I recently came across a paper that claimed to explain asset returns with a single factor. “Here we go again”, I thought to myself. “Another group of people who want to modify the CAPM so that it ‘explains’ financial markets. What a waste of time.” But then my eye saw the magic words:
As an average-at-best math student myself, I think some or the disconnect lies in the arcane language:
"The new paper I came across does something similar. The researchers use polynomial functions with degrees as low as four to approximate the recent performance of a wide variety of asset classes. Then they test if this fitted fourth-order polynomial is better at explaining the cross-section of returns than existing finance models."
What exactly does "explaining" mean in this context? It's appears to be a bit like "tracking error", which really isn't a "mistake" as much as an excursion, but the word never quite shakes its normal pejorative meaning. Perhaps it's the same for "explaining", which usually means "helping people understand the underlying fundamental drivers" but in a mathematical context appears to mean "account for" or "measure".
I think people with long careers in economics and finance have simply seen too many examples of mathematical attempts to "black box" financial markets which blow up spectacularly when exposed to real life. "Here's Dr. X and his staff of rocket scientist PhDs and their can't-miss quantitative trading model" ... which then systematically underperforms all those Oxbridge classics and music majors in Mayfair for eight straight years on the trot, and then fails completely when -35% market corrections such as the WFC and Covid occur. Lots of burnt fingers result in people inevitably reverting to more "fundamental" approaches, because even if they're wrong and underperform, at least they have the excuse that they tried hard by "working at it" ... rather than sitting around waiting for a set-and-forget quant strategy to work. And if the quants start tweaking their model on the fly, then the "fundamental" crowd squawks that that's really "active management" hiding behind a whiteboard full of Greek letters. Renaissance is then inevitably brought up https://en.wikipedia.org/wiki/Renaissance_Technologies , and the battle continues!
I genuinely hope you're onto something with this new approach, and can quit your day job ... but you just shared it with the world, so how soon berore the excess returns are arbitraged out? ;-)
Economists and fund managers certainly like to use quasi-mathematical jargon to try to sound smarter than they really are: Alpha and beta become "portable alpha" and "smart beta". "Uncorrelated inputs". "Black swan event". "Idiosyncratic risk". "Heteroskedasticity". "Efficient frontier". Be sure to use these with 90% confidence on (at best) around 10% knowledge!
If those fail, then just start making stuff up; my particular bête noir is "negative growth" to mean "decline", but "stored performance" to mean "losses" is a close second!
As an average-at-best math student myself, I think some or the disconnect lies in the arcane language:
"The new paper I came across does something similar. The researchers use polynomial functions with degrees as low as four to approximate the recent performance of a wide variety of asset classes. Then they test if this fitted fourth-order polynomial is better at explaining the cross-section of returns than existing finance models."
What exactly does "explaining" mean in this context? It's appears to be a bit like "tracking error", which really isn't a "mistake" as much as an excursion, but the word never quite shakes its normal pejorative meaning. Perhaps it's the same for "explaining", which usually means "helping people understand the underlying fundamental drivers" but in a mathematical context appears to mean "account for" or "measure".
I think people with long careers in economics and finance have simply seen too many examples of mathematical attempts to "black box" financial markets which blow up spectacularly when exposed to real life. "Here's Dr. X and his staff of rocket scientist PhDs and their can't-miss quantitative trading model" ... which then systematically underperforms all those Oxbridge classics and music majors in Mayfair for eight straight years on the trot, and then fails completely when -35% market corrections such as the WFC and Covid occur. Lots of burnt fingers result in people inevitably reverting to more "fundamental" approaches, because even if they're wrong and underperform, at least they have the excuse that they tried hard by "working at it" ... rather than sitting around waiting for a set-and-forget quant strategy to work. And if the quants start tweaking their model on the fly, then the "fundamental" crowd squawks that that's really "active management" hiding behind a whiteboard full of Greek letters. Renaissance is then inevitably brought up https://en.wikipedia.org/wiki/Renaissance_Technologies , and the battle continues!
I genuinely hope you're onto something with this new approach, and can quit your day job ... but you just shared it with the world, so how soon berore the excess returns are arbitraged out? ;-)
“Mathematicians are like Frenchmen: whatever you say to them they translate into their own language and forthwith it is something entirely different.”
― Johann Wolfgang von Goethe
Economists and fund managers certainly like to use quasi-mathematical jargon to try to sound smarter than they really are: Alpha and beta become "portable alpha" and "smart beta". "Uncorrelated inputs". "Black swan event". "Idiosyncratic risk". "Heteroskedasticity". "Efficient frontier". Be sure to use these with 90% confidence on (at best) around 10% knowledge!
If those fail, then just start making stuff up; my particular bête noir is "negative growth" to mean "decline", but "stored performance" to mean "losses" is a close second!
OK. So what happened to the FFT model? I'm reading your paper now. Thanks for this article and the references. Best, j
Nobody paid any attention to it, so I couldn't be bothered to continue updating it.