When the $300 billion California Public Employees Retirement System killed its $4 billion hedge fund program in the fall of 2014, Theodore Eliopoulos, CIO of America’s largest pension fund, told reporters that complexity and cost were the reasons why.
The State of Wisconsin Investment Board, with about 3.5 percent of its $99 billion in assets devoted to hedge funds at the end of 2015, is using technology to help navigate the complexity of those investments. A new case study released by index and analytics provider MSCI shows how SWIB is using the firm’s HedgePlatform risk analytics tool to address three common pitfalls plaguing asset allocators: style drift, tail risk, and paying for alpha but getting beta.
HedgePlatform tracks over 1,400 hedge funds, which means it has position-level holdings data on 90 percent of SWIB’s hedge fund managers. That’s more granular detail than you can get from combing through historical returns, investor letters, and SEC filings.
“Asset owners like SWIB can conduct analysis that would not be possible without reported holdings,” the report claims. “For example, SWIB can model market scenarios, including sudden changes in equity markets, interest rates, credit spreads and exchange rates, to uncover risks in their hedge fund portfolios.”
By simulating shocks in different market variables, SWIB uses the platform to determine whether managers are straying from their investment mandates and what impact this so-called style drift may have on their portfolios. It also allows SWIB to look under the hood and see the specific types of securities driving those exposures.
To avoid getting blindsided by outsize drawdowns, SWIB takes a bottom-up approach to building return profiles based on the underlying holdings in its managers’ current portfolios and calculating measures like value at risk (VaR) and expected shortfall (also known as conditional VaR) rather than basing risk and return expectations on a hedge fund manager’s track record.
Last but not least, SWIB can tell when managers aren’t really delivering alpha. The pension’s fund-of-funds team uses MSCI’s GEM2 Barra Model, which measures the effect of country, industry, and style exposures, to determine whether beta exposures might be driving returns. This approach allowed it to catch an equity market neutral manager, for example, who isn’t so neutral after all.
