NEW YORK and LONDON, Oct. 25, 2016 /PRNewswire/ -- MPI (Markov Processes International), a leading provider of quantitative research, risk analytics and reporting solutions for the global investment management industry, suggests institutional investors consider using daily or weekly performance data, and advanced quantitative modelling techniques, to provide insights into the drivers behind complex investment funds' performance.
This is the conclusion of the MPI's latest research, 'Standard Life GARS Fund: MPI's Factor X-ray'.
Using the Standard Life Global Absolute Return Fund (SLI GARS) as a case study, MPI demonstrates how sophisticated factor analysis techniques can provide valuable inputs into the overall fund selection and due diligence process.
The £27bn SLI GARS fund has been renowned as a leading absolute return UCITS/mutual fund since its inception in 20081. However, recently its performance reversed from the peak reached in April 2015. "With many investors concerned about GARS' recent performance, we wanted to shed some light on the factors that might be contributing to the complex global 'go anywhere' fund's performance results," said Michael Markov, co-founder and Chairman, MPI.
Digesting GARS' dozens of strategies, and thousands of positions, from a 'bottom up' holdings perspective could be a daunting exercise. MPI has therefore taken a 'top down' quantitative approach that has distilled the fund's performance history into a handful of well known, and easily understood, style/factor exposures.
Using its patented Dynamic Style Analysis (DSA) technique to capture SLI GARS' time-varying factor exposures, MPI inferred that SLI GARS has shifted both its gross factor exposure and net factor positioning. The analysis indicates that the primary reason for its recent underperformance appears to be that SLI GARS has missed out on most of the latest leg of the bond market rally. This is partly because its fixed income exposures appear to have been scaled back in mid-2015 and also due to short US interest rate duration exposure that has suffered as market expectations of Fed rate rises have been pushed further out. Apparent long exposure to European equities has also detracted from returns. On the other hand, long exposures to UK equities and US corporate bonds have contributed positively.
SLI GARS' reduction in fixed income exposure has markedly distinguished the strategy from those of its peers in the Morningstar global alternative multi-strategy category2. The peer group are inferred to have maintained greater long exposure to US and Euro bonds, which have so far delivered positive performance in 2016.
Going forward, SLI GARS appears to be positioned to profit from further Fed rate rises and an extension of the US dollar's uptrend. "We observed that the fund's returns exhibit significant strategic factor bets. If for example, the US dollar strengthens and US interest rates rise, the fund may be able to recover some of the losses this year," Markov said.
Reflecting on how allocators can use MPI's research, Daniel Li, PhD, Senior Research Analyst, MPI pointed out "At a time when transparency and liquidity are the focus of investor concerns, advanced machine learning techniques such as DSA, together with the use of more frequent data – daily or weekly fund NAVs – could significantly enhance investment due diligence processes. These techniques can help to corroborate reported portfolio exposures and monitor rapid shifts in style and leverage levels. Insights into factor exposures can also help investors to better anticipate a fund's performance and behaviour in light of observed financial market trends."
MPI (Markov Processes International) is a global provider of investment research, analytics and technology. Its solutions are used by leading organizations throughout the financial services industry, including: alternative research groups, hedge funds, hedge fund of funds, family offices, institutional investors, consultants, private banks, asset managers, investment advisors and private wealth professionals. For more information, visit http://www.markovprocesses.com. Follow us on Twitter @MarkovMPI.
1 SLI GARS is not a traditional mutual fund and according to its latest update in August 2016, the fund deploys between 20 and 35 different strategies across various asset classes, invests globally and often uses advanced derivatives techniques. Specifically, the fund follows strategies that are more similar to those of a global macro hedge fund than a traditional, balanced mutual fund. These features pose significant challenges for using traditional quantitative fund analysis methodologies to generate an illuminating analysis of the fund.
2 Using the same factors as in the GARS analysis, MPI analyzed the 37 largest funds from the 68 global alternative multi-strategy in the same Morningstar category, but limiting the timeframe of the analysis to a shorter period since GARS' performance peak in April 2015.
To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/mpis-factor-analysis-reveals-key-trends-behind-sli-gars-performance-300350250.html
SOURCE MPI (Markov Processes International, Inc.)