Capitalogix

To Rebirth & Spring Cleaning

Next Sunday is Easter, but yesterday was the first night of Passover - an 8-day long Jewish holiday that recounts the story of Exodus. 

The overlap can be seen in DaVinci's Last Supper, depicting a Passover Seder and Jesus's last meal before his crucifixion. 

 

 

Part of the Passover Seder tradition involves discussing how to share the story in ways that connect with different types of people, recognizing that everyone understands and relates to things differently.

To do this, we examine the Passover story through the lens of four archetypal children — the Wise Child, the Wicked Child, the Simple Child, and the Child Who Does Not Know How to Ask.

The four children reflect different learning styles — intellectual (Wise), skeptical (Wicked), curious (Simple), and passive (Silent) — and highlight how we must adapt communication to the diverse personalities and developmental stages of our audience.

This seems even more relevant today, as we struggle to come to a consensus on what to believe and how to communicate with people who think differently. 

 

On a lighter note, one of the memorable phrases from Exodus is when Moses says, "Let my people go!"  For generations, people assumed he was talking to the Pharoah about his people's freedom.  But after a week of eating clogging food like matzoh, matzoh balls, and even fried matzoh … for many Jews, "Let my people go" takes on a different meaning.

After Passover, and as we enter a new season, it's a great time for a mental and physical 'Spring Cleaning,' and delve into your experiences to cultivate more of what you desire and less of what you don't.

Here is to Spring, Re-Birth, and Spring Cleaning.

Hope you had a great weekend.

Are Billionaires Popular?

We live in an interesting time. Many billionaires aren’t just business leaders - they’re also influencers, personalities, and public figures. 

While countless billionaires go under the radar, several of today’s billionaires have become controversial figures - like Elon Musk. So, how do the top 10 richest Americans rank in this so-called “popularity contest?”

via visualcapitalist

It’s interesting how many of the 10 wealthiest people in America are still flying relatively under the radar. In my head, names like Sergey Brin or Larry Page should still be household names. 

On the other side of this scale, the three richest billionaires have primarily unfavorable ratings ... with Mark Zuckerburg being the most disliked of the bunch. 

Meanwhile, Warren Buffett and Bill Gates have predominantly positive ratings - though Bill is more polarizing than Buffett. 

As an aside, the world’s richest lost over $200 billion in a single day as news of Trump’s tariffs rocked markets. For context, that drop is the fourth-largest one-day decline in the Bloomberg Billionaires Index’s 13-year history.

Mad About March Madness

March Madness is in full swing and will have the world's attention for a few more days. As you can guess, almost no one has a perfect bracket anymore. McNeese beat Clemson, Drake beat Mizzou, and Arkansas handed Kansas its first first-round loss since 2006. On Friday, the NCAA said that of the over 34 million brackets submitted at the start of March Madness, approximately 1,600 remained perfect. That's less than .1% after the first day. The first game of the tournament - Creighton vs. Louisville - busted over half of the brackets. 

Before 24/7 sports channels, people watched the weekly show "The Wide World of Sports."  Its opening theme promised "The thrill of victory and the agony of defeat!" and "The human drama of athletic competition." That defines March Madness.

The holy grail is mighty elusive in March Madness (as in most things). For example, the odds of getting the perfect bracket are 1 in 9,223,372,036,854,775,808 (that is 1 in 9.223 quintillion if that was too many zeros count). If you want better odds, then you can have a 1 in 2.4 trillion chance based on a Duke Mathematician's formula that takes into account ranks). It's easier to win back-to-back lotteries than picking a perfect bracket. Nonetheless, I bet you felt pretty good when you filled out your bracket.

via Duke University

Here's some more crazy March Madness Stats: 

• Companies expect $4 Billion of corporate losses due to employees tracking games
• The highest-paid NCAA coach, Kansas's Bill Self, makes a salary of $8.8 Million
• In 2018, it was estimated that March Madness generated $10 Billion in gambling (twice as much as the Super Bowl)

 

Feeding the Madness

"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson

In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.

