Capitalogix

The Intersection of Fintech, AI, and Analytics

At the beginning of the pandemic, I participated in a series of webinars for IBM. The focus was on building smart and secure financial services. My talk was about advanced computing and the new world of trading.

Challenging times drive advancement - and what better time to talk about advancements in technology (and their applications) than in the midst of a global pandemic. 

You can watch a replay of the Fintech webinar here. There are several interesting presentations.  If you just want to watch my presentation, it starts at the 5:16 mark.

In addition, I've uploaded a different version of just my talk that you can watch directly here.

 

IBM and Capitalogix via YouTube

In the past, trading used to be about people trading with people. Markets represented the collective fear and greed of populations. So, price patterns and other technical analysis measures represented the collective fear and greed of a population. If you could capture that data and figure out certain statistical probabilities, you might have had an edge. The keywords are "might have". 

If you had more information than your competitors - meaning, an information asymmetry - you had an amazing edge. At one time, that was being able to print out reports on stocks from that new-fangled technology called the internet. As time passed, it became harder to gain an asymmetric information advantage (because people had access to more and better data). 

Each generation of traders finds new ways to play the game and generate "Alpha" (the excess return generated by manager skill, rather than luck or excess risk). As soon as enough people adopt a strategy (or figure out a way to combat it), the edge begins to decay.

When computerized data became available, simply understanding how to download and use it generated Alpha. The same could be said for each later evolution – the adoption of complex algorithms, access to massive amounts of clean data, or the adoption of AI strategies.

Each time a new shift happens, traders pivot or fail – it's not that active trading stopped working – it's that the tools, speed, and styles necessary to play that game evolved.

Said another way, the rules, the players, and the game (itself) have all changed. Today, technological asymmetry is a significant factor, and your edges come from things like bigger and faster servers, low latency connections to markets, or the ability to calculate the odds better or faster than others.

In the future, I see those edges combining as artificial intelligence starts to leverage exponential technologies and new data sources (like alternative data and metadata feedback loops). It is easy to imagine a time when information is the "fuel," but your ability to digest and parse that information is the "engine." 

Playing a New Game

Historically, most active traders don't beat the S&P in any given year ... and even less beat it with any semblance of consistency.  But those that do – the ones that have been doing it for long enough that it's not chance ... exercise a willingness (and a skill) to adapt quickly. 

One of Charles Darwin's best-known concepts is: It is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change.

While computers have made information accessible to everyone, they've also created a massive asymmetric information advantage for those who have both the access and the skill to best use the massive amounts of data now available.  This is more complicated than it seems.  You need the information, the technology, the process, and the people.  There is so much data available now that figuring out what to ignore is probably more important than what to use.  Likewise, the ability to ingest, clean, validate and curate the data is a huge hurdle that most can't clear.

I talk about much more in the video but boiling down the main points, ask yourself (in business, in trading, in life) are you separating the "signal" from the "noise?"

A technological advantage doesn't mean anything if you're plugging in inaccurate or biased data into it ... just like with the news. 

But, even with those skills, it's harder than ever to take advantage of inefficiencies (edges) than ever before.  The edges are smaller, more fleeting, and surrounded by more volatility and noise.  It's like finding a needle in a haystack.  That being said - finding a needle in a haystack is easy when you have a metal detector. 

That's where A.I. has come in for us. We use A.I. to develop algorithms, analyze markets, and create meaning where humans can't find any. 

We live in exciting times. 

Onwards!

Here Are Some Links For Your Weekly Reading - May 1st, 2022

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

Lighter Links:

• What is Web 3.0? Here's What the Internet Will Look Like In the Future. (LaptopMag)
• Amazing Video Shows a Tiny Jumping Robot Like Nothing You've Ever Seen. (BGR)
• 103 Bits of Advice I Wish I Had Known. (Kevin Kelly’s Technium)
• Does (Hand) Size Matter? Inside the NFL Draft's Fear of Tiny-Handed QBs. (GQ)
• This $2 Billion Personal Submarine is So Huge that It Can Dwarf a MegaYacht. the Vessel is Almost Three Times Longer Than a Football Field, It Has Lavish VIP Suites, a Helipad and Even an Open Deck Swimming Pool. (LL)

 

Trading Links:

• Bored Ape Metaverse Frenzy Raises Millions, Disrupts Ethereum. (Bloomberg)
• Can Capitalism Survive? 80 Years After Schumpeter's Answer. (AIER)
• Americans are Showing Inflation Fatigue, and Some Companies See a Breaking Point. (FoxBusiness)
• Foreclosure Filings are Up 132% From a Year Prior. Here's What that Means for the Housing Market (And It's Not What You Might Think). (MarketWatch)
• Warren Buffett and Charlie Munger Called Out Stock-Market Gamblers, Dismissed Bitcoin as Worthless, and Underlined the Risks of Inflation. Here are Their 12 Best Quotes from Berkshire Hathaway's Annual Meeting. (Markets)

How Tech Giants Make Their Money

In 2021, the Big Five – Alphabet (Google), Amazon, Apple, Meta (Facebook), and Microsoft - generated over $1.4 trillion in revenue.

