Can Quants beat the Markets?

Weekends are great : They give you an opportunity to network and meet your old friends!!

Last weekend, a Saturday night, quiet place in Koregaon Park, a glass of beer and an old friend who manages $100 million active fund, provided a great backdrop to unwind. But he asked me something I honestly could not believe! My friend was asking about right data science course to enroll. He exclaimed, “if I don’t learn how to do quantitative analysis I’m not going to have a job in two years!.”  “Re-skilling was a phenomena reserved for technologists!” So I thought until then !!

That got me thinking! Will the Dooms day scenario of ‘Machines taking over Man’ was onto us? Will the financial world that has direct dealings in money lead the way for this phenomena? On one hand you have the power of super computing merged with best of the minds that world’s largest Hedge funds can employ, on the other hand you have a humble trader with access to his basic trading toolkit. And you thought the answer was clear?

Most would imagine that quants would beat the individuals hands down?

God!! Has fairness taken a hike? As disappointed as I was feeling, I decided to do some research. After all, we live in the world of data driven management!! 

The more I read, the more I was elated. After all, it seemed like the invisible hand of God was helping the little guy on the street !

Investment industry sources estimate that quant funds managed more than U.S.$1 trillion by the beginning of 2019. However, barring very few exceptions, most pure quant funds seem to be under performing the passive ETF strategies.

What explains this?

To understand this, we must first understand how Data science works – at a high level.

Most machine learning and deep learning algorithms work on the principle of using the “learning” data to develop

models that get tested and refined using the test data. Thus more the data, more the refinement, better is the accuracy to predict the output.

If you are developing an algorithm to train a driver-less car, the more it drives, the more it collects data about environment it operates in, better “skilled” the car becomes in driving. Thus it can do a better job of driving than a human being….at least someday..at least in theory! We all know the story of Garry Kasparov, World chess champion losing the famous clash with IBM’s deep blue in a series of 6 matches.

Theory of Reflexivity @ Work

This is where financial data (price, volume, economic activity, GDP, etc.) defers from other data. Most eloquently explained by George Soros – the legendary hedge fund manager.

Reflexivity postulates that the data interacts with current world to change the course of future!  Heavy stuff? Let’s explain this with 2 concepts – objective reality and subjective reality.

Objective reality is unquestioned truth. Temp rose to 30 degrees today. No one can question it.

Subjective reality on the other hand is affected by what participants think of them. Put simply, what market participants think of market affects market and how market moves affects what participants think of it!!

Reflexivity makes the job of finding algorithm that works over a long period of time almost impossible!!

Statistical frailty - Finding a relationship that may not exist

The idea behind many quant strategies is that some variable of interest – say, a “rate of change” of price – can be modeled as some function of available data. The function of the data could be something as simple as a factor regression model or something as complex as a many-layered deep learning computation.

Thus it makes an assumption of finding the price based on finite number of input variables. However, markets have proven time and again that it is a complex concoction of human emotions, financial data, geo political news and many more. As kids, I am sure, you played with a kaleidoscope. That fascinating toy which created different combinations of glass every time you gave it a little twirl. Markets are like a kaleidoscope driven by thousands nah.. millions of data points. This makes it difficult to be modeled!!

Arbitrage – the cancer that kills “Alpha”

With hundreds of PhDs at your disposal, millions in investment dollars and vast computing power, if someone cracked the code, imagine what happens? Guess what, they probably get to enjoy a very short window of success.

After all, competing investment banks / Hedge funds also have access to same tools, same people and same deep money pools looking to make Alpha on their investments.

Thus Arbitragers come in swiftly to kill the Alpha. They develop similar strategies and with every additional $ chasing same window of opportunity, soon the window diminishes in front of your eyes.

Conclusion

Traders, Investment Banks, Hedge Funds – all have been chasing the “Holy Grail” – the Quant algo that will give them consistent Alpha at a reasonable risk. However, Markets are more complex than what most can comprehend. Reflexivity, Statistical frailty and Arbitrage make it extremely difficult if not impossible to get a sustainable advantage over any reasonable period of time!

Or so it seems..till some new advance in technology will make it happen.

After all, till Eliud Kipchoge ran the marathon under 2 hours, no one thought it was humanly possible !