic to systematic further reducing prices due to
an increasing discount rate. Whatever the theoretical explanation technological revolutions and
bubble like characteristics are difficult to separate
in the historical data. We always have to remember
what a stock represents. A stock is a claim on a
company's future profits. Investment returns do not
come from a company's growth. They come from the relationship between a company's future profits, and how much are you the investor
or paid for those profits? Paying a higher price should lead to lower realized returns or else equal. This is exactly what the
historical record shows. In the fifth edition of
Jeremy Siegel's book, "Stocks For The Long Run," Siegel offers the example
of the S and P 500 index. Since inception of the index its industry composition
has changed materially. In the 1950s steel chemical auto and oil companies dominated the index. Whereas today healthcare
and technology dominate. Despite the decline of the
originally dominant industries had an investor bought and
held the original firms in the S and P 500 at its inception, they would have beaten the actual index by more than 1% per year
for the next 50 years. Siegel argues that this is
due to investors overpaying for expected growth. From 1900 through 2019, rail
companies declined from a 63% share of the US stock market to a less than 1% share. It is the ultimate example
of a declining industry. Over that time period, rail stocks beat the U S market, road transportation stocks,
and air transportation stocks. Since the approximate start
of the age of information in 1971, the software industry has grown more than any other firm,
basically non-existent in 1971 to the largest by market
capitalization at the end of 2019 at nearly 15% of the US stock market. The oil industry on the other hand has seen a massive decline
in market capitalization from nearly 15% of the U S market in 1971 to about 3% at the end of 2019. Over this period a dollar invested in the
oil index grew to $134. Well, a dollar invested in the software index grew to only 76. Another common assumption is the betting on the winning companies. The companies that end up dominating a technological paradigm
make good investments. This is simply not been
the case historically. Every technological paradigm has had winner take all companies. These huge companies
make up a large portion of the stock market and drive the economy. Their stock returns though
have left much to be desired. For each decade, starting 1930, 40 50 and so on through 2010,
the 10 largest companies at the start of the decade
have trailed the market as a whole, by an annualized 1.51% on average for the decade that followed. Bets on new industries
or against declining ones have historically failed to pay off. What about the next
technological revolution? Does it make sense to look
for the next Apple, Amazon or Google before their prices rise? This notion is more akin
to playing the lottery than many people realize. Evidence from IPOs and
venture capital tells us why. Stock returns in general
exhibit positive skewness. Most stocks performed poorly and a relatively small number of stocks perform exceptionally well. The positive skewness in IPOs which tend to behave like
small cap growth stocks and venture capital is
even more pronounced. The vast majority of small cap growth stocks
produce poor returns while a few produced
large positive returns. Almost two thirds of venture
capital financings lose money while a tiny number of
them produce huge returns. The chances of picking
winners before the fact are not in your favor. Investing in technological revolutions is one of the least successful
strategies in investing. Whether we interpret the empirical reality with the lens of frenzied,
irrational investors paying too much for expected growth or rational investors assessing a highly
uncertain future payoffs. The historical record remains the same. Counter-intuitively investing
in declining industries or more generally
companies with low prices has produced reliably better outcomes. But every time that a new technology or industry creates a new opportunities for financial capital
investors have flocked to it with seeming disregard
for the historical record and the theory predicting
similar outcomes in the future. Thanks for watching. My name is Ben Felix, and this
is common sense investing. If you enjoyed this video,
please share it with someone who you think could
benefit from the information. And don't forget if you've run out of common sense investing videos to watch you can tune in to weekly episodes of the rational reminder podcast wherever you get your podcasts. (upbeat music)
Tænkte at jeg ville dele denne meget relevante video fra Ben Felix, hvor han på fornem vis opridser, hvorfor det ikke nødvendigvis er en god idé at overvægte sine investeringer mod de hotte nye teknologiske trends.
Virkelig interessant perspektiv!
Han er desuden også stor fortaler i Small Cap investering. Nogle af jer der har fyldt det råd? Jeg er pt 100% i large cap, men jeg overvejer at ændre