Capitalogix

Camp Kotok: Back Again!

I was just in Maine at Camp Kotok, a private gathering of economists, fund managers, and other financial industry professionals. 

There was limited phone service or access to the Internet… so people had to talk with each other.  And unlike most of my schedule, almost everything happened outside.  Discussions, while vigorous, often take place while fishing or grilling. 

At a past Camp Kotok, I did this interview with Bob Eisenbeis, Cumberland Advisors' Vice Chairman & Chief Monetary Economist.  Check it out. 

 

Cumberland Advisors via YouTube

 

Camp Kotok is an interesting place. The event transformed from a simple retreat after 9/11 ... when many attendees experienced the WTC collapse and came together for some fellowship and to discuss their experiences.  From then on, attendance grew, and the gathering evolved. 

As a side note, before the gathering became known as Camp Kotok, it was referred to as the “Shadow Fed” (in part because of the people who attend).

Attendees are bound to “Chatham House Rules” (participants are free to use the information received, but neither the identity nor the affiliation of the speaker(s), nor that of any other participant, may be revealed).  However, general thoughts, ideas, forecasts, and comments can be discussed and published.

On this trip, I talked with David Kotok about the event, what it means, and how it’s grown.

The intent of the participants (and the environment) helps create a platform for meaningful and productive conversations about the opportunities and obstacles facing America and the world. 

Every year, I come back with new ideas and fresh perspectives on things I forget to think about. 

AI was on everyone's mind.  The financial industry is changing quickly, and I’m confident that advanced technology will become an even bigger driver. 

In general, economically, the mood was cautiously optimistic to bullish. 

Remember, it is an election year!

"Is The Stock Market Going To Crash?!"

I usually don't concern myself with looking at stock charts anymore, but I still like paying attention to what people say about them ... 

Recently, I saw this image posted.

via r/StockMarket

So, will the market attract buyers … or sellers?

Personally, I expect volatility.  

Why?  

Because markets exist to trade, and it tends to generate those trades by 'shaking' the weak holders.  

A big move up here will trigger a lot of buying (and short-covering by weak bears).  

While a big move down will trigger a lot of selling (as Bulls fear the long-anticipated next leg down).

I also recognize that we're entering an election year. So there's still time for a correction before a sustained rally.

Here's the problem.  Even though I still enjoy the mental exercise of going through these scenarios, I recognize how little value they add.

You can look at any point in history and find articles and charts that tell you the world is ending, or that the fear is overblown and we're going to get to the other side, and there's a pot of gold waiting for you. 

It's easy to use charts to explain what happened. It is a lot harder to use charts to predict what is about to happen.

I still keep my ear to the ground because I like having a feeling for the sentiment around both experienced investors and your average Joe.  Conventional trading wisdom says that crowds are usually wrong at turning points.  That doesn't mean they are always wrong (still, it makes sense to notice when Smart Money clearly disagrees). 

Knowing these things doesn't make any difference in the decisions I make about trading ... because I let the computer make those decisions.  Nonetheless, it makes me feel better. 

So, is the stock market going to crash?  Who knows?  Anyone that pretends they know is full of it.  There are too many factors at play to decide whether the market is going to crash.

From my perspective, it doesn't make sense to try to predict something random.

On the other hand, if you don't know what your edge is ... you don't have one.

Algorithmic trading is about creating more ways to win. 

To be effective, algorithmic trading is about switching from lower expectancy positions to higher expectancy positions.

In general, here is how that works.

Understand that you can make trading decisions based on market patterns, trends, sentiment, statistics, behavioral economics, game theory, reversion to the mean, or countless other methods.  Further, realize that no technique works all the time ... but there is always a technique that works (even if that means getting out of the market). 

There is an advantage in tracking each of these to gain a perspective of perspectives (in order to identify an advantage or opportunity in real-time as it happens). For example, you could measure and calculate a blend of your confidence in an algorithm or technique and how it is performing.  This creates the opportunity to switch into and out of various techniques and markets as things change.

