May 2017: Don’t Put All Your ESGs in One Basket

ESG is one factor to consider in investment decisions, as is the growing alternative data space, which we revisit this month—this time from the point of view of quantitative traders and investment managers—courtesy of Risk magazine’s Faye Kilburn. Despite predictions of massive increases in spend on alternative data, many efforts to date have proved costly failures due to the complexity of not just handling the unstructured datasets, but being able to eke out consistent returns. Ironically, that’s exactly how some quants like it—or at least, so they profess: the harder and more expensive it is to harness this data, the less likely their competitors will be to attempt it, and the dataset will continue to deliver profits for longer, instead of everyone piling in at once, eliminating any advantage.

The impact of systematic investors’ activity on markets is also evident elsewhere in this issue of Inside Data Management: Quantitative traders at Morgan Stanley spotted strange modal activity in data from the Tokyo Stock Exchange, which suggests high-frequency trading activity is actually changing market microstructures. And in a separate article, Dan DeFrancesco analyzes how three US stock exchanges plan to introduce artificial delays to their data and order-routing infrastructures in response to IEX’s exchange approval. IEX uses a “magic shoebox” of spooled fiber to introduce a 350-microsecond delay to eliminate latency disparities between different market participants. By implementing similar offerings, NYSE, Nasdaq and the Chicago Stock Exchange hope to negate IEX’s main differentiating factor.

These trading innovations could not have been possible without significant automation across the trading infrastructure that connects firms and markets. But some other areas within financial firms struggle with automation issues. Focusing on changes coming out of the Monetary Authority of Singapore, Wei-Shen Wong reports on how the increasing regulatory burden has the potential to drive greater levels of automation around these functions, and how firms may flounder if they attempt to handle new-world regulatory requirements using old-school techniques—a sentiment that could equally be applied to any business function across today’s markets.