The third phase of value investing is formed and diffused based on network economics, and the most significant characteristic of this phase is that investments have the value of "value creation." In this business model, the cost of tangible asset investment has been significantly reduced, while the value output has increased exponentially. Companies that create hundreds of millions of dollars in profit often have a market value of several billion dollars, and the capital required to drive these is only a fraction of what was needed in the era of the industrial revolution.
In Robert G. Hagstrom's "The Warren Buffett Way," Chapter 3, the section on "The Value of Network Economics" is crucial. It is because the third phase of value investing is formed and diffused based on network economics, and the most significant characteristic of this phase is that investments have the value of "value creation."
Thinking about growth from a macroeconomic perspective, network economics is an economic theory model that uses network theory to discuss economics. The theory emphasizes that in an economic network, the connections among various nodes are not equal but uneven. Moreover, newly added nodes tend to seek out nodes with many connections within the existing network. That is to say, in an economic network, every newly added node will instinctively seek out nodes that already have many connections within the network to connect with. This further strengthens the connection advantage of nodes that have many connections, which is the "winner takes all" phenomenon in economics.
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The network economy is achieved through new technologies, including more powerful personal computers and smartphones connected by the global internet. In this business model, the cost of tangible asset investment has been significantly reduced, while the value output has increased exponentially. Companies that create hundreds of millions of dollars in profit often have a market value of several billion dollars, and the capital required to drive these is only a fraction of what was needed in the era of the industrial revolution. This continuous innovation process is referred to by Joseph Schumpeter as the evolutionary process of "creative destruction." Schumpeter believed that economic growth occurs in a series of long cycles, and the speed of each cycle accelerates over time, which he called waves.
Everett M. Rogers first proposed the S-curve theory of the development of new things. In his "Diffusion of Innovations," he attempted to integrate Schumpeter's rolling wave theory into a unique fluctuation theory to explain how, why, and at what speed technological ideas spread. The diffusion of innovation always starts slowly, and when the adopters reach a "critical mass," the diffusion process suddenly accelerates. The S-curve model explains the spread of new technologies or innovations in the market, from the initial slow adoption to the later rapid growth, and finally to stability. Different products or technologies may stay in these stages for different lengths of time, depending on various factors, including market demand, characteristics of adopters, and marketing strategies.
Evolutionary economist Carlota Perez introduced Thomas Kuhn's concept of "paradigm" to explore the interactivity between technological revolutions and financial markets, creating a four-stage model of technological revolutions/financial markets, and summarizing the regularity of the mutual influence between technological revolutions and financial markets. The so-called technological revolution is defined as a group of technologies, products, and sectors that have a strong influence, are obviously new and dynamic, and can bring about significant changes in the entire economy, and can drive a long-term development climax. However, only when each of these technological breakthroughs far exceeds the boundaries of the industries and sectors it causes, and spreads to a wide range of fields, does it belong to the true meaning of a technological revolution.
Perez believes that we are in the fifth technological revolution, which she calls the information and telecommunications era. It began in Santa Clara, California, in 1971, when Intel launched the microprocessor. The new technologies of the fifth technological revolution include microelectronics, computers, software, smartphones, and control systems. The new infrastructure includes global digital, telecommunications, cable, fiber optic, radio frequency, and satellites that provide the internet, email, and other electronic services.
The principles of the fifth technological revolution include information aggregation, decentralization, and globalization. Information aggregation means that knowledge, like capital, can appreciate in value. When the network structure is decentralized, the market will become fragmented, creating a large number of powerful niche markets. Global connectivity makes instant global interaction between local operators possible, thus achieving a wide range and scaled economy, creating an unprecedented overall locatable economic market in history. Perez goes further than Schumpeter and Rogers. She points out that the trajectory of technological revolutions is not as smooth as the programmed curves reflected in textbooks. As for the reason, she believes that it is because financial markets participate in the financing of technological revolutions.A Handful of Internet Winners
Scholars such as Joseph Schumpeter, Everett Rogers, and Carlota Perez have provided investors with a profound way of thinking from their respective research, which is to consider growth from a macroeconomic perspective. However, what is missing is how to determine which companies have which competitive advantages in this technological revolution. One of the founders of complex economics, Brian Arthur, has provided the answer.
Brian Arthur is an economist we have been paying attention to in recent years. Arthur believes that economics is undergoing significant changes. Over the past thirty years, economists have thought that their standard approach, neoclassical economics, has become seriously detached from reality. Neoclassical economics assumes that people are super-rational and make decisions in a static, equilibrium world. However, economics has diversified, and many economists are looking for more realistic assumptions. As a result, we have seen the emergence of behavioral economics, increasing returns economics, and evolutionary game theory. Complex economics is also the case.
