RP11: Smart Beta Investing – A Data-Driven Strategy to Exploit Systematic Risk Factors in the Financial Markets (WP4)


The capital markets expose systematic risk factors (size, value, quality, volatility, carry, momentum, term structure,  illiquidity anomalies), which can be harvested persistently.23 Definition of multi-asset investment strategies builds on rigorous backtesting over the broadest possible set of data, identifying, constructing, and measuring optimal signals for allocating investments across the different strategies, building broadly based risk management tools for the strategies, and monitoring efficient trade execution. Each step requires handling large quantities of market and economic data. The research project envisages supporting emerging smart-beta investment strategies of real-money investors, such as insurers and pension funds, by big data techniques and tools. Of particular interest is the integration of micro-economic data as early indicators for macro-economic-driven strategies.

“Pure” smart-beta indices, portfolio construction, and risk management tools will be built from big-data analytics of market data, macro-economic data, and select micro-economic data for carry, value, and momentum risk factors. These “pure” smart beta indices do not suffer style contamination or style drift. Overall, we expect to develop risk management tools that monitor spikes in volatility and contagion across risk factors so as to minimise portfolio risk.

Supervisors: David Hutchins SVP/Head, UK Research and Investment Design, ABDC, Multi Asset Solutions, Paula Dawson SVP/Senior Quantitative Analyst, Multi Asset Solutions, Prof. John Keane, The University of Manchester


AB corp logo