Everyone from Bruno Mars to Donald J. Trump wants to be a mere billionaire “so freakin’ bad.” Heck, even the current Mega Millions Lottery has become a misnomer with the current jackpot for this US game of chance standing at $1.6 billion for the drawing this coming week. If CAIA orange is the new black, we can certainly declare (with conviction) that a trillion is the new billion. Needless to say, in the world of high finance, these numbers don’t seem to impress nearly enough.
Quantitative strategies recently joined the trillion-dollar club as measured by aggregate global assets under management. While it might be a bit unfair to generalize here, these are basically strategies that rely on algorithmic-based trading decisions in either one market or hundreds around the world and can have leveraged exposure to the likes of currencies, rates, equity markets, and commodities. Investment processes are usually based on models developed by very smart and well-educated PhD’s and have been backtested, but represented to be free of over-fitting, data mining, or other hindsight biases, or at least that is what is said during IDD discovery.
The advent of big data and machine learning has continued to feed this beast. The average smartphone has well over a dozen sensors, Alexa and Siri likely never really sleep, and there seems to be a camera or a drone everywhere these days. Throw social media into the mix with the millennial penchant to chuck personal privacy out the window, and you can quickly see how fast the pile of structured and unstructured data has grown. This data is pure gold for the quant, and the less structured it is the better. At same time, the cost of data storage has shrunk considerably, and quantum computing continues to show the promise of solving the unsolvable.
In his more lucid days, Elon Musk said it is not the car, but the factory that is the product. No truer words have been spoken when it comes to the Tesla, but also to the quant strategies where the investment in the algorithm, the computing infrastructure, and the related execution capabilities are the product. None of these component parts has a conscience or behavioral biases mostly because they are not human, allowing hundreds of decisions to be made rapidly and simultaneously absent equivocation.
The market cap of the Russell 3000 stocks stands at about $30 trillion and equity exposure is just one factor looked at by these quant models. Through that lens, $1 trillion does not sound like a lot, but like many things in life (including life itself), there are limitations. The risk and frequency of flash-crashes is likely higher; the algorithms might be different and the data feeding them could be nuanced, but systemic weakness in certain parts of the market will likely be sensed by the soulless machines in unison and that will make for a tough trading session or two.
These quant strategies are likely the new normal and the future of investing, and even the more fundamentally-based investment processes have co-opted the term quantimental to describe how they invest. As investors, we need to continue to up our game when it comes to financial literacy, education, and certainly professionalism for those at the top of the pyramid. CAIA Association continues to lean into all of this with our ethics-based curriculum for alternatives, including many of the leveraged quant strategies in the market today. At the same time, exploration is actively underway, led by us, for a new credential to underscore the need for professionalism as data science moves even deeper into the investment process. This discovery will go even further this week as CAIA brings together a group of our Members in the CIO suite along with some SMEs at the Global Absolute Return Congress where we look to continue to keep pace with the rapidly changing investment landscape.
Seek diversification, education and know your risk tolerance. Investing is for the long term.
Written by Bill Kelly courtesy of CAIA Association.