Feature – Artificial intelligence
AI: FUND MANAGEMENT 2.0
When Hiromichi Mizuno joined GPIF as chief investment officer in 2014, he was taking on a big challenge. The Japanese Government Pension Investment Fund, which manages ¥159trn (£1.1trn) was in the midst of a significant switch into riskier assets. Between 2012 and 2015, GPIF reduced its alloca- tion to domestic bonds to 38% from 67%. By March 2019, Jap- anese bonds only accounted for 26% of the scheme’s assets while exposure to foreign debt and global equities increased significantly.
Over the past 10 years, in the context of Abenomics, the scheme has faced negative returns across its equity and bond portfolios whilst forking out more than ¥70bn (£500m) in management fees between 2013 and 2016 alone. In the final quarter of 2018, the pension fund giant reported losses of ¥15trn (£106bn). GPIF argues that the culprit for such a disappointing perfor- mance was not just low yields but also the failure of active managers to outperform. GPIF’s leadership then made a bold statement: artificial intelligence (AI) could play a key role in addressing this problem. In 2017, GPIF commissioned Sony Computer Science Labora- tories to investigate how the pension fund could use AI to transform its performance. By assessing fund manager styles, it hopes to improve its understanding of alpha generation and investment performance. As of January 2020, GPIF confirmed that it had set up a system to monitor funds across a universe of 1,000 Japanese and foreign stocks. By analysing trading data, the system aims to identify resemblances in the charac-
34 | portfolio institutional February 2020 | issue 90
teristics of various fund managers. It is now at the stage of implementing the system across its portfolio, initially on an experimental basis. While the Japanese investment giant might be at the forefront of AI implementation, there are early indications that its Euro- pean and American counterparts might follow suit. More than half of institutional investors globally plan to use AI as part of their investment research within the next five to 10 years, according to a recent poll by Thomson Reuters and Greenwich Associates. This would mark a significant change as only 17% of respondents are currently using AI in their investment process.
Machine learning Yet the extent of AI adaptation could easily be misinterpreted by conflating it with a more efficient use of financial data. For John Beckett, author of the book “The New Fund Order”, three key criteria define AI.
“Of course, fund managers and investors are used to accessing data since the early days of Bloomberg and Archipelago,” he adds. “But data as an information point doesn’t constitute AI. For AI to be present either of three criteria must apply. “First, it should involve an algorithm or programme built in layers, what we call pillars which make decisions, so there must be a clear learning aspect to it.
“The second form of AI is where you develop an algorithm which can move left or right based on the information you
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