Best Quant Paper 2020
- 07 Dec 2020
CFA Institute Research Foundation Wins Best Quant Paper 2020
As quantitative researchers have accelerated their pursuit of investment edge, artificial intelligence (AI) has become an integral part of the quant arsenal. For institutional investors exploring this field, quant material must be accessible and intelligible. Savvy Investor is pleased to award Best Quant Paper to CFA Institute Research Foundation’s, "Artificial Intelligence in Asset Management”, which is a comprehensive compendium of all things AI for the investment professional.
WINNER: CFA INSTITUTE RESEARCH FOUNDATION
Artificial Intelligence in Asset Management (CFA Institute Research Foundation, 2020)
Since computing power and data availability have improved in the last decade, the asset management industry has naturally gravitated towards more sophisticated quantitative methods to help ‘forward model’ the future. This review from CFA Institute Research Foundation provides institutional investors with a solid grounding in all aspects of AI within the asset management industry. Covering AI concepts such as deep learning, neural networks, and genetic algorithms as well as how AI may be used in portfolios, this document is a must-read for today’s institutional investors.
HIGHLY COMMENDED PAPERS
Quantifying Macroeconomic Risk (Qontigo, 2020)
In the quest for robust risk-adjusted returns, Qontigo and State Street have combined to present a “macroeconomic risk model”, which utilises interest rate, credit, commodity, and other exposures as investment factors. Insights from this study will no doubt be of interest to fund managers looking for analyses in portfolio exposure, risk, performance attribution, and portfolio construction.
Building Resilient Portfolios for Uncertain Times (WisdomTree Investments, Nov 2020)
For compliance reasons, this paper is only accessible in the UK & Europe
In the fight against equity drawdowns, limiting risk whilst allowing for upside potential is a phenomenon that must be actively managed by institutional funds. From the tech bubble crash to the COVID-19 crisis, Wisdom Tree backtests an all-weather portfolio strategy across 20 years of data illustrating that the study of defensive asset characteristics may help in the design of resilient portfolios.
The Data Science Revolution (Neuberger Berman, 2020)
For compliance reasons, this paper is only accessible in certain geographies
Big data has been described as the “new gold”. The discerning quant recognises, however, that scientific analysis of that data only has true value when it can be applied to an existing investment process. Through discussion of general data science, ‘Quantamentals’ and drawing upon real world examples, Neuberger Berman’s researchers illustrate how new alpha may be generated in investment portfolios.
How to Reduce the Sources of Forecasting Error (Morgan Stanley IM, 2020)
Behavioural finance is an often-underestimated piece of the modern-day jigsaw puzzle in portfolio management. This insightful paper from Morgan Stanley Investment Management illustrates how modelling human biases, market information and ‘noise’ (BIN model) may serve as a useful tool in the error-prone world of forecasting and prediction. Investors who can ‘think differently’ may therefore discover a way to improve decision making.
Tail Risk Hedging: Contrasting put and trend strategies (AQR Capital Management, 2020)
In the wake of two significant equity market declines since Y2K, investors have deliberately sought a better understanding of how to manage portfolio drawdowns and achieve robust crash protection. In this 16-page investigation, AQR illustrates that portfolio insurance need not always be ‘long put centric’, arguing that trend-based strategies can still achieve portfolio protection as well as long-term investment performance.
Learning From a Decade of Managed Volatility (PIMCO, 2020)
Since the Great Financial Crisis (GFC), the omnipotence of central banks’ QE initiatives has caused market volatility spikes to be not only been infrequent, but also short-lived. In a post-GFC world, price deviations beyond two sigma are now considered relatively abnormal. Pimco’s research team investigates this period in history, draws upon the lessons learned, and provides insights for the future.
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