Retirement Investment Research Articles

Leveraging FinTech Compliance to Mitigate Cryptocurrency Volatility for Secure US Employee Retirement Benefits: Bitcoin ETF Case Study

The integration of cryptocurrencies, particularly Bitcoin, into retirement savings plans has recently garnered significant attention. This interest has been amplified by the U.S. Securities and Exchange Commission's approval of Bitcoin Exchange-Traded Funds (ETFs) in January 2024 and Fidelity Investments' decision to include Bitcoin in their 401(k) plans. These landmark developments represent a paradigm shift in retirement investment strategies, merging traditional financial planning with the dynamic and volatile world of cryptocurrencies. The entry of Bitcoin introduces novel challenges, including increased volatility and regulatory uncertainty, necessitating a comprehensive examination of its impacts on retirement savings. The study sought to explore the role of Financial Technology (FinTech) in managing these risks and assess the adequacy of current regulatory frameworks. Employing a quantitative research approach, the study collected data from 386 participants, including FinTech practitioners and investment portfolio managers through a survey that combining closed-ended and open-ended questions. Multiple regression was used to analyze the relationships between variables such as FinTech integration, regulatory compliance, and the risk associated with cryptocurrency-inclusive retirement portfolios. The study revealed that the inclusion of Bitcoin significantly increases portfolio volatility. It also found that advanced FinTech data management techniques significantly enhance risk mitigation, while current regulatory frameworks are inadequate for governing the inclusion of cryptocurrencies in retirement plans. A comprehensive framework combining FinTech and regulatory compliance was shown to effectively reduce investment risks. The study recommends cautious consideration of cryptocurrencies in retirement portfolios, with an emphasis on assessing the risk appetite of participants. It advocates for dynamic regulatory frameworks and enhanced use of FinTech for real-time risk management. The study suggests that retirement plan providers should adopt an integrated approach, combining technological innovations with regulatory oversight, to navigate the complexities of cryptocurrency investments effectively.

Does the source of money determine retirement investment choices?

Using a unique dataset of actual investment choices of Oregon State University employees, we investigate how investment choices differ among (1) the optional retirement plan (ORP) funded by the employer and (2) the investments in 403(b) accounts funded by employees themselves using voluntary salary reduction. We find that the level of risk associated with voluntary, salary reduction investments in 403(b) accounts is lower than the risk these same employees are currently taking in their employer funded 401(a) accounts. We also investigate whether the choice of the provider has a significant impact on the asset allocation chosen by the employees and find that participant investment choices in Fidelity are riskier than the choices made by those in TIAA-CREF.

Target date funds as asset market stabilizers: evidence from the pandemic

Abstract Target date funds (TDFs) provide retirement investors, many of whom are unsophisticated or inattentive, with age-appropriate exposures to different asset classes like stocks and bonds. To maintain exposures, TDFs trade actively against market returns, buying stock funds when the stock market does poorly, and selling when the market does well (Parker et al., 2023, Journal of Finance). This paper shows that trading by TDFs was a significant stabilizing force in US equity markets during the unprecedented economic volatility of the COVID-19 pandemic period. Specifically, TDFs – now comprising a quarter of all 401(k) plan assets – caused significant contrarian investment flows across asset classes, flows that were not undone by enrollment of TDF investors or by discretionary actions by TDF managers. Mutual funds with large ownership by TDFs had more stable funding through the pandemic, and stocks that had greater indirect ownership by TDFs had lower co-movement with the market and lower volatility during the pandemic period.

How risky is your retirement income risk model?


 
 
 Adequately sustaining lifetime income is a critical portfolio objective for retired investors. This article provides a brief review of various retirement income modeling approaches including historical back testing, Monte Carlo simulations, and other more advanced risk modeling techniques. Implau- sible assumptions underlying common risk models may mislead investors concerning the risk and return expectations of their retirement investment strategies. We compare risk models, evaluate their credibility, and demonstrate how an oversimplified model may distort the risks retired investors face. Differences in sustainability rates are stark: 4% failure at the low end versus 49% failure at the high end. The article ends with general comments regarding model risk and practitioner investment advice.
 