Complex economics is a completely different way of looking at the economy. Complexity is actually a movement that has swept across all disciplines, not just a research topic. Complex systems refer to the multiple elements that make up a system, adapting or responding to the patterns they themselves create. The elements in a complex system can refer to cells in a cellular automaton or cars in a traffic system, with the former responding to the state of adjacent units and the latter responding to the cars in front or behind it. Of course, the "elements" and the "patterns" they respond to vary in different contexts. But in any case, the elements must adapt to the world they collectively create, that is, the overall pattern. Here, time naturally enters the system through adjustments and changes; as the elements respond, the total amount changes; and as the total amount changes, the various elements respond again.
Complex systems naturally emerge in the economy. Economic actors, whether banks, consumers, businesses, or investors, constantly adjust their market actions, purchasing decisions, prices, and make predictions to adapt to the market situation collectively created by all these market actions (or decisions, or prices, or predictions). Therefore, complex economics is a very natural way to look at the economy, and in a sense, it has existed for 200 years. In fact, complex economics is an economics of emerging things, focusing on pattern formation, structural change, innovation, and the consequences of perpetual creative destruction.
Regarding the "killer applications" of complex economics, Brian Arthur can think of two. One of them is the increasing returns economics he developed in the 1980s. It explains how network effects lead to "lock-in," or the market being dominated by one or a few participants. This work cannot be done through equilibrium economics because it is not an equilibrium phenomenon itself. Now, Silicon Valley has fully accepted this theory and operates according to it.
"Complex economics" is a term coined by Brian Arthur in an article he wrote for Science magazine in 1999. In economic theories based on physics as a standard, the market shows a state of diminishing returns. The law of diminishing returns is a fundamental principle of standard economics, which includes that, with other factors remaining constant, adding one more factor, that is, a requirement, will reduce the incremental return of unit production at some point. In other words, the law of diminishing returns means that after reaching a certain point, the level of economic returns obtained relative to the invested capital will decrease.
However, complex economics believes that some companies are destined not to be affected by the long-term law of diminishing returns. According to Arthur's view, the economic returns of some companies will continue to grow. He explained: "Accelerating returns refer to those who are leading will further lead, and those who lose their advantage will further fall behind." Diminishing returns are a characteristic of the old physical economy, while "accelerating returns are becoming a characteristic of the new economy, that is, the knowledge-based industry." Accelerating returns are particularly significant in specific technical fields where network effects are common. Network effects refer to the phenomenon where the value increases as more and more people use a product or service. In the new knowledge-based economy, digital networks are a symbol of value creation. There will definitely be competition between networks, but in the end, after the shuffle, there will be only a handful of network winners.
"Franchise Rights" Redux
Bill Miller has beaten the S&P 500 index for fifteen consecutive years. From 1991 to 2005, the Legg Mason Value Trust fund he managed achieved a total return of 980%, with an average annual compound return rate of 16.40%, and the management scale grew from $750 million to $20 billion. During the global financial crisis of 2008-2009, Miller made a contrarian bet on financial and real estate companies, resulting in a halving of the fund's net value and causing significant losses. He achieved great success in new economy investments but failed in old economy investments, which makes us sigh with emotion.Bill Miller joined Legg Mason in 1981 as an assistant to Ernie Kiehne, co-founder of the Value Trust fund. In 1990, he succeeded Kiehne to manage the Legg Mason Value Trust, beginning his legendary and tumultuous investment career. Miller holds a Bachelor's degree in History and Economics and pursued a Ph.D. in Philosophy. His professional strengths led him to embrace pragmatic philosophy and a latticework of mental models. He was closely associated with Arthur. Haggerstrom extensively describes Bill Miller because he sees him as a representative figure of the third stage of value investing.
In 1992, Bill Miller first visited the Santa Fe Institute. He frequently attended the institute to learn, which infused him with fresh vitality. He knew the market was in the midst of a new technological revolution, and he was aware that he had a roadmap to determine the competitive advantages of technology companies. At the same time, societal views on technology companies and investment literature were emerging, and one could even say that a library of such research was taking shape. These studies included Geoffrey Moore's "Crossing the Chasm," Brian Arthur's "Complex Economics," Clayton Christensen's "The Innovator's Dilemma," and Carl Shapiro and Hal Varian's "Information Rules."
That year, Brian Arthur explained to Bill Miller his views on increasing returns in economics, further pointing out which attributes companies experiencing increasing returns possess and how to further solidify their dominant position in a particular industry. They discussed network effects, with Arthur noting that people prefer to connect to a larger network rather than being confined to a smaller one. If there are two competing networks, one with 25 million members and the other with 5 million, a new member would tend to choose the larger network because it is more likely to meet his needs for connecting with other members, offering more services and benefits. Network effects are demand-side economies of scale, so being able to grow quickly is very important to have network effects, as only by rapidly expanding can one effectively counter competitors' expansion.
