NEW YORK—State Street Global Markets Wednesday unveiled seven new indexes designed to help institutional investors map out hidden market opportunities.
Called the Turbulence Indices, the tools go beyond the CBOE Volatility Index, said Will Kinlaw, managing director and head of the portfolio and risk management group at State Street Global Markets.
State Street's indices address questions involved with traditional Modern Portfolio Theory, macroeconomic trends, aggregate/disaggregate analysis and convergent views on market price and fair value, Farley said.
The seven indexes cover:
- Global Assets
- U.S. Assets
- European Equity
- U.S. Fixed Income
- U.S. Treasury
- U.S. Credit
Since the beginning of the financial crisis and market dislocation dating back to early 2008, Farley said, State Street clients—like those of so many asset management firms—have barraged the company with inquiries on risk and loss. Thus, very early on, State Street, already well-known for its indexes, decided to go back to square one.
“Volatility in standard deviation is not the sum of all fear,” said Daniel P. Farley, managing director and global head of investments for the Multi Asset Class Solutions (MACS) team at State Street Global Advisors.
“We’re not here to replace the VIX," Kinlaw added. “The goal is to estimate exposure to loss more reliably and create portfolios more resilient to turbulence to enhance performance.”
Users are also able to download the index values and apply them to their portfolios to more effectively manage risk, Kinlaw said.
At present, institutional investors are most keenly interested in hedging currencies, macro global trends, active equity and small-cap emerging markets, Kinlaw said. Two interesting plays in small-cap emerging markets, for instance, Farley said, are "India-Growing" and "China-Growing."
State Street said the “unusualness and abnormality can result from extreme events that move volatility up or down or from a sudden change in correlation” between assets.
In mathematical terms, State Street defined “unusualness” and “turbulence” this way:
“Unusualness” is the covariance-adjusted distance between that day’s observation, which is comprised of a set of contemporaneous returns, and the multivariate mean in multi-dimensional space. “Turbulence” is defined using this multivariate distance to quantify unusual patterns of investment returns.
Lee Barney is editor of Money Management Executive.
Tom Steinert-Threlkeld contributed to this article.