Finding an edge is hard - Maintaining an edge is even harder.

That's not to say there aren't edges to be found. 

Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray. 

The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted. 

You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.

In reality, several of the highest-ranked brackets every year are guesses. 

The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction. 

Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found. 

In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.

Can machine learning also help in March Madness?

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion. 

Two lessons can be learned from this:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

 

Feeding the Madness

"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson

In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.

Finding an edge is hard - Maintaining an edge is even harder.

That's not to say there aren't edges to be found. 

Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray. 

The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted. 

You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.

In reality, several of the highest-ranked brackets every year are guesses. 

The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction. 

Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found. 

In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.

Can machine learning also help in March Madness?

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion. 

Two lessons can be learned from this:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

The Psychology of Gamblers

March Madness, Vegas, and Wall Street share a lot in common. 

Over Time ... The House Wins

Casinos only offer to play games that they expect to win. In contrast, gambling customers play even though they know the odds are against them.

Why does this happen? The rush of a win, the chance of a big win, and random reinforcement are common factors that incentivize people to play the lotto, go to a casino, or try to trade.

Chemicals like adrenaline and dopamine play a part as well. Even in a sea of losses, your body can't help but crave the chemical reward of even a small win.

The "House" knows this and engineers an experience that takes advantage of it.  

In the case of casinos, every detail is meticulously crafted to extract you from your money - from carpet patterns to the labyrinthian layouts, the music, the lights, and even the games themselves. 

Here is an infographic that lays it out for you. 

Bojoko via DailyInfographic

Most people aren't gamblers ... the fear of losing big inhibits them. However, when people were instructed to "think like a trader," they showed considerably less risk aversion when gambling. And I bet you have no problem filling out a March Madness bracket, even if you put money on the line. 

The illusion of control convinces us we can overcome the statistics. 

When you almost get it right - when you guess the first round of March Madness correctly, when you miss the jackpot by one slot on a slot machine, when you just mistime a trade to get a big win - you're more likely to play longer, and place bigger bets ... because you're "so close." 

It's human nature to want to feel in control. 

This is why you find a lot of superstitious traders & gamblers. If you wear this lucky item of clothing ... if you throw the dice in this particular way ... if you check your holdings at this time every day ... you have control. 

There is a big difference between causation and correlation. 

It is not hard to imagine that, for most traders, the majority of their activities do little to create a real and lasting edge.  

Skill vs. Luck

There are games of skill, and there are games of chance.

In a casino, poker, and blackjack are considered games of skill. In contrast, slot machines are considered a game of chance.

In trading, predicting markets is much different than using math and statistics to measure the performance of a technique.

Much of what we do is to figure out how to eliminate the fear, greed, and discretionary mistakes humans bring to trading.

In trading, "Alpha" is the measure of excess return attributed to manager skill, rather than luck or taking on more risk.

We believe in Alpha-by-Avoidance ... Meaning much of what we do is figure out what to ignore or avoid so that more of the games we play are games of skill rather than games of chance.

Are you playing the right game?

Skype's Kodak Moment: Remnants of a Past Era

Last week, Microsoft announced that Skype would shut down in May ... after over two decades of service. 

Hydrox existed before Oreo, and Betamax before VHS.

But Skype might be even more surprising. Skype was so ubiquitous that it became a verb and eponymous with video calling. As a world traveler, Skype also used to be the go-to international calling app.

Imagine if Kleenex, Jell-O, or Band-Aids went out of business. 

That’s what Skype did - and it’s not the first tech business to fail similarly...

Thinking Linearly in an Exponential Age

Humans can’t do a lot of things. Honestly, the fact that we’re at the top of the food chain is pretty miraculous. 

We’re slow, weak, and famously bad at understanding large numbers or exponential growth. 

Making matters worse, our brains are hardwired to think locally and linearly.

It’s a monumental task for us to fathom exponential growth … let alone its implications. 