Bill Miller and Brian Arthur also discussed the concept of "positive feedback," a component of human behavior proposed by behavioral psychologist B.F. Skinner. Positive experiences give us pleasure or satisfaction, and those who have experienced them want to relive them. When using technological products or any other products, people with positive feedback experiences tend to return to those products. In business operations, the effect of positive feedback is that the strong get stronger, and the weak get weaker.
In human psychology, another habit related to technology investment is called the anchoring effect. Technological products, especially software, may be difficult to grasp at first, but once we become proficient in using a particular product and software, we strongly resist changing to use another product or software. Therefore, we become dependent on the path and prefer to repeatedly use the same technological functions. Once consumers are satisfied with the way they use technology, even if a competitor's product is considered superior, they find it difficult to switch. All these factors—network effects, positive feedback, anchoring effects, and path dependence—lead to high switching costs.
Buffett tells us that the best businesses with excellent long-term prospects have a trait called "franchise value." Companies with franchise value sell products or services that people need or desire, with no substitutes. Buffett believes that the next wave of great wealth will be gained by those who can identify new franchises. After visiting the Santa Fe Institute, Miller strongly believed that new technology companies were equivalent to the franchises mentioned by Buffett.
Finding Value in Value Creation
Bill Miller's definition of value also comes from the concept in John Burr Williams's financial textbook "The Theory of Investment Value," which was later reinforced by Buffett. The concept is that the value of any investment is the present value of the future free cash flows it brings. Soon, Miller pointed out that no one in the textbook said that value is defined by a low price-to-earnings ratio. Both Buffett and Miller observed from their studies of businesses that high incremental investment returns greatly increase the value of future cash flows.
The difference between Bill Miller and other value investors is not that his definition of value is different, but that he is willing to look for value everywhere. Most importantly, he did not exclude the possibility that technology companies contain value. He believes that technology can be analyzed based on business fundamentals, and intrinsic value can be estimated. Using the value method in the technology sector is a competitive advantage because investors in this field focus entirely or mainly on growth, which is often overlooked by value investors. Following the roadmap provided by Brian Arthur, Miller saw the inherent network effects within America Online (AOL), which had great power. Miller bought AOL at an average price of $15 per share, believing that the company's value was about $30 per share. Subsequently, he made a 50-fold profit on AOL, and the position in the stock quickly accounted for 19% of the entire investment portfolio.
Bill Miller is widely regarded as one of the first investors to successfully solve the valuation puzzle of technology companies. He has never deviated from the basic principles of value investing; he uses the discounted cash flow model to calculate the value of businesses and only acts when there is a margin of safety. "Compared to fund managers with an annual turnover rate of over 100%, our 11% turnover rate is abnormal," Miller said. "Finding good businesses at a cheap price and holding them for many years has been a wise investment in the past. When people use simple accounting-based indicators, linearly arrange them, and then use them to make buy and sell decisions, we are happy."Buffett's investment in Apple can be considered a perfect case of value investing that spans the second and third stages. Apple is not only a global consumer goods company with strong brand value but also a stock of the new economy type. All of Apple's products and services use Apple's iOS operating system, and once the product becomes part of the Apple ecosystem, network effects will form positive feedback, path dependence, and anchoring effects, etc., creating a strong global franchise. Today, Buffett calls Apple one of Berkshire's three greats, alongside its Geico Insurance and Burlington Northern Santa Fe Railway Highway Company.
Philip Fisher once said that few investors can evolve from the first method to the second method, let alone the third method. To succeed in a market cycle, a flexible mind, the right investment temperament, and a strong desire for continuous learning are needed. Even Bill Miller often switched between the first method and the third method. In the end, it was the first method that led to his failure, that is, classical value investing, not the third method, that is, value creation investment under the new economy.
Hagstrom pointed out that for a long time, investors have been wrongly and narrowly defining value investing. Warren Buffett, Charlie Munger, Bill Miller, Bruce Greenwald (author of "Value Investing", etc.), Paul Johnson (co-author with Paul Sogin of "Securities Analyst Advanced Guide"), and Michael Mauboussin (author of "Expected Investing", etc.), and many others, have been working hard to broaden the perspective of finding value. Through unremitting efforts, they have provided investors with a thoughtful investment perspective.
In summary, value will not hibernate forever, but it may lie dormant for a long time. Value will migrate, sometimes, value will exist in those enterprises with high capital returns and rapid growth; sometimes, value will exist in those companies with slow growth and high capital intensity. Usually, value can be found in both the value and growth camps. One of the biggest returns of studying Buffett is to observe how he has developed as an investor over the past 65 years. Buffett's excellence lies in spanning the three stages of value investing, from the first stage of classical value to the second stage of value growth, and then to the third stage of value creation.
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