 

Investment Performance of Voluntary Pension Funds’ Portfolios

To ensure adequate retirement income it is usually recommended to save „more and for longer periods”. However, this is not enough. Consumers often overlook the importance of long-term returns on retirement investments. At the same time, the Bulgarians award a lower assessment for the market performance of the services „investment products and private personal pensions” compared to the average for the European Union. The present research aims to analyze the investment results of the voluntary pension funds in Bulgaria for the decade, marked by unprecedented low interest rates and pandemic.

Retail Financial Innovation and Stock Market Dynamics: The Case of Target Date Funds

ABSTRACTTarget date funds (TDFs) are designed to provide unsophisticated or inattentive investors with age‐appropriate exposures to different asset classes like stocks and bonds. The rise of TDFs has moved a significant share of retirement investors into macrocontrarian strategies that sell stocks after relatively good stock market performance. This rebalancing drives contrarian flows across equity mutual funds held by TDFs, stabilizing their funding, and reduces stock returns for stocks disproportionately held by these funds when stock market returns are relatively high. Continued growth in TDFs and similar investment products may dampen stock market volatility and increase the transmission of shocks across asset classes.

The Multi-Goal Framework: Why Practitioners Have Not Adopted the Lifecycle Model—Yet

Investors have multiple goals throughout their lifetime, each requiring complex interconnected decisions about saving, consumption, and asset allocation. Economists have developed a theoretical solution to solve for lifetime retirement income using stochastic dynamic programming. However, practitioner adoption of this approach has been limited. We theorize that this is due to the inability of stochastic dynamic programming to address multiple investor goals due to the inherent computational complexity in the approach. We put forward a life-cycle model incorporating multiple goals that are relevant for retirement investors in the presence of uncertain future asset returns and longevity. Our objective is to maximize investors’ expected utility over their lifetime. We use a goal fulfillment gap as a metric to quantify the value added by an optimized strategy, and to illustrate the optimal consumption and asset-allocation decisions recommended by the model.

Robo Tontines

Robo advisors provide financial advice and manage investment portfolios, using online software. However, they often do not give advice concerning the decumulation phase of retirement planning. Tontines are financial products that provide a stream of income for life in retirement and serve as an alternative to annuities. They are an old product that fell out of favor but is making a comeback. They differ from annuities because they are not guaranteed and, therefore, incur lower costs. The benefits they provide vary over time depending on the mortality experience of the members and the financial market experience of the investments. This article proposes a combination of these two innovative products in the form of a robo tontine—that is, a tontine provided by robo advisors. We argue that robo advisors would be well suited to provide tontines for both supply and demand reasons. They are skilled in developing and managing financial products, and they have clients who will need help with the paydown phase of their retirement investments.

A three-level analysis of values related to socially responsible retirement investments

ABSTRACT The aim is to investigate the value basis of Socially Responsible Retirement Investments (SRRI) in a study of Swedish pension investors in the age range 18 to 65 years (N=1005). Logistic regression analyses were performed with self-reported SRRI choice as dependent variable and different levels of values as independent variables. On a higher level of analyses, self-transcendent values, especially universalism (e.g., equality, protecting the environment, and social justice), have the most important influences on SRRI choice. In contrast, on a lower-level analysis, SRRI choice is influenced by self-enhancement values with high priority for authoritarian power and low priority for wealth. The three-level analysis of values (self-transcendence vs self-enhancement value orientation, motivational domain, and value) questions the contradiction between dimension poles of values and the structuring of values in interrelated motivational domains. The results thereby clarify some previous findings and increase the understanding of the value basis of SRRI.

