Description: The paper demonstrates that the most popular rationalization for evolving glide paths is flawed and should be discarded. The paper also demonstrates that glide paths should generally evolve for investors that endeavor to optimize outcomes and reevaluate their portfolios regularly.

Description: While many know that machine learning is a big deal and even have a general idea of what it is, many do not know what machine learning can do for them. As an alternative to citing achievements or explaining algorithms, this article outlines the challenges that occur in statistics and the solutions that machine learning offers. Some of those challenges include correlated predictors, missing data, data interaction, and prediction intervals. Corresponding solutions include regularization technics, missing value imputation with KNN, tree based models, and cluster analysis for backtesting.

Description: U.S. bond markets have undergone dramatic changes due to the 2008 Global Financial Crisis (GFC) and the COVID-19 pandemic. In taking a retrospective view, we can see that bond markets, viewed through the lens of major bond indices, have been evolving for quite some time. Within this paper, TD Asset Management Inc. (TDAM) will explore underlying changes that have occurred within the U.S. Corporate Bond Index, a sub-component of the larger U.S. investment grade bond market, over the past decade. We will highlight key structural changes that have occurred within bond markets and why they are noteworthy

Description: Demographic challenges due to longevity increases and low fertility rates will lower economic growth as measured by GDP. By deconstructing GDP growth between population and productivity growth the article describes the problem and presents potential solutions. The article builds off an SOA research paper published in November 2023, Demographics and Productivity: Drivers of Economic Growth.

Description: Lifetime pension pools convert a lump sum into lifelong income, periodically adjusting benefit payouts based on mortality and investment experience. Volatility-targeting strategies can enhance benefit stability by dynamically adjusting the investment portfolio’s exposure to risky assets in the context of these pools, demonstrating superior performance compared to traditional static asset allocation methods.

Description: Letter from Investment Section chairperson discussing future plans for the section.

Description: Discussion of the new scenario generator selected by the NAIC and its behavior at low interest rates.

Description: Our previous article, “Introduction of Cashflow Matching Strategic Asset Allocation (SAA) Framework,” introduced the concept and included a real-world case study that developed a liability-driven investment strategy for a single line of business (LOB) for a life insurer. This article expands the framework and the case study from a single LOB to simultaneously optimize asset allocation across multiple LOBs. It discusses how this multi-line SAA framework can enable an insurance company to efficiently tag its asset holdings to each LOB, identify opportunities in the public and private asset markets to enhance risk-adjusted returns, and develop a deeper understanding of the trade-off between the degree of cashflow matching and risk-adjusted returns across LOBs.

Description: This article takes a look at how defined benefit (DB) pension plan financials ended the third quarter of 2023 on a solid footing, improving the capacity to take meaningful de-risking actions; as DB plans look to de-risk at reasonable costs, they may find it beneficial to consider a broad range of investment options; and completing a core bond allocation with private credit and income-oriented alternative strategies can help achieve important savings over other frequently pursued de-risking approaches, without materially increasing the funded status volatility or downside risk

Description: This is the second part of a 2 part series on Real options analysis (ROA). This article looks into the limitations of using financial option theory when doing real options analysis with projects that are long-dated and uncertain, such as: 1. First-degree homogeneity, 2. Uncertainty must derive from Brownian motion, and 3. Risk neutrality.