Think how many companies have failed due to that inability … RadioShack couldn’t understand a future where shopping was done online – and Kodak didn’t think digital cameras would replace good ol’ film. Blockbuster couldn’t foresee a future where people would want movies in their mailboxes because “part of the joy is seeing all your options!” They didn’t even make it long enough to see “Netflix and Chill” become a thing. The list goes on. 

 

via Diamandis

Human perception is linear. Technological growth is exponential.

There are many examples. Here is one Peter Diamandis calls “The Kodak Moment” (a play on words of “a Kodak Moment”... the phrase Kodak used in advertising to mean a “special moment that’s worth capturing with a camera”). 

In 1996, Kodak was at the top of its game, with a market cap of over $28 billion and 140,000 employees.

Few people know that 20 years earlier, in 1976, Kodak had invented the digital camera. It had the patents and the first-mover advantage.

But that first digital camera was a baby that only its inventor could love and appreciate.

That first camera took .01 megapixel photos, took 23 seconds to record the image to a tape drive, and only shot in black and white.

Not surprisingly, Kodak ignored the technology and its implications.

Fast forward to 2012, when Kodak filed for bankruptcy – disrupted by the very technology that they invented and subsequently ignored.

via Diamandis

Innovation is a reminder that you can’t be medium-obsessed. Kodak’s goal was to preserve memories. It wasn’t to sell film. Blockbuster’s goal wasn’t to get people in their stores, it was to get movies in homes.  

Henry Ford famously said: “If I had asked people what they wanted, they would have said faster horses.” Steve Jobs was famous for spending all his time with customers, but never asking them what they wanted.

Two of our greatest innovators realized something that many never do. Being conscientious of your consumers doesn’t necessarily mean listening to them. It means thinking about and anticipating their wants and future needs.

Meanwhile, despite Skype having several features that Zoom still hasn’t implemented, Zoom recognized an opportunity during COVID and capitalized. When Microsoft bought Skype, they focused on adding several new features and expanding the range of services instead of improving the quality of their audio or video. Meanwhile, when Zoom entered the space, they brought much better servers and the ability to have much larger rooms. More attendees meant a wider variety of use cases and quicker adoption and referral cycles. They also made it easy to join a Zoom room. Instead of getting your e-mail up front and forcing you to create an account to use it, they let you join a meeting without an account. You only needed an account to host a meeting. 

They focused on making it easy to use their service and on having a clear identity instead of trying to ride every wave and become unfocused. Of course, at the same time, Microsoft stopped focusing on the tool, with an increased focus on their new competitor to Zoom, Teams. 

Tech and AI are creating tectonic forces throughout industry and the world. It is time to embrace and leverage what that makes possible. History has many prior examples of Creative Destruction (and what gets left in the dust).

Opportunity or Chaos …  You get to decide.

Don’t forget ... you don’t have to be the first mover to win in the end. 

Onwards!

Here Are Some Links For Your Weekly Reading - February 9th, 2025

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

Lighter Links:

• OpenAI's Deep Research Smashes Records for the World's Hardest AI Exam, With ChatGPT O3-Mini and DeepSeek Left in Its Wake. (TechRadar)
• You Can Try DeepSeek’s R1 Through Perplexity—without the Security Risk. (FastCompany)
• The Recruitment Effort that Helped Build Elon Musk’s DOGE Army. (Wired)
• Humans are Evolving Before Our Eyes on the Tibetan Plateau. (ScienceAlert)
• How to Naturally Boost Your Dopamine, Oxytocin, Serotonin, and Endorphins. (FastCompany)

 

 

Trading Links:

• The True Cost of a Super Bowl Ad? You Don’t Want to Know. (FastCompany)
• Trump Says America Was at Its Richest in the Late 1800s. Is That True? (MarketWatch)
• The “5 Types of Wealth”: Why You’re Wealthier Than You Think. (BigThink)
• America’s Most Generous Philanthropists 2025. (Forbes)
• Why the AI World is Suddenly Obsessed With a 160-Year-Old Economics Paradox. What Is It – And What Does It Mean Today? (NPR)

 

 

Betting On The Super Bowl Champion ...

