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.
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.
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.
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.
This post seems like it is about football … but it is really a playbook of things we can do in business.
What Can Business Learn From Football Teams?
If you get a chance to watch an NFL practice … I highly recommend it. It is an awesome experience and opportunity for a businessperson.
Each time I've watched a practice session I've come away impressed by the amount of preparation, effort, and skill displayed.
The Cowboys' coach is Jason Garrett. He is detail-oriented and intellectual. His pedigree … he is a Princeton graduate who played quarterback in the NFL.
During practice, there's a scheduled agenda. Practice is broken into chunks, and each chunk has a designed purpose and a desired intensity. There's a rhythm, even to the breaks.
Every minute was scripted. You could tell there was a long-term plan … but, there was also a focus on the short-term details (many details).
They alternate between individual and group drills. Moreover, the drills run fast … but for shorter time periods than you'd guess. It is bang-bang-bang – never longer than a millennial's attention span. And they move from drill to drill – working not just on plays, but the skillsets as well (where are you looking, which foot do you plant, how do you best use your hands, etc.).
They use advanced technology (including advanced player monitoring, bio-metric tracking, and medical recovery devices … but also things like robotic tackling dummies and virtual reality headsets).
They don't just film games, they film the practices … and each individual drill. Coaches and players get a cut of the film on their tablet as soon as they leave. It is a process of constant feedback, constant improvement, or constant renewal.
How you do one thing is how you do everything. So, they try to do everything right.
Pro football is one thing. College football is another. But, even in high school, the coaches have a game plan. There are team practices and individual drills. They have a depth chart, which lists the first, second, and third choice to fill certain roles.
The focus is not just internal, on the team. They focus on the competition as well. Before a game, the coaches prepare a game plan and have the team watch tape of their opponent in order to understand the tendencies and mentally prepare for what's going to happen.
During the game, changes in personnel groups and schemes keep competitors on their toes and allow the team to identify coverages and predict plays. Coaches from different hierarchies work in tandem to respond faster to new problems.
After the game, the film is reviewed in detail. Each person gets a grade on each play, and the coaches make notes for each person about what they did well and what they could do better.
Think about it … everyone knows what game they are playing … and for the most part, everybody understands the rules, and how to keep score (and even where they are in the standings).
Imagine how easy that would be to do in business. Imagine how much better things could be if you did those things.
There seems to be a rising movement of anti-intellectualism and homegrown "experts" believing they know more than experts who have spent their careers creating informed opinions based on textbooks, peers, and experience.
"I saw it on facebook", "I googled my symptoms and it's definitely Lupus", "That's just a hypothesis, there's no proof…"
It is increasingly difficult for people to discern what's real from what's fake, and it's undermining the authority of experts. \
Experts make mistakes, and scientists and doctors are constantly learning, but having well-informed experts who can challenge those mistakes and create solutions. We wouldn't have the world today without that established knowledge base.
So how do you become better informed?
First off, acknowledging expertise, and searching for credible sources is paramount. Researching dissenting opinions and sources from the opposite side of the spectrum can also provide insight.
If most the news sources you follow are liberal-biased, don't neglect to research the other side of the spectrum and vice versa. Otherwise, you can end up in an echo chamber. When looking at studies or articles, be aware of fallacies and learn to spot bad science.
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).