How did they generate that revenue? We know they sell products ... but we also know that we're often the product they sell. 

Google and Facebook each make a lot of money selling you (or data about you) to advertisers. 

The image below shows how Alphabet generated its revenue.   The full infographic shows that breakdown for each of the Big Five.

Click to view the other companies via visualcapitalist

Apple, Amazon, and Microsoft, primarily sell products (like more traditional businesses). On the other hand, almost 98% of Meta's revenue (and 81% of Google's revenue) comes from advertising. 

Unsurprisingly, all five companies saw significant growth during the pandemic. 

Though the economy shrank in the past two years, societal changes continued to push demand for big tech's products and services. 

Will growth continue or slow down? 

I'm curious what you think.

Global Happiness Levels in 2022

Happiness is a complex concept comprised of conditions that highlight positive emotions over negative ones – bolstered by the support of comfort, freedom, wealth, and other things people aspire to experience. 

Regardless of how hard it is to describe (let alone quantify) ... humans strive for happiness.

Likewise, it is hard to imagine a well-balanced and objective "Happiness Report" because so much of the data required to compile it seems subjective and requires self-reporting. 

Nonetheless, the World Happiness Report takes an annual look at quantifiable factors (like health, wealth, GDP, and life expectancy) and more intangible factors (like social support, generosity, emotions, and perceptions of local government and businesses).  Click the image below to view the Report.

via visualcapitalist

In their 2021 report, there was a significant focus on the effect of COVID-19 on happiness levels and mental health. Much of that continued into the 2022 report. 

As you might expect, the pandemic caused a significant increase in negative emotions reported. Specifically, there were substantial increases in reports of worry and sadness across the ninety-five countries surveyed.  The decline in mental health was higher in groups prone to disenfranchisement or other particular challenges – e.g., women, young people, and poorer people. 

It is remarkable how resilient and stable the scores have been globally considering the amount of uncertainty, stress, and disruption households experienced this past year.

Ultimately, humans persevered in the face of economic insecurity, anxiety, and challenges to mental and physical health. 

This year, the average score improved slightly compared to 2021 - though worry and stress have continued to rise. 

There has been a decrease in overall happiness compared to pre-pandemic scores.  Yet, the relative balance demonstrated in the face of such adversity may point towards the existence of a hedonic treadmill - or a set-point of happiness.

Regardless of the circumstances, people can focus on what they choose, define what it means to them, and choose their actions.

I'm still surprised by what people can get used to ... and how some people find pockets of joy in even the hardest of times.  Conversely, other people use the same ability to feel profound unhappiness, even when they have seemingly everything. 

It's an oddly beautiful reminder that happiness comes from within.

Another bright spot, worth mentioning, has been the massive global upsurge in benevolence. People are supporting others, communities have stepped up, more money is being donated to charity, and more people are volunteering. 

Onwards!

Top 20 Internet Giants

For most of my life, I've been a tech early adopter. 

Here are some snippets from that journey. I fell in love with the Mac 128 in the 1980s. My frustration with the limitations of floppies caused me to fly across the country to get one of the earliest 20 MB hard drives (which I didn't know how I would ever fill up). Much to the consternation of those who thought only secretaries should be seen typing, I was one of the first lawyers to use a computer to do work. I waited in lines to grab Palm Pilots and cool phones before smartphones became a thing. And, somehow, I don't enjoy setting up my computer anymore (OK, I do – but not like I did before). 

A lot has changed, while much stays the same.

In the late 90s, I was obsessed with the early web scene. I spoke at computer events like Comdex and MacWorld, and I was able to see and identify many of the companies that would become major players. Many of those "major players" expanded into the dot-com bubble, then disappeared.

I've watched that cycle play itself out several times as the landscape and players changed and evolved.

There is a chart that captures a lot of those changes by listing the 20 Internet Giants that ruled the web since 1998. 

Take a look. 

via visualcapitalist

Humans are very good at recognizing major turning points. However, with that said, they often are much worse than they would believe in regards to understanding the implications of the changes they so easily predicted.

Who would have guessed that AOL would become almost wholly irrelevant? Or that Yahoo would make so many horrible decisions and still last to 2022?