Health State Risk Categorization: A Machine Learning Clustering Approach Using Health and Retirement Study Data

For countries such as the United States, which lacks a universal health care system, future health care costs can create significant uncertainty that a retirement investment strategy must be built to manage. One of the most important factors determining health care costs is the individual’s health status. Hence, categorizing individuals into meaningful health risk types is an essential task. The conventional approach is to use individuals’ self-rated health state categorization. In this work, the authors provide an objective and data-driven machine learning (ML)–based approach to categorize heath state risk by using the most widely used US household surveys on older Americans, the Health and Retirement Study (HRS). The authors propose an approach of employing the K-modes clustering method to algorithmically cluster on an exhaustive list of categorical health-related variables in the HRS. The resulting clusters are shown to provide an objective, interpretable, and practical health state risk categorization. The authors then compare and contrast the ML-based and self-rated health state categorizations and discuss the implications of the differences. They also illustrate the difficulty in predicting out-of-pocket costs based on self-rated health status and how ML-based categorizations can generate more-accurate health care cost estimates for personalized retirement planning. The results in this article open different avenues of research, including behavioral science analysis for health and retirement study.

Trading behavior of Swedish retirement investors during the COVID-19 pandemic

PurposeHow did investors in the Swedish Premium Pension System (PPS) react to the stock market shock ignited by the COVID-19 pandemic?Design/methodology/approachThe authors use fund-level data from the Swedish Pensions Agency on investment choices in the PPS. For each fund, the authors use monthly information on the number of investors and holdings' market value up to November 2020. The authors also use information on the total number of portfolio changes per day. For analyzing whether PPS investors reacted to the pandemic with claiming their pension, the authors use monthly data on the number of investors of a certain age group who initiate their public pension payment.FindingsTrades more than doubled, and shifted capital from equity funds to low risk interest funds. In economic terms, however, trading stayed at low levels–less than two percent of investors traded in March 2020 and there was no effect on pension withdrawals. The increased trading during the market tumult was disproportionately concentrated among investors in the top of the pension capital distribution.Research limitations/implicationsWith fund-level data, the authors cannot investigate what in particular made retirement investors stay calm in the midst of a severe market decline. Either, those investors have a long-term investment horizon as they save for their pension or particular features of the system's choice architecture induce inertia and discourage from trading. The sub-group analyses are more consistent with the explanation that PPS-induced inertia is responsible for the relatively small increase in trading activity, but future research could exploit individual level data to explore this in more detail.Practical implicationsThe often-criticized PPS choice architecture provided positive side effects in times of a severe market shock by shielding retail investors from committing trading mistakes when trying to outsmart the market.Originality/valueThe study complements previous evidence on the effects of COVID-19 on investor activity. The small response of PPS investors to COVID-19 is in line with earlier US findings on 401(k) accounts during the 2007 financial crisis (Tang et al., 2012) and industry reports about the COVID-19 period (see, e.g. Mitchell, 2020). The authors find no effects at all on public pension withdrawals in Sweden, while evidence from US 401(k) plans indicates a small share of workers taking COVID-related early withdrawals.

Can a Momentum Strategy Outperform the S&P 500 Index in a Retirement Plan?

The objective of this article is to explore the selection and rebalancing of mutual funds in the portfolio of individual retirement investors to enable their portfolios to outperform market indexes. Three interesting facts emerged from this analysis: (1) momentum strategy is better when rebalancing is done in shorter intervals; (2) momentum strategy works better for longer investment horizons; and (3) momentum strategy is better when funds are more broadly diversified. Analysis of the results indicates that retirees using the momentum strategy over long horizons can earn significant excess returns compared to those of the Standard and Poor’s (S&P) 500 index. The results suggest that if crafted carefully, a momentum strategy can help retirees improve the performance of their retirement portfolio over a traditional diversification strategy.

