What Was The Event?

The Battle of the Quants Big Data (a client project) took place at the Asia Society in Hong Kong on 15th October, 2019.  The event was for quantitative hedge fund managers, investors in quantitative funds, quantitative hedge fund data buyers; and big data providers and alternative data providers to quant funds.

What Was It About?

In its 14th year of hosting the leading quantitative event worldwide, the Battle of the Quants – BIG DATA returned for its 4th event in Hong Kong, combining the best in Quantitative Finance and Big Data. The Battle of the Quants has become the definitive event for investors, managers, and data buyers looking for key industry influencers, decision makers, and investment opportunities. The packed agenda included cutting edge discussions in quantitative finance, extensive networking, capital introduction and data introduction breakfasts, and pre-scheduled one-on-one meetings helping attendees to form valuable professional business relationships. The event attendees included carefully selected Quantitative Managers, Allocators, and Data Scientists leading the way into the new world of Artificial Intelligence, Alternative Data Sets, Machine Learning and Quantum Computing. Careful consideration was given to include issues confronting investors and traders participating in the increasingly quantitative global financial system.

Who Was There?

A sampling of who was in attendance:

  • Quantitative hedge funds – heavily systematic, and advanced users of AI / ML (Artificial Intelligence / Machine Learning)
  • Fundamental funds
  • Institutional Investors & Allocators – pensions, endowments, asset managers, fund of funds, family offices, and more
  • High Net Worth Individual investors
  • Exchanges
  • Big Data and Alternative Data providers
  • Technology & analytics providers
  • Industry consultants and innovators
  • Academics
  • Industry analysts

The speaker list is here.  It was a full house at the Asia Society.

Quick Hits, Before the Event

A series of context-setting events preceded the Battle of the Quants Big Data event in Hong Kong:

BattleBlitz Investor Series – Breakfast in China

China is the second largest economy in the world with a population of over 1.4 billion and an incredibly dynamic marketplace. The huge population, sophisticated digital ecosystem, fast growing middle class, and pace of business creation all combine to provide abundant alternative data for trading. The “Breakfast in China” event, held on August 13th 2019 at The Lambs Club in New York City, brought economists, experts in Alternative Data, Quantitative managers focused on Asian markets, and investors into a discussion about quantitative trading on alternative data in China.

BattleFocus – Live Video Discussion

This video discussion about Structuring Data for Predictive Analytics, streamed live on September 11th, 2019, foreshadowed an in-depth presentation at the Battle of the Quants Big Data in Hong Kong. As shown here at the Battle (with a link to the white paper), StreetSide, IQ Banker and Calculated Systems joined forces to develop Weibo Analytics, a natural language processing tool powered with supply chain relationships, specifically designed to analyze Chinese social media content for applications in Capital Markets.

Opening Cocktails at the Armoury, Tai Kwun, Hong Kong

Upon arrival in Hong Kong, Battle of the Quants Big Data event participants mingled at the Armoury Parade Ground Bar and Cafe in historic Tai Kwun.

Quick Hits, At the Event

Photos from the Battle of the Quants Big Data event are here.  These items stood out:

Capital Introduction / Data Introduction Roundtable Breakfasts:

Quant fund managers introduced their strategies to investors, and data providers introduced their data sets to quant fund data buyers, at a roundtable breakfast session.

[These posts for fund managers and investors, by Castle Hill Capital Partners, explain how to participate successfully at roundtable introduction events]


Research Presentations

  • Keynote: Sarasin & Partners presented The Quantitative Landscape – Factor Models, HFT, Trends and Machine Learning, Alternative Data. What is the next generation of Quants?
  • IHS Markit presented Demystifying Alternative Data: A Revealing Study of the Global Alternative Data Landscape – a continuation of the same presentation given at the Battle of the Quants Big Data in New York on May 22, 2019.

Data vs. Insights

The financial industry’s focus on data in comparison with its focus on insights, along with the importance of social media data, was a key theme at the Hong Kong Battle of the Quants event, which featured panel sessions covering big data.

Notably and particularly in the Chinese market geographically closest to the event, there have been great changes that are affecting how firms consider and handle data, and how social media data is harnessed.

Portfolio managers in China have become highly systematic, according to panelists at the conference. At the same time, the Chinese market has matured a great deal, putting it on par with Western markets such as the US and the UK, in terms of trading volume and the richness of data. This has, no doubt, attracted quant investors. Also, social media activity and the data it generates continues to increase rapidly in the Chinese market. The market is catching up with how to handle that data, however.

First, some context, namely with a few words on what the alternative data problem is. As Rob Passarella put it in the above mentioned video discussion about Structuring Data for Predictive Analytics, alternative data at first meant all data other than the “classic” data that is “ready made,” such as point in time, securities identifiers and the like. The approach to alternative data was to build haystacks, then go looking for the needles. This approach of collecting all available data used to be enough, but now companies should be asking the right questions, then finding the data that can answer those questions.

Social media data, as a form of alternative data, is yet another haystack. For all of that data to be useful for finance, Passarella says, it has to be organized. This requires structure that can be achieved by identifying entities, products and brands, then matching those to mappings and identifiers. This kind of structuring is now needed and expected to make alternative data useful. Think of this structure as raising a barn, to be a place where you can spread the hay out on the floor and look for the needles.

Social media data can, for example, be a barometer for relationships between companies that do business with each other or are part of the same supply chain. Speakers at the Battle of the Quants Big Data in Hong Kong talked about looking at how social media volume in China affects investment products, specifically in terms of market share.  StreetSide, IQ Banker and Calculated Systems presented their joint effort to develop Weibo Analytics (as shown here with a link to the white paper) , a natural language processing tool that uses supply chain relationship data to analyze Chinese social media content, and then use the resulting insights in capital markets applications.

This is another way that analyzing alternative data or unconventional content can yield market insights, just as AI learned what slang is used to identify bad investments, as related at the Battle of the Quants Big Data in New York earlier in the year.