In the early days of the internet, most of the leaders were aggregators and search engines. Now we have a much broader set of influencers. The top 20 players in the space are also playing much larger games than their 1998 predecessors. Most of the leaders are platforms that help other products succeed as well. 

I'm curious to see what names are added to the list in 5 years. 

Who do you believe we will see there in 2027?

Changing the Course of History

A little over a week ago, a deepfake of Ukrainian President Volodymyr Zelenskyy was used to try and convince Ukraine's soldiers to lay down their arms and surrender against Russia.  On top of being shared on social media, hackers got it onto news sites and a TV ticker as well. 

While it's not explicitly known that Russia did this – there's a long history of Russian cyberwarfare, including many instances of media manipulation. 

Luckily, while the lip-sync was okay in this video, several cues helped us know it was fake. 

Unfortunately, this is only the tip of the iceberg.  Many deepfakes aren't as easy to discern.  Consequently, as we fight wars (both physical and cultural), manipulated videos will increasingly alter both perceptions and reality. 

Even when proven to be fake, the damage can persist.  Some people might believe it anyway ... while others may begin distrusting all videos from leaders as potential misinformation. 

That being said, not all deepfakes are malicious, and the potential for the technology is attractive.  Production companies are already using it to splice in actors who might have aged or died into scenes in movies.  Deepfake technology can also be used to allow a celebrity to sell their likeness without having to waste their time doing all the filming necessary to produce the intended finished product. 

Deepfake technology also allows us to create glimpses into potential pasts or futures.  For example, On July 20th, 1969, Neil Armstrong and Buzz Aldrin landed safely on the moon.  They then returned to Earth safely as well.   What if they didn't?  MIT recently created a deepfake of a speech Nixon's speechwriter William Safire wrote during the Apollo 11 mission in case of disaster.  The whole video is worth watching, but the "fake history" speech starts around the 4:20 mark. 

"Fate has ordained that the men who went to the moon to explore in peace will stay on the moon to rest in peace." - Nixon's Apollo 11 Disaster Speech

 

MIT via In Event Of Moon Disaster

Conclusion

“Every record has been destroyed or falsified, every book rewritten, every picture has been repainted, every statue and street building has been renamed, every date has been altered. And the process is continuing day by day and minute by minute. History has stopped.“ - Orwell, 1984

In an ideal world, history would be objective; facts about what happened, unencumbered by the bias of society, or the victor, the narrator, etc.  On some level, however, history is written by the winners.  Think about it ... perceived "truth" is shaped by the bias and perspectives of the chronicler.

Consequently, history (as we know it) is subjective.  The narrative shifts to support the needs of the society that's reporting it. 

The Cold War with the Soviet Union was a great example.  During the war, immediately thereafter, and even today, the interpretation of what transpired has repeatedly changed (both here and there).  The truth is that we are uncertain about what we are certain about.

But while that was one example, to a certain degree, we can see this type of phenomenon everywhere.  Yes, we're even seeing it again with Russia.

But it runs deeper than cyber-warfare.  News stations color the story told based on whether they're red or blue, and the internet is quick to jump on a bandwagon even if the information is hearsay.  The goal is attention rather than truth.

Media disinformation is more dangerous than ever.  Alternative history can only be called that when it's discernible from the truth ... and unfortunately, we're prone to look for information that already fits our biases. 

As deepfakes get better, we'll likely get better at detecting them.  But it's a cat-and-mouse game with no end in sight.  Signaling Theory posits that signalers evolve to become better at manipulating receivers, while receivers become more resistant to manipulation. 

I'm excited about the possibilities of technology, even though new capabilities present us with both promise and peril. 

Meanwhile, "Change" and "Human Nature" remain constant.

And so we go.

A Look at Codebases

When I was a child, NASA got to the Moon with computers much less sophisticated than those we now keep in our pockets.

At that time, when somebody used the term "computers," they were probably referring to people doing math.  The idea that businesses or individuals would use computing devices, as we do now, was far-fetched science fiction.

Recently, I shared an article on the growing "compute" calculations used in machine learning.  We showed that the amount of compute used in machine learning has doubled every six months since 2010, with today's largest models using datasets up to 1,900,000,000,000 points.

This week, I want to take a look at lines of code.  Think of that as a loose proxy showing how sophisticated software is becoming.

 

via informationisbeautiful

As you go through the chart, you'll see that in the early 2000's we had software with up to approximately twenty-five million lines of code.  Meanwhile, today, the average car uses one hundred million, and Google uses two billion lines of code across their internet services. 

For context, if you count DNA as code, the human genome has 3.3 billion lines of code.  So, while technology has increased massively - we're still not close to emulating the complexity of humanity. 

