Numerous smart people are foreshadowing a sea change in quantitative finance. This change has big alpha potential for the mathematically inclined, and will result in a much higher technical bar for those trying to learn algorithmic trading. And, pity those buy and hold investors.
Different folks are converging on this change in different colloquial ways. Derman has an upcoming book criticizing financial over-modeling. Taleb has been writing books on imprudent mathematical assumptions for many years. Haug has debunked Black-Scholes in several papers. Bouchaud and Potters have spent a decade popularizing econophysics by questioning classic dogma. Meucci wrote a book and has been teaching it for several years. Sornette is inventing quant macro by tackling crash modeling and prediction. Even big bank folks are jumping in, such as recent papers by Petrelli et al.
Despite different words, all boil down to the same fundamental change: convergence of the and worlds. The financial crisis punctured the pristine mathematical world of risk-neutrality, laying seeds for bi-directional synergy with the real world .
For those unfamiliar, and are shorthand for two divergent finance traditions (see Meucci 2011). is the buy-side world of portfolio management, including retail, prop, and most of the fund world (as well as much of pension and insurance). is the sell-side world of derivatives, best exemplified by exotics (and structured products, to a lesser extent). Historically, the two worlds could not be more different (e.g. compare mathbabe with Falkenstein).
To grossly and unfairly characterize their historical traditions: is former physicists working on mathematically beautiful PDEs and stochastic calculus (hence similarity to statistical mechanics and related fields), driven by traders looking to book P&L and offload risk; are portfolio managers building investment models by applying fairly elementary statistics and optimization primarily from the Markowitz / Black-Litterman tradition. Notably absent from both worlds are descendants from old exchange locals who live in the absence of mathematics: spread, execution efficiency, and technology (including pure-play HFT).
The sea change is these two worlds are beginning to increasing blur, along with it the migration of alpha.
The first blurring was statistical arbitrage. Arguably the big quant funds are famous precisely because they recognized this – convergence and built corresponding large-scale modeling and execution expertise. In the past few years, this convergence is beginning to accelerate: take a few minutes to skim Wang 2009 and Petrelli 2010. Quantivity has never read more overtly confrontational academic papers (by big bank folks, no less), nor more use of italicized text. Yet, Quantivity nodded in affirmation while reading, having traded both stat and vol arb for years.
Most importantly, this blurring is popping up in retail quant projects. This is no theoretical debate reserved for academia.
Take two representative examples faced by millions of retail investors: proxy hedging and optimal derivative liquidation. Both have “solutions” from their respective literatures—yet they are ridiculously unsatisfactory in real life. Proxy hedging hails from , exhibiting near complete ignorance of in its treatment of basis risk (while, of course, assuming away residual risk). Optimal liquidation sounds ideal for , but defies risk-neutrality because the holder faces an incomplete market. Practical solutions to both depend upon a concrete convergence of and .
Generalizing beyond these two examples, the following are emerging characteristics of this converged – world:
- Real life in : risk-neutral fantasy disappears, uncovering a messy nest of problems
- formalization: is being increasingly mathematically formalized, borrowing models from both and theory from diverse areas of probability and statistics
- Interdisciplinary: models which are large-dimensional, formalized, and calibrated require deep interdisciplinary knowledge spanning , , and large-scale machine learning
- Empirical: use of empirical statistics and monte carlo methods, rather than closed-form distributions and proofs, is pervasive to modeling the messy real world
- Leadership: statisticians and computer scientists are accelerating (with mathematicians in tow), just as physicists did for
This convergence represents potential for a beautiful renaissance of quantitative finance, opening the door to reconcile long-standing technical contradictions into solutions which can be traded in practice (without deluding ourselves on risk). How many strategies from this converged world have real scalability is a question yet to be answered.
Looking ahead, alpha will increasingly go to those who understand and trade consistent with this convergence. For those who do not, this will quickly evolve into a structure arbitrage.