Chief Portfolio Strategist
Analytical models inform investment recommendations, risk management at First Allied
Independent financial advisors and their clients rely on First Allied Asset Management to help them make the right investment decisions. Using SAS, First Allied teams manage 100 different investment models that support timely recommendations and identify potential risk exposures.
With a network of nearly 1,000 financial advisors and 500 branches across the US, First Allied – a full-service independent broker/dealer, registered investment adviser and wealth management firm – is a dynamic leader in the financial industry. Founded in 1994, First Allied aims to provide independent financial advisors with cutting-edge technology, innovative products and superior service. Today, the firm enjoys a reputation as one of the premier broker/dealers for successful independent financial advisors.
We run our portfolios through proprietary SAS models to identify potential risk exposures … I'm able to maintain it all without any dedicated resource or outsourced contractor.
One of the linchpins to this successful track record is the contribution of its asset management division based in Scottsdale, AZ, which handles more than $1.1 billion in client holdings. Under the direction of Jeff Mindlin, Chief Portfolio Strategist, teams of First Allied investment professionals develop detailed analyses that guide the investment recommendations the firm provides its financial advisors and their clients. First Allied uses SAS to help manage more than 100 different investment models.
"We rely on SAS for many of our investment decisions as it provides the framework for our quantitative infrastructure," Mindlin said.
First Allied uses SAS for a variety of technical and macroeconomic analyses, and a broad range of financial modeling to support the investment decision-making process. "Our chief investment officer is a Chartered Market Technician (CMT), so our challenge is to translate the most critical charts and patterns into SAS models that identify the measures he focuses on the most," Mindlin said. "On the technical analysis front, we have a universe of about 1,000-2,000 candidate stocks and exchange traded funds (ETFs). We're running a very deep set of calculations and metrics across numerous periodicities. Since we have daily pricing data from Morningstar and other sources – that extends back decades – we're looking at tens of millions of rows and several gigabytes of data."
Moving to a virtual machine for greater performance
First Allied runs its analytical models every week to gain updated visibility into the technicals of ETFs, individual stocks, sectors and the top 1,000 stocks (by market capitalization). Even a simple update to five moving averages or a report on overbought/oversold securities can result in thousands and thousands of calculations.
"We secured a virtual-machine license and moved these analytical procedures to the cloud," Mindlin said. "Instead of taking a half-day to run these routines on my desktop PC – which also impacted my productivity – we are now able to get our answers in a few minutes. A lot of this analysis involves pattern recognition. We're looking at charts and trying to define what we see in measurable signals and indicators – pullbacks, waves and other indicators that we've determined are significant."
Risk management is also an ever-present consideration. "We run our portfolios through proprietary SAS models to identify potential risk exposures – beta and correlations to stocks, bonds and commodities, and more granular size, sector, style, country, credit and interest rate exposures," said Mindlin. "Then we can see if our portfolio risks align with our market outlook and themes."
Mindlin noted that the SAS deployment is very low impact and easy to maintain. "Although we run resource-intensive routines, we have a remote virtual machine that has kept our cost profile low," he said. "While we modify the routines, I'm able to maintain it all without any dedicated resource or outsourced contractor."
First Allied needed an efficient way to build and maintain sophisticated financial models that help the firm make informed investment recommendations on behalf of high-net-worth clients.
First Allied investment professionals now have access to timely analyses and unique, proprietary screens that reflect their market perspectives and risk tolerance. Investment analysis is not only more reliable and scalable, but faster as well.