That Doesn't Work Anymore

Retooling Investment Economics in the Age of Disruption

Robert S. Kricheff

• Éditeur: De Gruyter
• Année: 2018
• ISBN:
  9781547400775
• Édition: 1
• Sujet: Volkswirtschaftslehre
• Sous-sujet: Ökonometrie

Economic measures and concepts like GDP, inflation, business cycles and supply chains that were created decades ago are being disrupted and altered by technology. These changes affect asset values, interest rates, stock valuations, barriers to entry, as well as regression and correlation analysis. That Doesn't Work Anymore discusses how to adapt traditional data to these changes and outlines ways to use newer and better tools that help you make good investment and business decisions.

The book's short pragmatic chapters grouped by topic with research and real-life anecdotes delve into how technological and societal developments have changed the meaning and value of traditional economic data-points, predictive tools, and business concepts. Robert S. Kricheff provides specifics on new and more valuable data sources as well as better methods for applying the information to investing, business, and even your career.

Part 1:Introduction

Chapter 1
The Economy Is Running the Data Is Walking and Trends versus Cycles

Sending a document cross-town, trading millions of shares of stock, ordering groceries, and manufacturing a car all happen much faster than they have at any time in the past. The acceleration in the speed at which you can get things done in this era of digitally driven innovation is not like anything seen before. New technology is also getting adopted much more quickly than at any time in the past. If everything is moving with such greater speed, economic theories and measurements need to keep pace. Should traditional business and credit cycles move faster than in the past? Why should investors react to data such as gross domestic product (GDP), which was developed in the 1930s and contains data that is sometimes six months old if the economy has evolved while waiting for the results? If you are an investor, of any kind, you need to rethink how to use popular economic data and traditional economic theories, consider other newer data points to use and reevaluate the relevance of all this data that is available in the current environment.

This era of technical and societal revolution is impacting how investment decisions need to be approached. First, these developments are so extreme and rapid that historical economic data is not as good a tool as it once was when trying to predict future asset values. Secondly, that the multitude of technologically driven improvements in efficiency should lead to an extended period of macroeconomic expansion with recessionary dips potentially being very minor and fleeting when compared to the past. However, these same developments are likely to cause select industries and regions of the economy to go through much greater distortions leading to dramatic differences between winners and losers at the micro level. The value of historical data has declined. Investing is about deciding on where you believe the future value of an asset will be. This decision is usually made using historical data as a significant input. However, since technology and related sociological changes are making historical information less relevant in predicting the future, investors must adapt. With so many aspects of economics and business being different now, historical interactions between data and asset valuations often do not work the same anymore.

What once may have been a very valuable data point to use in analyzing asset values may not work so well today. One of the common reasons this occurs is that the components in the data set may have changed. For example, you can discuss how high the current average price/earnings ratio for stocks in an index are compared to historical averages. However, today the largest stocks in the index are likely to be very different companies in very different types of businesses than they were ten years ago. How valuable is it to compare the historical average ratios versus the current ones if the underlying companies are so different? The second common reason a data point may become less valuable for your investment decision process is that interactions have changed. The music industry is a good example; in the late 1980s through the 1990s you could track a relationship between the sale of music CDs and the revenue for companies that produced and sold recorded music. By the mid-2000s services like Apple’s iTunes had disrupted this correlation and using the number of digital music downloads was a more important data point relative to industry revenue. More recently streaming services have changed the paradigm for downloaded music sales. Tracking sales of CDs or even downloaded music is not as useful in understanding the business today. Relationships between different data points are not constant; the introduction of new technologies is causing relationships to change more frequently. You can not ignore the old data. It still has value and markets still react to it, but you must adjust to how you use it and find other tools to use as well.

It is not just technology but also social change that is transforming investment economics. Some of this social change is due to the data driven era. People are communicating differently and using different types of entertainment. Demographics are also driving social change. There is a large population bubble in the United States and some other developed countries, referred to as millennials. This demographic will be transforming the economy and public policy over time. Many millennials were just getting ready to enter the work force when the great recession hit, and that experience may influence how they invest. Many of them are drawn to different employment structures and have consumption patterns that vary from prior generations. All of this will shift the value of old data and theories and will influence asset valuations in the economy.

The economy is made of people and their individual choices, technology, education and societal developments change how those choices are made over time. However, there is always an effort by investment decision makers to quantify and formulize the aggregate data of these individual choices as if they are mathematical constants. The use of averages, regression, and correlation seem to be the most popular ways to formulize data. Most often this is done with time series which are driven by old data that comes from time periods that may not be applicable to the current situation. The overuse of these techniques without the application of logic can be significantly misleading.