Are you trying to get rich quickly? Do you want to know if the markets will be bull or bear this year?

Look no further than the “Super Bowl Indicator”. It has to be real; the winning percentage is high, and there’s even a Wikipedia page about it.

 

Image via NFL/Getty Images.

The theory is that a Super Bowl win for a team from the AFC foretells a decline in the stock market, and a win for the NFC means the stock market will rise in the coming year. So, for those who care more about markets than football, you’d be rooting for the Philadelphia Eagles. 

There is one big caveat (among lots of others) ... it counts the Pittsburgh Steelers as NFC because that’s where they got their start. 

If you accept that, the Super Bowl Indicator has about a 68% success rate. Sounds good, right?

Come on ... you know better.

Here are some other “fun” stock market indicators:

• January Indicator
• Aspirin Count Theory
• Hemline Indicator
• Sports Illustrated Swimsuit Indicator
• Men’s Underwear Index
• Big Mac Index

 

Back to Reality

Rationally, we understand that football and the stock market have nothing in common. We also probably intuitively understand correlation ≠ causation. Yet, we crave order, and look for signs that make markets seem slightly more predictable.

The problem with randomness is that it can appear meaningful. 

Wall Street is, unfortunately, inundated with theories that attempt to predict the performance of the stock market and the economy. The only difference between this and other theories is that we openly recognize the ridiculousness of this indicator.

More people than you would hope (or guess) attempt to forecast the market based on gut instinct, ancient wisdom, or prayers.

While hope and prayer are good things ... they aren’t good trading strategies.

As goofy as it sounds, some of these “far-fetched” theories perform better than professional money managers with immense capital, research teams, and decades of experience.

To get a better perspective, here is a thought experiment to try. 

What percentage of active managers beat the S&P 500 in any given year?

... Then, what percentage beat the S&P 500 over 15 years?

The answer is that, on average, less than 33% of active managers beat the S&P in any given year. Last year, 43% beat the Index. Even more interesting is that over a 15-year period, the numbers drop much further. Depending on who is measured, only 12% of active managers and about 5% of U.S. Equity Funds beat the S&P over a 15-year period.

Here are a couple of things to consider when you evaluate those statistics. First, market statistics represent predominantly bull market periods (and underperformance tends to spike during bear markets). Second, the statistics mentioned were for professional traders and funds (and most retail traders do considerably worse than that). Third, and perhaps most importantly, the implication is that professional traders’ “intelligent” choices often turn out worse than chance. That means something they’re doing is hurting performance (rather than helping it). 

via Gaping Void

There’s simply too much information out there for us to digest, process, rank, and use appropriately.

There will never be less data or slower markets.

The only thing you can predict confidently about the markets is that volatility and noise will increase.

There are people beating the markets — not by using the Super Bowl Indicator ... they’re doing it with more algorithms and better technology.

Let me know if you want to learn more about that.

Onwards.

Are you trying to get rich quickly? Do you want to know if the markets will be bull or bear this year?

Look no further than the “Super Bowl Indicator”. It has to be real; the winning percentage is high, and there’s even a Wikipedia page about it.

 

Image via NFL/Getty Images.

The theory is that a Super Bowl win for a team from the AFC foretells a decline in the stock market, and a win for the NFC means the stock market will rise in the coming year. So, for those who care more about markets than football, you’d be rooting for the Philadelphia Eagles. 

There is one big caveat (among lots of others) ... it counts the Pittsburgh Steelers as NFC because that’s where they got their start. 

If you accept that, the Super Bowl Indicator has about a 68% success rate. Sounds good, right?

Come on ... you know better.

Here are some other “fun” stock market indicators:

• January Indicator
• Aspirin Count Theory
• Hemline Indicator
• Sports Illustrated Swimsuit Indicator
• Men’s Underwear Index
• Big Mac Index

 

Back to Reality

Rationally, we understand that football and the stock market have nothing in common. We also probably intuitively understand correlation ≠ causation. Yet, we crave order, and look for signs that make markets seem slightly more predictable.

