Artificial intelligence, while generating powerful tools for analysis, is only the beginning of a more ambitious phase making AI systems more accurate, less biased, and effective prediction tools. Gathering more and more raw data does not create value. One cannot simply push a button and have valuable output generated. Data needs to be collected, processed, stored, managed, analyzed, and visualized – only then can we begin to interpret the results. Each step is challenging, and every step in this cycle requires massive amounts of work and value-added tools. It’s not just the software and hardware artifacts we produce that will be physically present everywhere and touch our lives all the time, it will be the computational concepts we use to approach and solve problems, manage our daily lives, and communicate and interact with other people. It will be a reality when it is so integral to our lives it disappears. The problems and solutions we address are limited only by our own curiosity and creativity.
What did we learn this year? Well, not too much. Observing is not learning. Acting is. But we’re not going to do that. A call for action is sufficient, as long as someone else does it. That much we’ve learned. Pandemic Time What used to take several years now takes a fraction of that –…
Digital assets are disrupting finance – the world’s largest industry. All assets, intellectual property, and even currency can now be digitized, and anyone can access anything from anywhere. The finance industry is being this intermediated and globalized, economic development and policy will be forever changed.
Transformation, Valuation, Employment, and Deflation
Disruption to some of the world’s most important industries, deflationary pressure caused by scaling lower-cost businesses, and sustained low interest rates challenge traditional valuation models. Technological platforms, from blockchain-based businesses to energy storage to DNA sequencing, enable unprecedented disruption to business and economic models.
Interest rates will remain low, equity values will remain high, innovation will drive deflationary pressure, and volatility will be intense and frequent. A new approach is required to understand dynamic global competition and sustainable value.
A National Investment Authority, an idea gaining traction among the administration, would be responsible for “devising, financing, and executing a long-term national strategy of economic development and reconstruction.”
This is not the job of a government; this is the role of the free market. The market does this quite well, and government does this quite poorly. An NIA is another way to bring misery and inefficiency.
Policy reflective of central planning, socialism, or industrial policy brings misery to all. This discredited philosophy that tortured so many in Eastern Europe and Soviet Russia seems to be getting more traction today bewilderingly. It leads to nothing more than bureaucratic idiocy, waste, and disregard for any consumer needs.
Investors expected that the Fed would not only end its bond buying program, but many believed it would also raise interest rates. While the Fed did agree to taper its bond buying, essentially decreasing its $150 billion monthly bond buying program by $15 billion per month, ending the program in 2022. However, the Fed kept interest rates the same and clearly signaled that it would not raise interest rates anytime soon, and almost definitely not until the taper of its bond buying was completed – in other words, not for at least one more year.
Investors who had been betting on the Fed raising interest rates wagered on the yield curve flattening for Treasuries. Therefore, they invested in short-term Treasuries believing those would outperform longer-term Treasuries, as well as 10-year and 30-year bonds. Instead, we are seeing the opposite happen. Short-term bonds are dropping in price and yields are approaching their highest levels since March 2020. Meanwhile, prices for long-term bonds have climbed. This same phenomenon is happening for government bonds that only in the United States, but also in the UK, Canada, and elsewhere.
Decentralized finance (DeFi) can disrupt global finance – but only if Defi systems and central governments cooperate. Yes, sworn enemies cooperating for the greater good.
While each seems to be the sworn enemy of the other, ultimately, a cooperative relationship between decentralized and efficient (versus anachronistic and cumbersome) financial infrastructure and government central banks with stable currencies is absolutely necessary.
Defi transactions, to scale globally, require stable and predictable value. Government-issued currencies are the only reliable and foreseeable foundation. Cryptocurrencies, such as Bitcoin were never currencies. They are a sideshow that will remain a speculative asset, and increasingly unimportant.
Cryptocurrencies represent an architectural shift in how financial infrastructure and technology interact, and therefore, it is disrupting how the financial industry works globally. It is neither a new kind of money system nor a danger to economic stability. It is more important than that.
Technology is facing a substantial crossroads as policy changes with global resonance, such as China’s new crackdown on the country’s big tech companies (such as Ant Financial and Didi Global), the rising resistance to social media behemoths like Facebook, and the need for governments, whether in the United States, Western Europe, or China, to manage and control technological development. Regardless of any good intentions, this will add friction, inefficiency, and underperformance to the most dynamic global industry. The best intentions usually bring disastrous consequences. China cannot escape the law of unintended consequences. Trying to “manage” innovation and creativity takes away the often unplanned and serendipitous breakthroughs that make many significant advancements possible in the first place. From an economic perspective, capital is not going to invest in an uncertain environment where prosperity is managed and, despite great risk where most ventures will fail, the truly successful ones which make up for the losses and encourage capital to keep investing, will be mitigated. The vanguard of capital flight from China is beginning, and it will not ease if this policy and attitude are not revised. This attempt at “fairness and more equal distribution” will do nothing more than keep capital away and stifle any attempt at creativity, technical innovation, and economic advancement. The intention of this policy will yield the opposite outcome as a consequence. The signal means substance. Substance means innovation, creativity, and competitive dynamics that create the most effective innovations, the best solutions, and the most sustainable companies. Central planning, bureaucratic industrial policy, government-led economic management, and dictatorial focus have always failed, and always will. The US should not fall into this trap, regardless of how appealing it may be.
The “Thucydides trap” is where a rising nation-state – for Thucydides it was Athens – must eventually have a violent confrontation with the existing dominant nation-state – Sparta in his time. It is a zero-sum game where there can be only one dominant nation-state as the eventual winner – and it is usually assumed to be the rising nation-state outdoing the dominant nation-state.
Today, many “experts” (and I have great disdain for self-proclaimed experts) believe this is the circumstance between the US and China. We are headed toward violent confrontation where there can be only one winner. I read the book by Thucydides about the conflict between Athens and Sparta (I cannot be dispassionate here about that outcome because my family is from Sparta on my father’s side). But I fundamentally disagree with Thucydides’s historical descriptions being used as analysis by anyone to describe global events, especially those between the US and China.
Economic predictions have always been highly variable and uncertain, and, for some reason, relied upon as if the future were a magical algorithm. Essentially, economists would make one fundamental mistake. They thought they were practicing a science. Data could be collected, inputted, and a predictive algorithm could be generated. Even Nobel Prize winners like Paul Samuelson believed that with enough data we could come to understand the economy and how it functioned.
This is nonsense. As Daniel Kahneman and Amos Tversky have shown us, human behavior and irrationality, combined with unpredictability and randomness (thank you Naseem Taleb) make this even a questionable social science. Using existing analysis and algorithms to reliably forecast is a fool’s errand, essential for someone’s tenure, and maybe even a Nobel Prize, but doesn’t add much that is useful. Some of the more laughable Nobel Prizes have been given to people who determined that markets were efficient. They are not. Economies can be predicted with useful data input. They cannot. A couple of inputs about inflation and the unemployment rate, and we know how to manage an economy. We can’t. That last one is the Philip’s Curve – true for a limited time and then it goes spectacularly wrong – a lot like most risk and market prediction models.