With economic change happening at a much faster pace using more market-based data can often help to give a better picture of the current environment, market prices change much more often and have greater fluctuations than economic data. Market data sends critical signals as to how demand and valuations may be moving. When there is so much change afoot utilizing market data, and more heavily weighting more recent information, can help give a much better sense of the current and future outlook for valuations than over emphasizing out of date historical analysis.

It is easy to get lost in all the data. Just because some data is widely used doesn’t mean it is a good signal. It might just be noise. It is good to have confidence about what is and is not a good signal. However, even if you think a data point is just noise and has no bearing on your investments, if people are talking about it, it matters and can move market prices. If markets are reacting to some data that you believe is now useless in the modern economy, it may create an opportunity to either buy or sell. The media and markets often react to new data at least temporarily, but also often have the attention span of a cat in a yarn factory and quickly move on to the next data point.

While one theme is clearly that technological advancements are changing the value of using historical economic and market data to make decisions, a second theme is that these developments are also altering how long-term economic trends and cycles are acting. People are constantly trying to apply the laws of natural science to economics—it often does not work. In the natural sciences there are highly predictable cycles; like how sound waves move and the timing of the sun rising and setting A cycle is supposed to be a series of events that gets repeated in the same order. People try to apply cycles to economics all the time. However, this does not always work; because the patterns and the context in the economy are not always the same as in the past, there is always a significant difference. For example, in the United States some recessions have lasted six months and some eighteen months, these are meaningful differences and not that predictable. It is not that boom and bust cycles do not sometimes occur in economics, but each one has its own nuances and differences and too often people try to squeeze and manhandle data to fit into a specific definition of a cycle that they have seen before and not factor in what might be different now. With everything from data to capital moving so much faster, cycles may start to look very different than in the past.

While cycles are usually thought of as somewhat circular, trends tend to be linear. A trend occurs when something is developing in a specific direction. Major economic driven investment themes are usually best to think of as trends. This is when, over a reasonably long period of time, selected data moves in the same general direction and impacts asset valuations. Over time some factors driving the trend are likely to change, and eventually trends end, but they often last longer than some people realize, and the current technology driven trend looks like it has some significant way to go. During any long-term trend there are likely to be some bumps and dips in the trend line. These shifts could be viewed by some people as cycles, but if you are a long-term investor do not lose sight of the trend when these bumps occur, they can create opportunity. The increasing velocity of economic change and financial flexibility should make these dips in the economy last for much shorter time periods than in the past and the declines in economic activity may be less extreme. If these economic dips are shallower and of shorter duration, they will matter less.

Long-term trends account for the bulk of the time periods in which you will be investing, as opposed to periods of big bubbles and bursts that diverge from trend. Bubbles and bursts do not occur that often, and it is better to prudently invest along trends you believe in than constantly be trying to call the next great crisis or rebound while missing a current trend. To get a sense of some trends over time we can look at the economy of the United States. In the United States there have been eleven post-war recessions through 20171 with 130 months of contraction and 722 of expansion. The odds have been with you if you focused on the expansionary trends for 722 months rather than trying to call the eleven recessions. Trends and cycles can be tricky things to define and predict in real life. Figure 1.1 shows interest rates since 1981 in the United States using the five-year Treasury bond as a benchmark. This chart shows a major trend of declining interest rates. You can also see that there are certainly some periods where money could be made by going against the trend and positioning for rising rates, and some of these could be called cycles, but the long-term trend is pretty clear and if your investment thesis was for declining rates and you stuck with it long term you would have done very well. Lots of money can be made in booms and busts, and the potential for these to occur should not be ignored, but the bulk of time economies are following a much less cyclical pattern and following a more linear trend.

Source: Board of Governors of the Federal Reserve System (US), 5-Year Treasury Constant Maturity Rate [WGS5YR], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/WGS5YR, September 2018.
Figure 1.1: Yield on the Five-Year U.S. Treasury Note—Constant Maturity

Macroeconomic and Microeconomic Trends

Various parts of the economy can have their own trends and cycles that differ from aggregate economic data. Economics is typically divided into macroeconomics and microeconomics, even though the two are incredibly intertwined. Macro examines the broad economy, micro focuses on decisions by individual agents in the economy such as people and businesses. In investment economics, perhaps there should be a separate level of economic analysis, medi-economics (medi being Latin for middle). This field would include the studies of how macro and micro decisions influence subsectors of the economy such as an industry or a region. This medi arena currently seems to fall into discussions on both macro and microeconomics, but it really has its own unique dynamics. While the broad economy can be going in one direction at the medi levels there can be very different trends and this divergence is likely to be more common during this current era. Technology is transforming different industries and regions in varied ways, so sector and regional analysis is critical. Decisions at the medi-economics level are what drive key rotations in investments and decisions on how to weight different factors in a portfolio, such as the decision within an investment portfolio to overweight stocks of software companies while reducing exposure to the stocks of microchip manufacturers. With industry disruption so prevalent understanding the changes happening at the medi-level and making the right choices can be as valuable as the decision at the macro and micro level.