Having an edge in trading often comes down to information asymmetry. This means knowing more, faster, better, or different things than what others are using to make decisions.

Hope that helps.

Understanding Industrial Revolutions

Last week, I talked about the potential for room-temperature superconductors. 

In that discussion, I noted that we are now in the 4th Industrial Revolution, in part because of better and more connected chips (semiconductors).

I want to dive back into Industrial Revolutions because we're at an inflection point in AI and chips. 

A Look at Industrial Revolutions

The Industrial Revolution has two phases: one material, the other social; one concerning the making of things, the other concerning the making of men. - Charles A. Beard

There are several turning points in our history where the world changed forever.  Former paradigms and realities became relics of a bygone era. 

Tomorrow's workforce will require different skills and face different challenges than we do today.  You can consider this the Fourth Industrial Revolution.  Compare today's changes to our previous industrial revolutions. 

• First industrial revolution - Discovery of the steam engine and creation of factories
• Second industrial revolution - Introduction of the assembly line and mass production
• Third industrial revolution - The world wide web and computers connect the world, enabling the digital age. 

Each revolution shared multiple similarities.  They were disruptive.  They were centered on technological innovation.  They created concatenating socio-cultural impacts.

Since most of us remember the third revolution, let's spend some time on that. 

Here's a map of the entire "internet" in 1973. 

Reddit via @WorkerGnome.

Most of us didn't use the internet at this point, but you probably remember Web1 (static HTML pages, a 5-minute download to view a 3Mb picture, and of course ... waiting for a website to load over the dialup connection before you could read it).  It was still amazing!

Then, Web 2.0 came, and so did everything we now associate with the internet; Facebook, YouTube, ubiquitous porn sites, and Google.  But, with Web 2.0 also came user tracking and advertising, which meant that we became the "product."  Remember, you're not the customers of those platforms - advertisers are.  And if you're not the customer, you're the product.  And when you're not the customer, there's no reason for the platforms not to censor what you see, hear, or experience to control the narrative. 

Now we're seeing a focus on the Blockchain, and its reliant technologies, with Web3.

Where we are and where we are going

I believe that, if managed well, the Fourth Industrial Revolution can bring a new cultural renaissance, which will make us feel part of something much larger than ourselves: a true global civilization. I believe the changes that will sweep through society can provide a more inclusive, sustainable and harmonious society. But it will not come easily. – Klaus Schwab

With Web3, A.I., better chips, and more, we're at the apex of another inflection point.  As a result, the game is changing, as are the rules, the players, and what it means to win. 

At significant transition points, it is easy to see fear, resistance, and a push to keep things the same.  Yet, time marches on.  Much of the pain felt during these transitions occurs because people hesitate to adapt.  As a result, the wave crashes on them instead of them riding it to safety. 

Robots can do many things, but they've yet to match humanity's creativity and emotional insight.  As automation spreads to more jobs, the need for management, creativity, and decision-making won't go anywhere … data and analytics might augment them, but they won't disappear. 

Our uniqueness and flexibility rightly protect our usefulness.  AI and automation free us up to be our best selves and to explore new possibilities. 

All of these changes bring about a decentralization of power - and a new set of freedoms for people – including the ability to discover and adopt capabilities in less time and with less effort.  But, to bring it back to my skepticism again, there are a lot of roadblocks, interferences, and time between now and the consumer being in control again. 

We can shorten that distance, though.  This reminds me of a quote by Elon Musk: 

Stop being patient and start asking yourself, how do I accomplish my 10 year plan in 6 months? You will probably fail but you will be a lot further ahead than the person who simply accepted it was going to take 10 years."

One of an entrepreneur's most powerful capabilities is the ability to shorten time - and get more done than others thought possible. 

Onwards!

Are You Ready For Some Football?

Are you ready for some Football?

Yesterday was the Cowboys' first preseason game. 

