Unconstrained Fixed Income | Voya Investment Management
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Unconstrained Fixed Income

Approach

This strategy employs an unconstrained and flexible approach, investing broadly across debt markets to provide a more stable and resilient long-term investor experience. This can be achieved through flexible portfolio construction guided by a constrained absolute risk target and a careful use of duration to diversify portfolio risk exposures.

Key Benefits

  • Seeks consistent, moderate returns across all market environments with a focus on downside protection
  • Controlled fixed income-like risk exposure
  • Avoidance of undue correlation to traditional fixed income and equity

Performance

Performance

As of 6/30/251 Month3 MonthYTD1yr3yr5yr10yrSince Inception (1/01/13)
Gross1.212.494.588.516.534.514.174.08
Net1.172.364.327.976.003.993.703.62
Index*0.361.082.164.934.662.832.161.78

* ICE BofA USD 3M LIBOR Constant Maturity Index

Past performance does not guarantee future results.

Periods greater than one year are annualized. Performance data is considered final unless indicated as preliminary. Monthly performance is based on full GIPS Composite returns. Access the GIPS page for full composite details.

The Composite performance information represents the investment results of a group of fully discretionary accounts managed with the investment objective of outperforming the benchmark. Information is subject to change at any time. Gross returns are presented after all transaction costs, but before management fees. Returns include the reinvestment of income. Net performance is shown after the deduction of a model management fee equal to the highest fee charged.

Literature

Investment Team

Sean Banai

Sean Banai, CFA

Head of Multi-Sector Fixed Income

Years of Experience: 26

Years with Voya: 26

Sean Banai is head of multi-sector for the fixed income platform at Voya Investment Management. Previously, Sean was a senior portfolio manager and before that head of quantitative research for proprietary fixed income. Prior to joining the firm in 1999, he was a partner in a private sector company. Sean received a BA and an MS in actuarial science from Georgia State University. He holds the Chartered Financial Analyst® designation.

Eric Stein, CFA

Chief Investment Officer

Years of Experience: 22

Years with Voya: 1

Eric Stein is the chief investment officer for Voya Investment Management. With responsibility for public and private markets platforms, Eric leads teams of investment professionals across fixed income, alternatives, equities, multi-asset strategies and solutions, and income and growth. Previously, he served as Voya's CIO of fixed income and head of investments. Prior to Voya, Eric was chief investment officer for fixed income at Eaton Vance and Morgan Stanley Investment Management, where he was responsible for overseeing over 275 investment professionals managing strategies with approximately $200 billion in assets under management across the fixed income spectrum for institutions and individual investors worldwide. He previously was co-head of the global macro/emerging market debt group at Eaton Vance. Eric earlier worked on the Markets Desk at the Federal Reserve Bank of New York. Eric earned a BS from Boston University and an MBA from the University of Chicago Booth School of Business. He is a member of the Council on Foreign Relations and a CFA ® Charterholder.
Brian Timberlake

Brian Timberlake, PhD, CFA

Head of Fixed Income Research

Years of Experience: 22

Years with Voya: 22

Brian Timberlake is the head of fixed income research at Voya Investment Management, responsible for managing the organization’s global fixed income research analysts as well as the coordination of macroeconomic data across the fixed income platform. His team is responsible for macro and quantitative fixed income research and provides additional assistance to individual sector groups and the risk management team. In addition, Brian is a named portfolio manager on several global and opportunistic fixed income products. Previously at Voya, he was the head of quantitative research where he helped develop an integrated, automated tool for interest rate hedging, created multifactor risk models, and was integral to the design and monitoring of customized client portfolios. Prior to that at Voya, he was a senior quantitative analyst. Brian earned a PhD in chemical engineering and an MS in quantitative and computational finance from the Georgia Institute of Technology, and a BS in chemical engineering from the University of Maryland. He is a CFA® Charterholder.

Disclosures

Peer Rankings: eVestment collects information directly from investment management firms and other sources believed to be reliable; however, eVestment does not guarantee or warrant the accuracy, timeliness, or completeness of the information provided and is not responsible for any errors or omissions. Performance results may be provided with additional disclosures available on eVestment’s systems and other important considerations such as fees that may be applicable. Not for general distribution. All categories not necessarily included. Totals may not equal 100%. Copyright 2013-2023 eVestment Alliance, LLC. All Rights Reserved. Voya Investment Management composite peer rankings represent percentile rankings which are based on monthly gross of fee returns and reflect where those returns fall within the indicated eVestment’s universe. eVestment provides third party databases, including the institutional investment database from which the presented information was extracted. The eVestment institutional investment database consists of over 1,500 active institutional managers, investment consultants, plan sponsors, and other similar financial institutions actively reporting on over 10,000 products. Additional information regarding eVestment rankings for year to date and since inception performance of the composites is available on eVestment’s website. For more information about the rankings presented above, including universe and additional time periods, please see our detailed eVestment ranking slides.

Principal Risk

The strategy employs a quantitative investment process. The process is based on a collection of proprietary computer programs, or models, that calculate expected return rankings based on variables such as earnings growth prospects, valuation, and relative strength.

Data imprecision, software or other technology malfunctions, programming inaccuracies and similar circumstances may impair the performance of these systems, which may negatively affect performance. Furthermore, there can be no assurance that the quantitative models used in managing the strategy will perform as anticipated or enable the strategy to achieve its objective.

The principal risks are generally those attributable to bond investing. Holdings are subject to market, issuer, credit, prepayment, extension, and other risks, and their values may fluctuate. Market risk is the risk that securities may decline in value due to factors affecting the securities markets or particular industries. Issuer risk is the risk that the value of a security may decline for reasons specific to the issuer, such as changes in its financial condition. The strategy may invest in mortgage-related securities, which can be paid off early if the borrowers on the underlying mortgages pay off their mortgages sooner than scheduled. If interest rates are falling, the strategy will be forced to reinvest this money at lower yields. Conversely, if interest rates are rising, the expected principal payments will slow, thereby locking in the coupon rate at below market levels and extending the security’s life and duration while reducing its market value. High yield bonds carry particular market risks and may experience greater volatility in market value than investment grade bonds. Foreign investments could be riskier than U.S. investments because of exchange rate, political, economics, liquidity, and regulatory risks. Additionally, investments in emerging market countries are riskier than other foreign investments because the political and economic systems in emerging market countries are less stable.

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