The problem with randomness is that it can appear meaningful. 

Wall Street is, unfortunately, inundated with theories that attempt to predict the performance of the stock market and the economy. The only difference between this and other theories is that we openly recognize the ridiculousness of this indicator.

More people than you would hope (or guess) attempt to forecast the market based on gut instinct, ancient wisdom, or prayers.

While hope and prayer are good things ... they aren’t good trading strategies.

As goofy as it sounds, some of these “far-fetched” theories perform better than professional money managers with immense capital, research teams, and decades of experience.

To get a better perspective, here is a thought experiment to try. 

What percentage of active managers beat the S&P 500 in any given year?

... Then, what percentage beat the S&P 500 over 15 years?

The answer is that, on average, less than 33% of active managers beat the S&P in any given year. Last year, 43% beat the Index. Even more interesting is that over a 15-year period, the numbers drop much further. Depending on who is measured, only 12% of active managers and about 5% of U.S. Equity Funds beat the S&P over a 15-year period.

Here are a couple of things to consider when you evaluate those statistics. First, market statistics represent predominantly bull market periods (and underperformance tends to spike during bear markets). Second, the statistics mentioned were for professional traders and funds (and most retail traders do considerably worse than that). Third, and perhaps most importantly, the implication is that professional traders’ “intelligent” choices often turn out worse than chance. That means something they’re doing is hurting performance (rather than helping it). 

via Gaping Void

There’s simply too much information out there for us to digest, process, rank, and use appropriately.

There will never be less data or slower markets.

The only thing you can predict confidently about the markets is that volatility and noise will increase.

There are people beating the markets — not by using the Super Bowl Indicator ... they’re doing it with more algorithms and better technology.

Let me know if you want to learn more about that.

Onwards.

Happy Birthday, Mom

Yesterday was my Mother's 85th birthday. 

Her children surprised her with over 60 family and friends at dinner last night. Here is a photo of us with her at the party.

My mom is quite the woman. She went to Cornell, taught Spanish Literature at Temple University, and has volunteered for countless good causes. At 40, as her kids became more self-sufficient, she decided to go to law school and become a lawyer to help those who needed it most. That doesn't even begin to capture it! For example, she still serves as a museum docent and is an active member of many clubs and organizations. In addition, after my Dad died, she chose to serve as a hospice counselor to help families going through that difficult time. After doing that for a while, she decided that she wanted to continue – but in a more positive way. So, to help make things better and easier to bear, she became a clown to bring light to people struggling. That is not a sentence I imagined writing a few years ago.

My mom also loves poems, wordplay, and puzzles.

As part of her celebration, we had everyone (OK, almost everyone) write poems for her. 

I did not write a poem (though I did write something) ... and I also chose not to use ChatGPT (or any other large language model) to help with what I wrote. 

I feel like I should explain that. What I did write, came from the heart.

If my goal had simply been to come up with a poem, I would have used ChatGPT or one of its competitors. The truth is, many people at the event did exactly that, and I was surprised at the quality of their output.

With that said, there's something meaningful about the process of thinking deeply about something (in this case, my Mother) and choosing which things to highlight (or set aside), what to poke fun at, and which things to express gratitude for. The act of thinking and writing is valuable ... separate and apart from the output generated.

The same is true for your life as well. Being and Doing are both important. 

Your identity and strategies combine to create the life you are living. Said a different way, the things you choose to focus on (and what you make them mean) shape your perspective and guide your actions. 

That is also why it's vitally important to consciously create a compelling future that calls you forward (and keep score by tracking your progress in ways that resonate with your values).

Here is a small excerpt from my love note to my Mother.

The Golden rule says “Do unto others as you would have them do unto you.” But sometimes, it’s important to remember to be as kind to yourself as you are to others.