It wasn't exactly the prettiest (partly because it was the first game of the season, but also because many of the starters sat the game out to avoid injury).  With that said, it was still a fantastic experience.  The NFL (and Jerry Jones) knows how to put on a show. 

 

It's Easy to Feel Good at the Start of a Season.

Lots of people ask me how the Cowboys look this year.  The truth is, at this point in the season, it's impossible to know because injuries have a dramatic impact on the game.  

Regardless, each year I choose to be optimistic about the chance of a post-season run. 

That kind of logic (or lack there of) is why I think automated trading is better than humans attempting to do it themselves.  It's a way to make objective decisions and eliminate fear, greed, and discretionary mistakes.

On the other hand, it feels so good to hope!

A Lesson From the Game.

I had an interesting discussion at the game yesterday.  My guest commented that Jerry Jones is a fantastic business person - which is hard to argue - but probably shouldn't be running the team.  He believes the team needs a change of pace to switch things up. 

While I don't know if that's why we tend to struggle so much more late in the season, it reminded me of a great business lesson. 

Entrepreneurs often mistake their domain expertise for general expertise.  "I'm fantastic because I'm fantastic at all these different things." And the result is they overestimate their ability to be great at things outside their unique ability.  A similar issue is that many people believe they are deep thinkers, because they think deeply about what they think about.  However, they often don't realize how narrow their range of thinking is, and how many things fall outside their expertise, interest, or even consideration.

Less Is Often More.

Learning to offload tasks that you may not be as fantastic at as others is a great way to free up time to focus on not only the things that you're great at – but also bring you joy and energy. 

Hope that helps!

How 'bout them Cowboys!

A Brief Look At Quantum Computing

I am not an expert on quantum computing ... but I saw an impressive photo of Google's new quantum computer, and thought it was worth diving a bit deeper. 

Google's computer stands at the forefront of computing technologies. This extraordinary device boasts 70 qubits, a significant improvement over the previous 2019 model, which had 53 qubits. A qubit is the quantum world's answer to classical bits. Not to dive too deep, but as you increase the number of qubits in a model, the possible states a quantum computer can hold simultaneously grows exponentially (due to quantum entanglement,) allowing it to perform faster calculations.

So, while 70 qubits don't sound like that much, it calculates exponentially faster than normal computers. For some context, Google's team used a synthetic benchmark called random circuit sampling to test the system's speed, and the results showed that they could perform calculations in seconds that would take the world's most powerful supercomputer, Frontier, 47 years. 

Four years ago, Google announced that they'd reached quantum supremacy, a benchmark demonstrating that a programmable quantum device could solve a problem impossible for classical computers to solve within a practical timeframe. It took less than five years to successfully establish the technological feasibility of quantum computers. 

The progress made in quantum computing enhances our capacity to tackle complex problems that previously posed a challenge (or seemed impossible). The ripple effects will extend to other domains and industries (improving artificial intelligence, logistics, medicine, and almost anything you can imagine). As with the space race or AI, the benefits will not be limited to the realm in which they were created ... but will also have a significant impact on broader industries, the world, and our lives.

 

It's important to temper your expectations and recognize that quantum technology is still in its infancy. It comes with significant limitations, such as the need for extremely low temperatures and precise magnetic fields. Even if these specific conditions are satisfied, there will be stability issues. Additionally, the current cost to develop and operate this technology is quite high.

But, it's an exciting horizon for us to walk towards. 

Onwards!

Here Are Some Links For Your Weekly Reading - July 9th, 2023

Here are some of the posts that caught my eye recently. Hope you find something interesting.