Another thing to consider is that when computers had tighter memory constraints, coders had to be deliberate about how they used each line of code or variable.  They found hacks and workarounds to make a lot out of a little.

However, with an abundance of memory and processing power, software can get bloated as lazy (or lesser) programmers get by with inefficient code.  Consequently, not all the increase in size results from increasing complexity - some of it is the result of lackadaisical programming or more forgiving development platforms.

In better-managed products, they consider whether the code is working as intended as well as reasonable resource usage. 

In our internal development, we look to build modular code that allows us to re-use equations, techniques, and resources.  We look at our platform as a collection of evolving components. 

As the cost and practicality of bigger systems become more manageable, we can use our intellectual property assets differently than before. 

For example, a "trading system" doesn't have to trade profitably to be valuable anymore.  It can be used as a "sensor" that generates useful information for other parts of the system. It helps us move closer to what I like to call, digital omniscience. 

As a result of increased capabilities and capacities, we can use older and less capable components to inform better decision-making.

In the past, computing constraints limited us to use only our most recent system at the highest layer of our framework.

We now have more ways to win.

But, bigger isn't always better - and applying constraints can encourage creativity.

Nonetheless, as technology continues to skyrocket, so will the applications and our expectations about what they can do for us.

We live in exciting times ... Onwards!

No Crying In Trading

As a fund manager, I am always looking for ways to eliminate emotions (like fear and greed).  During crazy times, like these, that is harder than seems.

But as a father whose son just got married, the equation was different.  It's been six years since I originally shared this video; but as we near their wedding anniversary, I re-watched this video ... and decided to share it again. 

One of my son's instructions to the "Officiant" was to make me cry.  I made it through the Ceremony; then, I got a chance to say a few words at the Wedding Reception.  Here they are …

 

The words "I love you" are powerful.  Most people consider it an expression of emotion.  It can also be a promise …

Artificial Intelligence Is Great, Artificial Stupidity Is Scary

When I first got out of Law School in the 1980s, "professionals" didn't type ... that was your assistant's job (or the "typing pool," which was a real thing too).

At that point, most people couldn't have imagined what computers and software are capable of now.  And if you tried to tell people how pervasive computers and 'typing' would be ... they would have thought that you were delusional.

My career has spanned a series of cycles where I was able to imagine what advanced tech would enable (and how businesses would have to change to best leverage those new capabilities).

Malcolm Gladwell suggests that it takes 10,000 hours of focus and effort for someone to become an expert at something.  While that is not necessarily true or accurate, it's still a helpful heuristic.

Today, we can do research that took humans 10,000 hours in the time it took you to read this sentence.  Moreover, technology doesn't forget what it's learned – As a result, technological memory is much better than yours or mine.  Consequently, the type and quality of decisions, inferences, and actions are better as well.  Ultimately, we will leverage the increased speed, capacity, and capabilities of autonomous platforms.  While that is easy to anticipate, the consequences of these discontinuous innovations are hard to predict.  Things often take longer to happen than you would think.  But, when they do, the consequences are often more significant and more far-reaching than anticipated.

Still, technology isn't a cure-all.  Many people miss out on the benefits of A.I. and technology for the same reasons they didn't master the hobbies they picked up as an adolescent. 

I shot a video discussing how to use technology to create a sustainable creative advantage.  Check it out. 

 

 

Many people recognize a "cool" new technology (like A.I.), but they underestimate the level of commitment and effort that mastery takes. 

When using A.I. and high-performance computing, you need to ask the same questions you ask yourself about your ultimate purpose. 

• What's my goal?
• What do I (or my systems) need to learn to accomplish my goal?
• What are the best ways to achieve that goal (or something better)?

Too many companies are focused on A.I. as if that is the goal.  A.I. is simply a tool.  As I mentioned in the video, you must define the problem the right way in order to find an optimal solution. 

Artificial Intelligence is a game-changer - so you have to approach it as such. 

Know your mission and your strategy, recognize what you're committing to, set it as a compass heading and make deliberate movement in that direction. 

I end the video by saying, "Wisdom comes from making finer distinctions.  So, it is an iterative and recursive process... but it is also evolutionary.  And frankly, that is extraordinarily exciting!"

I hope you agree.

Onwards!

A Look At Gas Prices

Gas prices feel very high right now ... but are they? Well, obviously, yes. But, the degree is less than most of us would guess. 

schi854 via usinflationcalculator (Interactive Version)

This chart shows the real cost of gas based on inflation. It also goes back to 1992. It makes a pretty obvious case for inflation being the real culprit. That being said, the rise is still worth watching. On the one hand, the rise in gas prices isn't unprecedented; on the other hand, a surge this sharp has only happened five times in the past 30 years ... and it's been over a decade since the last time it happened.