Latest Research

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How Long is Long Enough?

Defined Contribution (DC) Plan (DCP) fiduciaries are often faced with conflicting perspectives when it comes to executing their responsibilities and terminating underperforming active managers.  Consultants, academics, investment managers and capital market intermediaries generally argue that more time is needed to prove an investment strategy is suboptimal. These parties often have inherent conflicts of interest to argue for active management over passive management. Most conflicts are economic in nature, but some are steeped in intellectual hubris. In this article we enter the fray from the plan participants’ (PP) side. Ultimately, the very essence of a DCP is to offer a menu of investment options that enable PP to optimize wealth aggregation in a diversified manner using a multi-asset class solution. We show that PP are better served when fiduciaries monitor active investment managers and replace them with passive alternatives in a timely manner if they underperform. Too often plan fiduciaries churn a DCP by replacing underperforming active funds with other active funds. 

What History Can Teach Us About Building an Optimal Retirement Plan

The purpose of this paper is to explore ways to incrementally improve the design of retirement plans. Specifically, we discuss ways to blend the better characteristics of defined benefit plans with those of the defined contribution framework in a manner that has the potential to more optimally balance the needs of the individual plan participant. The blended approach contains periods of traditional wealth maximization that enables the investor to opportunistically capture future income streams throughout their working years. As the income is captured the associated investment liability is also transferred to the income provider. Such a structure would offer participants the benefits of the current DC framework plus the possibility of transitioning into a lifetime income solution as retirement approaches. We also present several means available to employers and the capital markets to facilitate the development of such a product

Active Management in Defined Contribution Plans

We analyze the problem that fiduciaries face when monitoring and selecting from a universe of active mutual funds within a defined contribution (DC) plan. In a DC plan a fiduciary must recognize that there are two levels of decision makers, namely the fiduciary who decides which funds will comprise the DC plan and the individual plan participants who must decide which funds to invest in and the timing of their investment. Moreover, plan participants, and to some degree the fiduciary, need to be able to make investment decisions without being an investment professional.

We find that due to the general lack of consistency in performance of mutual funds, fiduciaries and plan participants would be better served by selecting passive rather than active funds across the US equity mutual fund space. Moreover, the most consistently outperforming funds tend to have meaningfully higher tracking errors relative to their stated benchmarks which makes effective asset allocation in a DC plan more difficult.

Forthcoming in the Journal of Retirement, Winter 2020.

Introducing the Power Series Method to Numerically Approximate Contingent Claim Partial Differential Equations

We introduce a previously unused numerical framework for estimating the Black-Scholes partial differential equation. The approach, known as the Power Series Method (PSM), offers several advantages over traditional finite difference methods. The PSM is more stable than explicit methods and thus computationally more efficient. It is as accurate as hybrid approaches like Crank Nicolson and faster to compute. It is more accurate over a far wider spectrum of time steps. Finally, and importantly, it can be expressed analytically thus offering the capability of performing comparative statics in a far more stable and accurate environment. For more complex application this last advantage may have wide implications in producing hedge ratios for synthetic replication purposes.

Journal of Mathematical Finance, Fall 2019.

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