As I think about you and what I wish for you, Mom, it’s that you’re as kind and understanding to yourself as you’ve been to those around you.

It’s important to recognize the progress you’ve made with the good you’ve done, rather than what could have or should have happened - or how many things you still feel the need to do.

I think one of the most useful definitions of “intelligence” is that it is the ability to get more of what you want - and for you, Mom, I think that is a sense of happiness, contentment, and purpose. In your words - a Happy Heart.

Happy Birthday, Mom … and many more! 

I suspect we all know the power of purpose. With a big enough WHY, the HOWs don't seem to matter.

The average age at this party was probably 80 – and at least one of them was 100! Think how important it is for them to have a sense of purpose and accomplishment!!

But if it is important for them ... it is probably more important to you because of something I call The Time Value of Life (which we'll discuss next week).

Here Are Some Links For Your Weekly Reading - January 12th, 2024

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

Lighter Links:

• Incarcerated Firefighters Play Key Role in Battling Los Angeles Wildfires. (Particle)
• Transition 2025: A Report the Incoming Trump Administration Should Read. (CFR)
• What Happened to Justin Trudeau? (RollingStone)
• How OpenAI’s Sam Altman is Thinking About AGI and Superintelligence in 2025. (Time)
• AI Could Crack Unsolvable Problems — And Humans Won't Be Able to Understand the Results. (LiveScience)

Trading Links:

• The Insurance Apocalypse – Fire, Money, and Who Gets Burned. (TheBulwark)
• US Top Court Leans Towards TikTok Ban Over Security Concerns. (BBC)
• VCs Say AI Companies Need Proprietary Data to Stand Out From the Pack. (TechCrunch)
• Wall Street Just Got Another Sign that Dealmaking is on the Rebound. (Finance)
• Dow Sees Worst Start to a Year Since 2016 as Fed Rate-Cut Hopes Fade for 2025. (MarketWatch)

How'd Markets Do In 2024

At the beginning of 2024, I asked the question - how did markets do in 2023?

It makes sense to ask the same question as we start 2025. 

Before I get started, it’s worth stating that the market is not the economy ... but with Trump about to step into office, I know people are wondering. 

I still think about the often-quoted quip “It's the economy, stupid” - coined by James Carville, a strategist in Bill Clinton’s successful 1992 U.S. presidential election against incumbent George H. W. Bush.

2022 was the worst year for the U.S. stock market since the 2008 financial crisis.

2023 was much better, but much of the gains came in concentrated sectors.  

2024 saw nearly every sector posting gains - driven primarily by AI enthusiasm and a robust U.S. economy. 

To help you get a sense of 2024 returns, VisualCapitalist put together a few helpful infographics.

 

via visualcapitalist

66% of companies on the S&P ended up in positive territory this year. The S&P also had its best two-year stretch since the late 90s. 

Communication Services usurped IT’s #1 spot, driven primarily by Meta & Google. Strong consumer spending and digital ad revenue brought ad spending to almost $400 billion. 

Materials was the only sector to see negative returns, hampered by China’s economic slowdown and increased interest rates. 

Here is a more global look at return by asset class.

 

via visualcapitalist

Driven by that end-of-year run, Bitcoin surged to all-time highs, and gold also saw its best performance in 14 years. Meanwhile, bonds suffered heavily amid reflationary concerns and a potential widening deficit under the Trump administration.

In 2024, I predicted a brief market correction, blamed on various geopolitical instabilities and partisan weaknesses, followed by a long and steady push higher as the November elections approached.

How did that prediction hold up? I'd say pretty well. 

On one level, I try not to think about or predict markets (because I know better). On another level, sometimes I can’t help myself ...

Part of me is so bullish about AI (and its impact on other things) that it’s hard to maintain objectivity. With that said, I think we’ll have another decent year. However, I expect increased volatility and noise.

What do you expect for 2025?

Do you think the continued investment into generative AI will impact these trends?

Will cryptocurrency continue to explode? What scenarios do you think have the potential to be force multipliers?