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FAVORITE ACADEMIC RESEARCH
In a recent article, The Economist argued that Science is in crisis. In the context of Finance, Prof. Campbell Harvey has asserted that “most claimed research findings are likely false”. The implication seems to be that the peer-review process is severely flawed, which may explain why only a tiny fraction of academic work ends up becoming useful to practitioners. To survive this crisis of confidence, the Ivy Towers need to engage and collaborate with the Wall Street Towers. Financial firms are the only laboratories where academic models can be reliably tested and validated. I think it is safe to assume that academic theories and models not applied by financial firms are likely to be either impractical or wrong.
The list below includes groundbreaking (mostly P-side) academic works that either I or my colleagues at various firms have found helpful in our daily job of managing investments. Please contact me if you are a practitioner who is aware of useful publications not listed below.
|Harvey, C. and Y. Liu||2015||Backtesting||The Journal of Portfolio Management, 42(1): 13-28||
Cam and Yin show how selection bias under multiple testing inflates backtest results, and propose a haircut for Sharpe ratios that corrects for that inflationary effect.
|Harvey, C., Y. Liu and H. Zhu||2014||…and the Cross-Section of Expected Returns||SSRN||
Most claimed research findings in financial economics are likely false. Because of its implications, this may well become one of the most important papers in history. If the authors are right, we may have to throw out most financial academic publications of the last 50 years and start again from scratch...
|Rebonato, R. and A. Denev||2014||Portfolio Management under Stress: A Bayesian-Net Approach to Coherent Asset Allocation||Cambridge University Press||
Here is a book that combines the soundest of theoretical foundations with the clearest practical mindset. This is a rare achievement, delivered by two renowned masters of the craft, true practitioners with an academic mind. Bayesian nets provide a flexible framework to tackle decision making under uncertainty in a post-crisis world. Modeling observations according to causation links, as opposed to mere association, introduces a structure that allows the user to understand risk, as opposed to just measuring it. The ability to define scenarios, incorporate subjective views, model exceptional events, etc., in a rigorous manner is extremely satisfactory. I particularly liked the use of concentration constraints, because history shows that high concentration with low risk can be more devastating than low concentration with high risk. I expect fellow readers to enjoy this work immensely, and monetize on the knowledge it contains.
|Gatheral, J., A. Jacquier||2011||Convergence of Heston to SVI||Quantitative Finance 11(8): 1129-1132||
It proves the Gatheral conjecture, namely that SVI implied volatility and the large-time asymptotic of the Heston implied volatility agree algebraically. It provides a simpler expression for the asymptotic implied volatility in the Heston model. Gatheral's book "The Volatility Surface" (John Wiley & Sons, 2006) is a wonderful read on this subject.
|Meucci, A.||2011||A New Breed of Copulas for Risk and Portfolio Management||Risk, 24(9): 122-126||
A brilliant solution to the computational challenges posed by copulas. Attilio Meucci's book on "Risk and Asset Allocation" (Springer, 2006) is one of the most comprehensive treatises on P-side mathematical finance.
|Avellaneda, M. , J. Reed and S. Stoikov||2011||Forecasting Prices from Level-I Quotes in the Presence of Hidden Liquidity||Algorithmic Finance, Vol. 1, No. 1||
The authors compute the probability that the next price move is upward, conditional on the best bid/ask sizes, the hidden liquidity of the market and the correlation between changes in the bid/ask sizes.
|Baron, K. and J. Lange||2007||Parimutuel Applications In Finance||Palgrave Macmillan||
There is a broad range of uncertain exposures where intermediaries tend not to offer derivatives or risk management products, as they are unable to hedge the resulting exposures. Baron and Lange suggest a parimutuel auction system adapted from the betting industry as a solution to this problem.
|Carr, P., H. Geman and D. Madan||2001||Pricing and Hedging in Incomplete Markets||Journal of Financial Economics, 62: 131–167||
One of the greatest contributions to securities pricing, trading and hedging.
|Ané, T. and H. Geman||2000||Order flow, transaction clock and normality of asset returns||Journal of Finance, 55: 2259–2284||
A true classic among High Frequency Traders, for reasons that may not be obvious in a first reading.
|Almgren, R. and N. Chriss||2000||Optimal execution of portfolio transactions||Journal of Risk, 3: 5-39||
The cornerstone of algorithmic execution. That seminal work was later expanded in collaboration with Julian Lorenz.
|Mandelbrot, B.||1997||Fractals and Scaling in Finance||Springer||
To this day, Mandelbrot's work remains controversial among academic financial economists and econometricians. And yet the applications of his work have produced fortunes. His introduction of fractal geometry inspired the modeling of subordinated stochastic processes in Finance, a discovery that underlies most high-frequency trading applications, e.g. the volume-clock.
|Easley, D., N. Kiefer, M. O'Hara and J. Paperman||1996||Liquidity, Information, and Infrequently Traded Stocks||Journal of Finance, 51(4): 1405-1436||
Practitioners have referred to it as the "Black-Scholes of market making".
|Black, F. and R. Litterman||1992||Global Portfolio Optimization||Financial Analysts Journal, September: 28–43||
It changed the asset allocation industry with the introduction of "views".
|Litterman, R. and J. Scheinkman||1991||Common Factors Affecting Bond Returns||Journal of Fixed Income, 1: 62-74||
What would be of fixed income PMs without it?