How to Monetize Your Algorithmic Trading Experience

It costed you blood, sweat and tears to become an algo trader… how did that play out for you? If the answer is anything other than “I don’t ever need to work again”, then you need to read this. By Luis Molina & Julian Molina Learning to trade is a daunting task. But I don’t need to tell that. you You’ve been there. You know it. You invested countless hours, devoured books and melted your corneas staring at the screen. Lost a bunch of hair and ran out of fingernails to bite. Your keyboard is worn out from the relentless coding — and still — no life-changing event has materialized so far. You’ve had your good runs and your bad ones. Enough of the good ones to keep you going, for sure… but still, you feel you haven’t nailed it yet. You’ve had your moments and know for sure you’ve climbed the steep learning curve, but the bank account is still nowhere near where you’d dreamed it would be. aha Guess what? That’s how it’s supposed to be! Yes, you heard me right. You were dazzled by the few success stories in blogs and forums and thought you were being left behind, but the truth is it’s not true. Very few individuals have life-changing experiences with trading. You are in the vast majority group. The 99%. The truth is that any single person, no matter how hard she trains, no matter how smart she is, no matter how good with numbers or code she becomes… after all the sacrifice, time and money invested, still has very slim chances of consistently outperforming the market in the long run. Beating the markets is no piece of cake. That is one of the reasons why , tracking indexes through ETFs. almost half of investable money is in passive investments That is the reason why . active managers are slowly becoming an endangered species Not even the big boys with buildings full of quants and many zeros in AUM can offer anything close to reliability, so why would you? Then… should you just drop it? Forget about it? Throw all your effort and hard-earned know-how down the drain? Hell no! The costly toolbox you carefully assembled in your brain can certainly be put to good use. You’ll just need to change your strategy. Stepping Out of the Box We have been working on something for some time. We came up with a theory of why no trading intelligence in investment firms has ever evolved enough to attain a dominant position in the markets. The central thesis is that, despite the fact that companies acquire significant amounts of talent, they fail at organizing human and machine resources in a way that would yield the best possible results. Put it bluntly, people within investment firms work in silos. Be it due to incentives, workflows, segmentation of incumbencies or organizational requirements, the point is — save for a few exceptions — there is very little collaboration within firms. In fact, small teams and sometimes even individuals work in absolute secrecy. Yes, secrecy. Secrecy is a given in the investments industry. No one wants their neighbor to know what they are up to. No one wants their algos to fall in someone else’s hands. This industry-wide approach is probably founded in the belief that secrecy gives players an edge against other market participants. There’s also the widely accepted idea that algorithms lose performance if used too broadly. Don’t get me wrong… I’m not saying there is a flawed reasoning behind that line of thought. What I’m saying is there surely are other ways around those concerns, and that if other solutions were found to address them, then secrecy would no longer be a requirement in the system. So, again… guess what? Yes, we did find other solutions. A Global Trading Intelligence We invented a framework to disrupt and outperform the reigning algorithmic trading model and are advancing on its implementation. In a nutshell, our model is about a global crowd creating trading algorithms and putting them to compete for prize money. So far so good, right? Now, please, brace for impact… After each competition ends, algorithms are open-sourced within the community so that the crowd forks and improves the best algos and puts them back to compete, over and over again. This is the core of our model. Now, breathe. Take it easy. It’s not blasphemy. If it didn’t sink in yet and you are still struggling with conflicting thoughts about and being used in the same sentence, then take another deep breath and follow my reasoning… It’ll come to you… Just open your mind… trading open source Open source and open collaboration is the most efficient method to foster the advancement of knowledge. No need to believe . me It actually is scientifically proven, pun intended. The scientific community has been open sourcing research results, findings and breakthroughs for centuries. Coupled with advancements in communications, , in what looks pretty much like exponential growth. the result of the sharing model is that scientific output is currently doubling every 9 years Segmented growth of the annual number of cited references from 1650 to 2012 Where do you reckon humankind would be had people of science always worked in silos? How do you imagine our world would look like had people always craved to keep knowledge for themselves? Hunting and gathering? The Stone Age? Well… the same reasoning applies to active management of investments and algorithmic trading in particular. Investment firms are in the Stone Age of Trading because they work in silos. Companies are consumed in an arms race to produce the better algos within closed doors to gain an edge over other firms doing exactly the same thing. They are trapped in a backward system; a path that leads to nowhere. The Era of Superalgos Our vision of the future of trading is radically different: we envision a superior trading intelligence evolving within an open global collaboration of humans and machines, at the service of all people. In our model, competitions are organized as a multi-layer league system designed to drive evolution towards trading big capitals. The crowd self-organizes in teams, who need to win in minor leagues to move to higher leagues. The bottom leagues run short competitions, with minimal capital requirements and relatively small prizes. Higher leagues have longer competition periods, higher capital requirements and offer significant prize money. Teams winning a league get enough prize money to cover the capital requirement of the next league, affording mobility to teams who perform well. A big-enough crowd working and playing under this model will produce such diversity of strategies and such accelerated evolution that the prompt replacement of algos that lose their edge is guaranteed, negating the two main concerns embodied by the culture of secrecy of the current system. Moreover, a big-enough crowd in open collaboration will certainly produce a superior intelligence that will outperform and disrupt the current closed, backward model. The is building a Trading Intelligence Marketplace on which investors of all calibers will rent the crowd’s collective trading intelligence to manage their assets. Superalgos project In our model, the crowd owns the business. There is no middle man. Algo-makers decide on the fees they charge for the use of their algos, adding incentives on top of fun competitions and prize money. A few market participants like Quantopian, QuantConnect or Numerai are toying with the notion of outsourcing algos and predictions from crowds; however, they too keep their crowds working in silos, as there is literally zero collaboration among contributors. Needless to say, their crowds do not own the business either. At the end of the day, Superalgos should become a dominant player in the markets, with a global legion of amateur and professionals who own the business working on a zero-cost basis, producing a superior and ever-evolving trading intelligence, with verifiable and reliable top-of-the-market performance. What’s In It for You By now, you’ve probably found a few good reasons why you would like to be a part of Superalgos. However, there is more to what you may have deduced so far… The technology required to run the Superalgos model has been in the making for over a year, and it’s still in its infancy, with built by the Core Team and a few developers in the extended Dev Team. a working MVP in alpha stage Remember the crowd building algos owns the at the Trading Intelligence Marketplace? rental business Guess who owns the business? system maintenance That’s right: Dev Teams. We are distributing the development and maintenance of the system on a global network of Dev Teams. Being an open project, we strive to create a highly resilient body of talent in charge of both producing and maintaining the technology required to run the project. If you bring your algo-trading experience in and build one of the missing pieces of the puzzle, you get a share in the business of maintaining the platform, which means getting a share on the fees paid by algos running on the platform, for as long as you keep maintaining your module. Most details on how to come onboard Superalgos as a developer are covered in the page in our website. Join the Dev Team If you liked this piece, you might also like these other pieces about related topics: Superalgos & The Trading Singularity “One day in the future, a trading intelligence capable of outperforming every other entity at the markets will emerge. Both humans and current algorithms will be surpassed by Superalgos.” Superalgos: Building a Trading Supermind “A supermind of humans and machines thinking and working together, doing everything required to maximize the group’s collective intelligence so as to minimize the time needed for superalgos to emerge is being built right now.” A bit about me: I am an entrepreneur who started his career long time ago designing and building banking systems. After developing many interesting ideas through the years, I started Superalgos in 2017. Finally, the project of a lifetime. Follow Superalgos on Twitter or Facebook ; or visit us on Telegram or at our web site .