Lighter Links:

• France Set to Allow Police to Spy Through Phones. (Lemonde)
• Your Most Ambivalent Relationships are the Most Toxic. (NYT)
• Is Positive Psychology Science or Snake Oil? (PsychologyToday)
• Einstein and Musk Chatbots Are Driving Millions to Download Character.AI. (Bloomberg)
• New Report Warns of Brain Control Weapons Being Developed by Communist China. (DailyWire)

Trading Links:

• The Copyright Battles Against OpenAI Have Begun. (Quartz)
• Baby Boomers Own Pretty Much Everything - But Millennials Could Be About to Catch Up. (Markets)
• Forbes World's Billionaires List 2023: The Top 200. (Forbes)
• Wall Street Soothsayers Are Bewildered About What's Next. (Bloomberg)
• SVB, BBBY, Lordstown Lead List of US Bankruptcies as Companies Fold up at the Fastest Pace Since 2010. (Markets)

Economic Allies and Economic Enemies

Last week, I brought up the concept of Economic Freedom. It reminded me of an idea I last shared in 2008, during the housing crisis. 

I noticed how correlated and coordinated worldwide actions were during the housing crisis. During the pandemic, while there was a lot of dissent, there was also a remarkable amount of coordination. 

The concept of economic allies presupposes that we also have economic enemies. It’s easy to construct a theory that countries like Russia and China use financial markets to exert leverage in a nascent form of economic warfare.

It's easy to come up with a theory that suggests we are our own worst enemies. Our innate fear and greed instincts (and how we react to them) tend to lead us down a path of horrifying consequences. This has been evident in recent years, not just in society, but also in the world of business. I am confident that this pattern will persist in the context of Artificial Intelligence, with both its potential benefits and risks.

The butterfly effect theorizes that a butterfly flapping its wings in Beijing on one day can create or impact a rainstorm over Chicago a few days later. Similarly, in a world with extensive global communication and where automated trading programs (and even toasters) can interact with each other from anywhere across the globe, it is not surprising that market movements are becoming larger, faster, and more volatile.

Perhaps governments cooperate and collaborate because they collectively recognize the need for a new form of protection to mitigate the increasing speed, size, and leverage behind market movements.

And we can also extend this idea to other entities beyond governments. It doesn’t have to be limited to traditional markets either; it can include cryptocurrencies or other emerging technologies as well.

It’s worth understanding the currents, but we must also consider the undercurrents and countercurrents. 

Conspiracy theories are rarely healthy or helpful, but maintaining a healthy skepticism is a great survival mechanism.

Hope that helps.

The AI Hacking Paradox

Fear is a natural response to change or the unknown, serving as an evolutionary mechanism designed to safeguard us. However, it’s also worth noting that many of our fears turn out to be unjustified.

Sometimes, however, fear is a much-needed early warning system. 

In the context of AI hacking, you should be afraid. Given the exponential growth in technology and artificial intelligence, concerns about security breaches and intentional misinformation campaigns have become common.

In 2016, DARPA created the Cyber Grand Challenge to illustrate the need for automated, scalable, machine-speed vulnerability detection as more and more systems—from household appliances to major military platforms—got connected to each other and the internet. During this event, AI systems competed against each other to autonomously hack and exploit vulnerabilities in computer programs. The competition revealed the unprecedented speed, scope, scale, and sophistication with which AI systems can find and exploit vulnerabilities.

And that was seven years ago. 

AI hackers operate at superhuman speeds and can analyze massive amounts of data, enabling them to uncover vulnerabilities that might elude human hackers. Their ability to think differently, free from human constraints, allows AI systems to devise novel hacks that humans would never consider. This creates an asymmetrical advantage for AI hackers, making them formidable at infiltrating and compromising systems.

We expect people to use AI for malicious purposes intentionally, but unintentional AI hacking arises when an AI autonomously discovers a solution or workaround that its creators did not intend. This type of hack can remain undetected for extended periods, amplifying the potential damage caused. 

So, how do we stop it?

Ironically, or perhaps, exactly as you would expect it, AI itself holds the key to defending against future attacks. Just as hacking can drive progress by exposing vulnerabilities and prompting improvements, AI hackers could potentially identify and rectify weaknesses in software, regulations, and other systems. By proactively searching for vulnerabilities, they can contribute to making these systems more hack-resistant. This is the paradox of AI hacking. 

It’s the same concept as I mentioned in the article on potentially halting the creation of generative AI.  

