Determining the best separate account manager in a particular asset class can be a daunting task for brokers, financial intermediaries, consultants, investors and even other separate account managers who want to check their progress against the competition.
Now, data and software company Effron PSN and investment analysis firm Analytic Engines, both of White Plains, N.Y., have partnered to offer a SMART solution.
The collaborative SMART technology (which stands for Structured Managed Asset Rating Tool) ranks separately managed accounts. Similar evaluation technology is being adapted for use with both mutual funds and exchange traded funds (ETFs). Later this year, it will also assess hedge funds.
But don't look for any magic bullet, single number, or star-type ratings within the SMART program. Instead of crunching together a separate account manager's performance and risk characteristics and trying to produce a single metric rating, the engine produces rankings that collectively show how each separate manager's expertise ranks against a logical peer group the two partners have created.
People can become overly dependent on a single-number or star-type rating system, said Lac An Vuong, managing director of Effron PSN. Instead, there are many factors and scores that should be looked at in the evaluation process, he added. "This gives us a newer way of looking at the information." Effron PSN build its tool by collecting performance and account data directly from separate account managers and pouring that information into a proprietary database.
Wrong Side of the Track?
Tracking separate account performance is difficult, at best, predominantly because performance information on managed accounts is not as available, unlike the much more transparent performance information widely disseminated for mutual funds.
Moreover, while the precise performance on every available share class of every publicly available mutual fund is broken out with its own individual performance, separate account managers aren't required to separately report the performance on every single client account that they manage. Rather, performance standards allow managers to aggregate all discretionary portfolios that they manage in a similar style into a single representative group called a composite.
However, that composite does not reflect performance in a client's separate account, which can vary widely. A separate account investor's risk, investment and tax-management needs means each portfolio must be tailored.
To provide a more granular look at SMA managers, the SMART proprietary mathematical modeling engine built by Analytic Engine President and CEO Dr. Shervin Hanachi, analyzes a composite based on 21 quantitative indicators across five categories. Before starting his own company, Hanachi formerly built similar quantitative systems for his employer Merrill Lynch.
Categories include performance attributes, performance evaluation, portfolio characteristics, risk measures and return characteristics for the past three and five years. Using mathematical modeling, the raw data is then crunched and "scores," in most categories from one to 10, are spit out, allowing each account manager to then be ranked against the similarly produced scores of other managers in a peer group. SMART's analysis can rank separate account managers across 76 peer groups. For mutual funds, it will rank them against 87 peer groups.
Perhaps the most significant information is derived from the investment-management analytical components - asset allocation, security selection and timing - that are built into the SMART system and used to assess how a manager has achieved his or her returns. That allows SMART users to see if active managers are adding value, or have just been lucky, Hanachi explained.
SMART-er Metrics
SMART includes two significant attributes, according to Hanachi. First, instead of attempts by some to squeeze investment performance into equally populated quartiles, which can end up skewing numbers, SMART allows performance trends to fall where they may into a bell shape.
Secondly, some systems utilize the Sharpe Ratio to measure the return that is produced with excess risk. But given the current market environment, in many cases negative numbers for Sharpe ratios are turning up. "A negative Sharpe Ratio is a meaningless and misleading measure," Hanachi said. The SMART system doesn't produce a simple risk ratio like Sharpe, he said. Instead SMART uses a more complex mathematical model to determine risk.
Other data providers are working to also develop systems that can cut through the separate account performance haze and provide more concrete information.
Last June, Morningstar of Chicago debuted Principia for Separate Accounts, a proprietary separate account database for financial intermediaries fashioned after its sibling Principia mutual fund database. But Morningstar is still working to develop a proprietary rating system for separate accounts, confirmed Martha Moss, a Morningstar spokesperson. New York rating agency Standard and Poor's is also holding discussions to consider whether to offer a separate account rating system although no decision has been made, said spokesman Dave Guarino.
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