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"Is Momentum Still Relevant for Today's Markets?" from QuantCon Singapore 2016

Anthony Ng, Senior Lecturer, gave this presentation at QuantCon Singapore 2016. QuantCon, our algorithmic trading conference, will be back in Singapore this September 28th-30th with another expert line up of speakers. Check out Anthony Ng’s presentation below to get a preview of this year’s event, and reserve your spot today.

"Is Momentum Still Relevant for Today’s Markets?" by Anthony Ng, Senior Lecturer

Despite being ‘discovered’ over 20 years ago, there is still confusion on what a momentum strategy entails. There are two generally accepted definitions of momentum in academic literature. In the quantitative equity investment sphere, momentum is frequently referred to as across securities or assets (cross-sectional or relative) and typically traded in a long-short or hedged manner. In futures trading, momentum is often referred to the past return of the security (time-series) and normally traded in a directional fashion.

Following from the above, we conducted an analysis on the performance of a momentum strategy of different asset classes: equity, fixed income, futures, and currencies. The study showed that both types of momentum are prevalent and persistent across all asset classes. Furthermore, as the correlations between the two types of momentum strategies and amongst the asset classes are quite low, substantial diversification benefit can be derived by combining them.

Join us this year to hear "An Ensemble Approach to Nowcasting Economic Conditions: A Practitioner’s View"  from our keynote speaker Yi Li, Portfolio Manager at GIC’s Systematic Investment Group (SIG). Use discount code QCommunity2017 to get 10% off  your ticket at

Other 2017 talks include:

  • "Order & Randomness in Asian Market Microstructure" by Dr. Kerr Hatrick, Executive Director of the Electronic Trading Strategist Group at Morgan Stanley
  • "Supply Chain Earnings Diffusion" by Josh Holcroft, Head of Quantitative Research, Asia at UBS Investment Bank
  • "Real-time Machine Learning Architecture and Sentiment Analysis Applied to Finance" by Juan Cheng, Data Scientist at InfoTrie

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