Unfortunately, when you invent the car, you also invent the potential for car crashes ... when you ‘invent’ nuclear energy, you create the potential for atomic bombs. That’s not a reason to stop innovation - it’s a call to action for innovators to respond faster and counteract the bad actors. 

We can’t stop bad actors from existing - but we can get better at preventing harm due to them. This is a helpful framework for innovation. If you want to stop the bad actors from misusing a technology, the good actors "simply" have to get better at using the technology faster. 

The best way to stop negative motion is with positive motion. But, we can also make moves in the background to counteract bad actors and bad actions.

For example: 

1. Regulation and Transparency: Regulatory frameworks can be established for AI technologies that demand transparency regarding how they function and how they’re secured.
2. Ethical Guidelines: Implementing ethical guidelines for AI development can help prevent misuse.
3. Cybersecurity Measures: Enhancing cybersecurity protocols and utilizing state-of-the-art encryption methods could make AI systems more resilient against hacking attempts.
4. Education: Increasing public understanding of AI technologies would spread awareness of their benefits alongside potential risks.

While these measures won’t eliminate the potential risk of AI hacking, they could significantly mitigate it and provide reassurances about employing such technologies.

Understanding Economic Freedom

We often think about the U.S. as the "land of the free." That is good marketing ... but is it true?  In large part, it depends on the contexts and frameworks you choose to evaluate what constitutes freedom. 

For example, Strategic Coach breaks "entrepreneurial freedom" into four categories: time, money, relationships, and purpose.

Meanwhile, if you look at the First Amendment of the U.S. Constitution, you've got freedom of speech, press, assembly, and the right to petition the government ... and we've since instituted a litany of other freedoms and liberties. 

In this post, we will examine the concept of economic freedom.  Economic freedom represents more than just freedom to make money, it pertains to the decisions and liberties one has in that pursuit. 

The Heritage Foundation releases a yearly Economic Freedom Index. 

 

 

According to VisualCapitalist, the ranking uses four broad categories, each with three key indicators to measure economic freedom.

1. Rule of law: property rights, judicial effectiveness, government integrity
2. Size of government: tax burdens, fiscal health, government spending
3. Regulatory efficiency: labor freedom, monetary freedom, business freedom
4. Open markets: financial freedom, trade freedom, investment freedom

The 12 indicators are weighted equally and scored from 0-100.  The overall score is the average score among those indicators. 

Based on these metrics, the U.S. doesn't even enter the top 10. 

Surprisingly, the U.S. ranks 25th overall - and only 3rd in the Americas. 

Now, freedom means a lot of different things, and economic freedom is only one of many modalities ... but it's an important factor. 

If you were in control, what change would you make to increase the United States' economic freedom?  If you're not from the U.S., where does your country rank, and why?

Nvidia Joins The Trillionaire Club

Believe it or not, Nvidia is now worth nearly as much as Amazon. America’s largest semiconductor company has skyrocketed past the $1 trillion market cap mark and joined the likes of Apple, Amazon, and Microsoft. 

via visualcapitalist

My Thoughts

Nvidia’s growth is largely built on the back of the AI hype. It is also a mainstay of technology, benefitting a litany of AI projects, gaming systems, crypto mining, and more. 

But, the question is whether it will continue to rise in popularity – or see a “correction” to pre-hype levels. I think the reality is you’ll see both happen.

Despite my obvious bullishness on AI as a market mover and industry transformer, after a hype cycle comes a trough of disillusionment. The media attention on AI will diminish again. Meanwhile, tech giants like Google and Apple rely on the technology, and Nvidia has also launched new products spanning from robotics to gaming. So, as the hype dies down, its mainstream uses will increase. 

These chips will only continue to be more important. We saw the company’s stock rise and fall during the peak of inflated expectations of cryptocurrency, but AI’s staying power - I believe - is inevitable. 

So, while it may not be a good investment in the short term, it’s a technology you can count on to be essential for decades.