The process of coding financial market trading systems is fascinating , but they never seem to last very long and their performance is never very consistent.
Quantopian is an interesting outfit. For a number of years they have worked hard on setting up an extremely impressive on-line back testing platform for the US stock market. They have sophisticated software open for all to use and give access both to price data and fundamental information (such as debt levels and earnings for corporate America).
They have a most impressive series of lectures and tutorials on everything you might need to take up their challenge.
They are backed by Steve Cohen, the US hedge fund manager said to be the model for Bobby Axelrod in the hugely popular and amusing TV series Billions.
As per Wikipedia:
Steven A. Cohen (born June 11, 1956) is an American investor, hedge fund manager, and philanthropist. He is the founder of Point72 Asset Management and S.A.C. Capital Advisors both based in Stamford, Connecticut.[3] He has an estimated net worth of US$14 billion as of March 2018.
So what is the “Challenge”?
Quantopian seek to outsource system design to their 200,000 users and offer prizes and allocations for the few who manage to devise a pleasing algorithm.
And yet here is the rub with financial market algorithms:
The further out-of-sample it gets, the variability of expected returns would increase.
How very paradoxical and typical of systematic financial market trading. A bunch of intelligent people go to extraordinary lengths to produce Alphalens, Zipline and Pyfolio.
The stated aim is to produce market neutral algos which fare well (smoothly) in up and down markets.
To that end various in/out of sample routines are suggested to make sure that will continue to be the case. It is proposed that fundamental factors should be used as predictors. What more sensible sounding scheme than that? Over the long term, earnings growth and a strong balance sheet are all that count. Without those a stock will eventually wither and die. With those factors a stock will prosper.
And yet it is still suggested that “The further out-of-sample it gets, the variability of expected returns would increase.”
Are there no constants in financial markets? Nothing we can count on? Are we eternally doomed to design complex systems to fail? It would seem so. A system will have its time in the sun and must then be consigned to the dustbin. That is not at all what was envisaged. The whole idea of market neutral is that it should survive and prosper. Equal dollar amounts of long and short positions. Equal or at least limited exposure to any one sector or trading style. A carefully curated universe of stocks (well that at least has to change day by day).
Do we care? Should we care ?
Well we humans are such short term animals probably not. As long as our algo lasts long enough for us to fill our pockets on fees we should be more than happy.
Should we care to ponder immortality in the context of trading and investment we might be forced to adopt a different and less fancy approach. Who is to say that Morningstar sector definitions have much validity today let alone tomorrow? Remember how the staid telephone utility companies suddenly morphed into debt crippled monsters back in the early 2000s? And the coded definitions of momentum, value or other styles. Do they hold? Are they universal?
Am I a deep cynic? A Jeremiah? If so, do I have reason to be or am I just inadequate at finding the golden key to systematic immortality?
Weltanschauung 