Seemingly everywhere I go, someone asks me about Bitcoin.
Clearly, there are speculators and day traders banking coin.
I am a little surprised by how fast it captured the cultural zeitgeist.
Here's a clever spoof … worth watching.
AwakenWithJP via Youtube
I'm sure we'll talk more about Bitcoin … but, more importantly, Blockchain (which is the technology that Bitcoin and other cryptocurrencies were built upon).
I am currently investigating and planning how we'll use Blockchain.
Onwards.
Here are some of the posts that caught my eye recently. Hope you find something interesting.
Human's can't do a lot of things. Honestly, the fact that we're top of the food-chain is pretty miraculous.
We're slow, we're weak, and we're famously bad at understanding large numbers and exponential growth.
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.
via Diamandis
Human perception is linear. Technological growth is exponential.
There are many examples. Here is one Diamandis calls "The Kodak Moment."
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.
Tech and A.I. 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.
Onward!
I just saw the new Star Wars with my family.
It's a bit crazy to think about what percentage of my life occurred since the original came out
I can still remember watching the first one.
BTW, I'm not 60 yet … but, I am pushing double nickels.
Here are some of the posts that caught my eye recently. Hope you find something interesting.
Here are some of the posts that caught my eye recently. Hope you find something interesting.
There's a paradigm shift happening in trading.
Today's investors have access to data and information that would have been unheard of 10 years ago … and unfathomable 20 years ago. In the past, investors relied on information and experience from their real lives, from counterparties, and from fastidious attention to CNBC and stock tickers.
However, fundamental discretionary traders account for just 10% of today's trading volume. Quantitative investing based on machine intelligence and algorithms is the new normal.
While the games, the rules, and the players have all changed, the goal hasn't … more alpha … more money … more reliably.
What's Changed?
Algorithmic trading isn't new, but there is a shift in who's making the algorithms. For example, you can crowdsource development through Quantopian … or let machines do the heavy lifting through A.I.-based firms like Sentient.
Some argue that artificial intelligence is unable to generate significantly different results because "analyzing more and more data results in increasingly similar strategies".
But I'd argue that's only true if you look at the same data, the same way.
The Future of Trading
One of the reasons A.I. is a great option for trading is that it takes away the human element of fear, greed, and discretionary mistakes.
Sentient's founder says:
"For me, it's scarier to be relying on those human-based intuitions and justifications than relying on purely what the data and statistics are telling you." – Babak Hodjat
In addition, people tend to get similar results because they do things similarly. As A.I. matures (and more researchers become better versed in what's possible) solutions will evolve.
It won't be a Ph.d. writing an algorithm … it will be machines and code trying unthinkable combinations and finding edges that otherwise would remain invisible and unused.
Currently, most people train their algorithms on markets, or with human intervention, but there are more data sets that can be used to build more robust models.
Alternative Data
Alternative data, to most, means tracking Twitter and Facebook sentiment, but confining your definition to that limits potential alpha.
New sources of data are being mined everywhere, and are letting investors understand trends "before they happen".
For example, mobile devices, low-cost sensors, and a host of new technologies have led to an explosion of new potential data sources to use directly for predictive insight or indirectly to help improve models.
In addition, private company performance, logistics data, and satellite imagery are becoming popular data sets in a data scientist's alpha creation toolbox.
There are often concerns about the cost and completeness of these datasets, but as we get better at creating and using them, both will improve.
Here is a chart of alternative data sources.
via CBInsights
Finding more ways to train algorithms on new data can help traders once again find an edge on their competition.
The thing about "sustainable alpha" is that while one might be able to achieve it, you can't expect to have it doing the same thing everyone else, or that you've always done.
Markets change, and what worked yesterday won't necessarily work today or tomorrow. Trading is a zero-sum game, and as we move toward the future, this only gets more apparent.
Behavioral Game Theory shows that human choices don't necessarily reflect the benefits they expect to receive. That's no longer the case with algorithms.
For more on Big Data and its potential, here's access to the full panel discussion I participated in recently at The Trading Show in New York.
via YouTube
Let me know if you have questions or comments. Thanks.
Here are some of the posts that caught my eye recently. Hope you find something interesting.
I'm excited … because I've been at Joe Polish's Genius Network Annual Event this weekend.
Genius Network is a business group that also serves as an advisory board, counselor's office, and idea factory.
It brings brilliant minds and industry transformers together in a forum focused on innovation, creative disruption, and possibility.
Peer groups, like this, help you set (and raise) standards.
They help bring new capabilities, but also new possibilities, new found energies and a reconnection to your purpose, mission, and values.
This is a great place to meet extraordinary people.
Buck Joffrey is one of them. He is a doctor, an international best selling author, member of Genius Network, and host of WealthFormula (which is a podcast where he educates professionals on how to build lasting wealth).
Buck recently interviewed me for WealthFormula. We talked about old-world trading versus new-world trading … and where I think A.I and Machine Learning have the best opportunities to add alpha and help investors make and keep more money.
You can listen to it below (or subscribe to his podcast on iTunes, Android, or RSS).
The world's super-rich hold the greatest concentration of wealth since the turn of the 20th century.
According to The Guardian, there are now 1,542 billionaires in the world. Meanwhile, last year, the collective wealth of billionaires increased almost a fifth – to six trillion dollars. For context, that's more than almost every country's GDP… except the top 4 (China, United States, India, and Japan).
The first Gilded Age was established by monopolies in US rail, oil, steel, and banking.
Income equality was extreme with the Vanderbilts being worth $185 billion due to his railroad empire, Andew Carnegie being worth $309 billion due to his steel empire, and John D. Rockefeller built an Oil empire (it controlled about 90% of the American oil business) that netted him $336 billion.
It's interesting to look at the transition from the richest in the late 1800's to the richest in 2017 … the transition from industries like Steel, Oil and Rail, into companies like Amazon, Microsoft and Walmart.
While there are more "super-rich" today than before, our wealthiest individuals don't compare to before. Jeff Bezos is worth approximately $90 billion, Bill Gates is worth approximately $90 billion, and the Walton family has a combined net worth of about $149 billion. You can check out a full list of the top 10 richest people here.
Let me know when your name makes that list. I'll do the same.
Debt often enables governments to run smoothly. But sometimes you can have too much of a good thing.
The US recently passed $20 trillion in debt for the first time. To put that in perspective, I am going to reference an article I wrote in 2011 … when the debt was approaching $15 trillion.
Here is what the $15 trillion U.S. debt looked like when it is piled up in stacks of $100 bills.
To put it in context, do you see the tiny tractor trailer? Squint, and you can see the barely visible human in front of it.
via WTFNOWAY
The United States has a net wealth of approximately $300 trillion. Nonetheless, the statistics are sobering.
Take a look at the list of country debt as a percentage of GDP. Apparently, Japan has embraced its inner borrower.
According to the World Economic Forum, if the Japanese wanted to pay off their national debt, each individual would owe approximately $90,345. For comparison, US citizens would owe $61,539 a person.
It's also worth noting that lower debt levels don't translate to safety on a global scale. Yugoslavia had very low government debt until its breakup.
If you want to see an updated, interactive version of the U.S. Debt Clock, just click here. It is worth spending a little time to watch the pace the numbers turn.
