Japanese Firms Are Most Advanced in Asia At Using Machine Learning To Generate Alpha

Bloomberg poll shows real-time data is most commonly used for signal generation

A recent Bloomberg poll of 450 market participants – comprising traders, portfolio managers, analysts and market data practitioners in Hong Kong, Mumbai, Tokyo, Singapore and Sydney who attended the company’s second annual Machine Learning Decoded roadshow – showed that Japanese firms are the most advanced in Asia in using machine learning to generate alpha. Japan is also leveraging a diverse range of data sets in their investment strategies, including real-time data to fundamentals and news and social media sentiment data.

More than 50% of 140 respondents in Tokyo surveyed said they have started to use machine learning to generate investment signals, while the majority of participants in Sydney (53%), Singapore (52%) and Mumbai (70%) are investigating or just starting to look into using machine learning in their investment strategies.

Keen competition, slower growth, intense fee pressure and the resulting need for differentiation is driving active, passive, quantitative, fundamental, traditional and alternative managers to find ways to leverage machine learning to capture alpha. Machine learning is a subset of artificial intelligence that focuses on teaching computer systems to “learn” independently with data, as a way to automate processes and increase efficiency.

Gary Kazantsev, Head of Machine Learning Engineering at Bloomberg LP said: “As a result of critical advances in the past few years in computing power and newly available vast pools of data, we are seeing more clients using Bloomberg’s data solutions as inputs into strategies for black box trading. Looking ahead, I expect the pace of innovation to accelerate because the barrier to entry to using these tools continues to fall.”

In the Bloomberg survey, the majority of participants are using real-time data (45% in Sydney, 43% in Japan, 35% in Singapore), followed by fundamentals (financial results, securities prices), news and social media sentiment.

Investors are increasingly turning to alternative data sets with new techniques focused on finding new, relevant investment signals. The massive data sets available for analysis span the spectrum from basic market and economic data to data from social media sources, satellite imagery, written documents and weather forecasts.

One of the top challenges cited by survey participants in adopting machine learning was the lack of high quality data. Companies want to use data in a normalized format, as these ‘tidy formats’ facilitate data analytics.

Bloomberg recently launched a web-based data delivery platform, Bloomberg Enterprise Access Point, which seeks to help customers explore and interact with bulk data sets in ways that are easy to manipulate, model and visualize.

“Data fragmentation creates inconsistencies and misalignment across the enterprise, ultimately exposing organizations to unnecessary risks and costs,” said Gerard Francis, Global Head of Enterprise Data at Bloomberg. “Having a single point of access for trusted data not only creates a new standard for quality, but also accelerates the client’s ability to realize bottom-line value across the enterprise.”

Machine learning is still in the early stages of being applied across Asia. The top challenge cited in the adoption of machine learning in the survey is the lack of in-house expertise. The majority of respondents across the region will be focusing on professional development and learning more about machine learning for the next 12 months. To address this challenge, Bloomberg recently released “Foundations of Machine Learning,” an online video education course for financial professionals with a strong mathematics background to learn more about the concepts, techniques and mathematical frameworks used by experts in machine learning.

Bloomberg has been implementing and investing in machine learning for approximately a decade. More than 5,000 technologists, over a quarter of the Bloomberg workforce, includes data scientists, quantitative researchers, machine learning experts, software engineers and developers. Their focus is building software applications and systems to derive intelligence and insight from data so clients can make smarter, more informed decisions about their business and investment strategies.

About Bloomberg
Bloomberg, the global business and financial information and news leader, gives influential decision makers a critical edge by connecting them to a dynamic network of information, people and ideas. The company’s strength – delivering data, news and analytics through innovative technology, quickly and accurately – is at the core of the Bloomberg Professional service. Bloomberg’s enterprise solutions build on the company’s core strength: leveraging technology to allow customers to access, integrate, distribute and manage data and information across organizations more efficiently and effectively. For more information, visit www.bloomberg.com or request a demo.

Media Contacts
▪ APAC, Grace Ngoh, gngoh2@bloomberg.net, +65 6231 3690
▪ EMEA, Anna Schoeffler, aschoeffler@bloomberg.net, +44 20 3525 0776
▪ U.S., Alyssa Gilmore, agilmore7@bloomberg.net, +212 617 4901
▪ LATAM, Pam Snook, pamsnook@bloomberg.net, +212 617 7652