October 23, 2018
Conventional wisdom holds that active strategies rarely outperform passive over significant time horizons. The stats support the theory: From 2006 to 2016, 83% of active funds in the U.S. failed to meet their announced benchmarks, 64% were forced to seriously alter their strategies, and 40% were shuttered before their chosen period.
For many fund managers, emerging markets (EM) are the answer. Their characteristic volatility delivers opportunities for that one big call where a market shock can be exploited, and wide disparities in information and reporting (legitimately obtained) mean that technology-based research and analysis can make a significant difference.
In the early days of the very concept of ‘emerging markets,’ the BRICs lacked in efficiency next to their more established cousins, and were even more lacking in coverage. When MSCI launched its EM index in 1988, it only included ten countries, offering a picture that was far from complete.
Today, the biggest index for EMs, compiled by MSCI, includes about 1,600 companies in 24 countries, compared to the more than 10,000 firms in the EM extended universe.
Over the last decade, the space matured but the lack of reliable data was a significant obstacle, as was the inherent biases that could be reflected in the market – an excessive focus on tech stocks in East Asia, classically, or a similarly excessive weighting to Mexico and Brazil. These problems were well-known, making passive strategies unattractive, and some managers built their reputations on finding ‘diamonds in the rough’: firms not on any index that were poised to grow significantly.
Serious players are working hard to acquire far more index and benchmark data than they did even five years ago by either building or buying new tools to help manage that data, as discussed at this year’s Buy-Side Forum in Indonesia.
The MSCI is far from the only EM index, and asset managers are now leveraging those tools to invest actively or incorporate the passive funds that track directly to EMs internal indices.
The high volatility in emerging markets has meant that some indices – especially those including companies involved in China’s vast infrastructure projects in Central Asia – have yielded results that are extraordinary for passive strategies. The iShares Core MSCI Emerging Markets ETF had returns of 38% between 2013 and 2018, even accounting for the 2016 slow down in China.
Currently, new technologies are entering the picture that promise to radically overhaul passive strategies all over the world, regardless of market.
Machine learning (ML) has helped passive investors achieve a detailed level of tracking to make sure they are delivering: ML offers improved performance attribution capabilities that are culture-neutral – there’s no language barrier or historical lens for a machine.
The ability to process vast amounts of data need not necessarily be pointed at the markets, either: internal processes could be revolutionized or the life expectancies of clients could even be used to tailor strategies.
The increase in the quantity of data gathered also means that better quality outcomes are possible – once AI is mature, risk profiles will be adjustable almost literally at the touch of a dial. Sentiment analysis takes a more central role as well – AI can, in theory, become your active manager away from home.
The chief impact here, though, is likely to be a downward pressure on fees. Managers won’t necessarily be in favor, but the pressure created by the popularity of passive strategies may be magnified when clients become aware just how much leg work is done by automation. It’s possible, however, that the new landscape will create new opportunities to redistribute profit risk, or link fees more closely to performance.
We’re still in the nascent stage of adopting new technological strategies into EM investing for both passive and active investors, which means there’s a first-mover advantage for those who are able to leverage the tools that can surface data with speed and accuracy.