The changes wrought by this digital era should change how you think about investing at all levels of the economy. Technology innovation is leading to greater flexibility in corporate structures and capital movements as well as greater operational efficiencies. This should keep the overall long-term macroeconomic trends in most developed economies on a positive trend for a significant period of time. Historically, we may look back and see that we are currently in the very early stages of this technologically driven era of growth. The biggest risk to this trend would appear to be poor decisions by government entities that could stifle or distort the potential benefits accruing to the economy from innovation.

Technology is having a very different transformative effect at the medi and microlevels. It is changing the equation for many aspects of business, such as, barriers to entry, the ability to attract capital and corporate structures. This is going to continue causing significant disruption and swings in asset valuations at the regional, industry and corporate levels of the economy. People will need to reevaluate historical data and relationships at the medi and micro levels. While the general economy should perform well, at these other levels we are likely to see a meaningful number of recessions that stay contained in an industry or regional pocket. These pocket recessions are often likely to get nasty and cause significant divergence in asset valuations, but, the impact should generally stay within the pockets and not lead to larger more troublesome economic malfunctions. This will mean that sector rotations and individual investment decisions matter more in this era.

Using Data Wisely

Understanding the data you are using to make decisions and how it fits into the current world should lead to better investment results. It does not mean things need to be complex; as a matter of fact, simpler is often better. In the era of big data with the capacity to run enormous rapid calculations it is easy to be persuaded to use more data when a smaller series of data might work fine. With the value of data changing rapidly you need to constantly monitor the relevance and the interactions of each data point you are using. More data does not always create a more robust answer and using too many different data series can create problems as it increases the probability of dirtying up your conclusions with information that has become irrelevant as the economy has moved on. A quote sometimes attributed to Albert Einstein sums it up as, “Keep everything as simple as possible, but not one bit simpler.”2

There are some major biases to guard against when using any data, and particularly when more market based data is used. These include anchoring, confirmation and recency biases. Anchoring occurs when you base too much of a decision on one initial or older piece of data and disregard other signals in favor of your initial data point. Confirmation bias happens when you are too wed to your current position and any new data is manipulated to rationalize your current investment holdings. Both are dangerous in an environment of constant innovation. Recency bias also needs to be guarded against. This can happen as you try to be more reactive to market data and place too much emphasis on the most recent data point, often assuming that this one data point is a predictor of a massive new trend, when it could just be an anomaly. Rapid innovation may be the only constant in the current economy, in such an environment it is vital to look at all data, and the conclusions derived from it, with a very cynical eye. Questioning the consensus views and the data used to reach those views is a good thing, it does not always mean consensus is wrong, but be sure to poke it. Just because certain data points usually interact a certain way does not mean that they always have to act that way. This book is not supposed to provide all the answers, but should expand the angles from which you examine data used to make investment decisions. A good quote to keep in mind as you examine any data in this period of evolution is attributed to the nineteenth century writer Oscar Wilde, “To believe is very dull. To doubt is intensely engrossing.”3

Chapter 2
An Approach to Economics—Bottoms Up

Economics is sometimes described as a social science that focuses on decisions about the allocation of limited resources. This definition is broad and acknowledges that economics may not always only involve commercial decisions. It could study the decision process of someone with a limited amount of time that has to allocate between going to a party or to the gym. This book takes the approach that finance and the study of investments are subsets of economics. Finance focuses on investments, assets, liabilities, uncertai...

Table des matières

• Cover
• Title Page
• Copyright
• Dedication
• About De|G PRESS
• Acknowledgments
• Contents
• Preface
• Part 1: Introduction
• Part 2: Disruption, Culture, and Indexes
• Part 3: Math Moves–Remembering That Everything Changes
• Part 4: Big Economic Data Points
• Part 5: Old Capital, New Capital
• Part 6: Tonight the Role of Government Will Be Played By…
• Part 7: Business is Different Now, But It Always Is
• Part 8: Value, Volatility, Uncertainty–Different Arrangement but the Song Remains the Same
• Part 9: Random Ramble and Concluding Topics
• Index