Practical Applications of An Analysis of the Performance of Target Date Funds

In <b><i>An Analysis of the Performance of Target Date Funds</i></b>, from the Spring 2021 issue of <b><i>The Journal of Retirement</i></b>, authors <b>John Shoven</b> and <b>Daniel Walton</b> (both of <b>Stanford University</b>) investigate whether target date funds (TDFs) have helped investors diversify their portfolios while protecting them from market losses. TDFs have become wildly popular with retirement investors, even though the vehicles suffered large losses during the financial crisis of 2008–2009. Shoven and Walton examined how TDFs have performed since then, with a focus on the stock market crash of February–March 2020. They find that TDFs with the longest-term target dates allocated 85%–90% of assets to stocks, while the shortest-term TDFs had 50% in stocks. This means TDFs reduce their stock holdings over time but still leave people exposed to market losses as they get near retirement. In fact, during the crash of 2020, TDFs with a target date of 2025 lost 20%–25% of their value. The authors therefore question whether TDFs work as one-size-fits-all retirement investments. As an alternative, they suggest that retirement plans could offer an array of balanced funds, encourage participants to fill out risk tolerance questionnaires, and allow plan participants to choose funds that fit their goals and circumstances.

Effect of uncertainty visualizations on myopic loss aversion and the equity premium puzzle in retirement investment decisions.

For many households, investing for retirement is one of the most significant decisions and is fraught with uncertainty. In a classic study in behavioral economics, Benartzi and Thaler (1999) found evidence using bar charts that investors exhibit myopic loss aversion in retirement decisions: Investors overly focus on the potential for short-term losses, leading them to invest less in riskier assets and miss out on higher long-term returns. Recently, advances in uncertainty visualizations have shown improvements in decision-making under uncertainty in a variety of tasks. In this paper, we conduct a controlled and incentivized crowdsourced experiment replicating Benartzi and Thaler (1999) and extending it to measure the effect of different uncertainty representations on myopic loss aversion. Consistent with the original study, we find evidence of myopic loss aversion with bar charts and find that participants make better investment decisions with longer evaluation periods. We also find that common uncertainty representations such as interval plots and bar charts achieve the highest mean expected returns while other uncertainty visualizations lead to poorer long-term performance and strong effects on the equity premium. Qualitative feedback further suggests that different uncertainty representations lead to visual reasoning heuristics that can either mitigate or encourage a focus on potential short-term losses. We discuss implications of our results on using uncertainty visualizations for retirement decisions in practice and possible extensions for future work.

The Association between Subjective and Objective Financial Knowledge: Path Analysis to Investor Behavior by Age

Financial literacy affects stock market participation, as well as individuals’ age, gender, income, and education level. However, measuring financial literacy is more appropriate to identify individuals with strong knowledge of finance rather than average individuals with general knowledge. This could be problematic to identify general participation of the stock market and investment as more individuals are now participating without having to have such knowledge. This study explored how individuals’ subjective financial skills and well-being affect investment participation by age. Overall, males are likely to participate more in both retirement and non-retirement investment. In between the boomer generation and younger group, the younger generation who reported participating in a non-retirement investment, such as stock market were having a higher score on subjective financial well-being (STDYX = .052, 95% CI [.07, .08]; p < .05). Importantly, among the older group, subjective financial skill score becomes a predictor of participating stock market (STDYX = .09, 95% CI [.01, .17]; p < .05). As the result suggest, while younger participants focus more on financial well-being, such as having security on finances, when they are participating in a non-retirement investment, whereas older adults are likely to invest based on their beliefs on financial skills regardless of secured finances. A retirement plan has shifted toward less on savings and more on investing. Older adults are now interested more in participating in investments, such as the stock market than the young population, and the proper preparedness for those older adults in participating in the investment is needed.

HARI: Characteristics of a new defined lifestyle (DL) retirement planning product

Approximately 16% of the world's population lives in countries with some concept of a financial retirement plan. Of the remaining population, many do not have access to a Western-style retirement system, and the concept of Dharma subliminally influences them. Dharma, an Eastern philosophical system, recommends Sanyasa (renunciation), instead of comfortable retirement life, as a life goal. This paper proposes a new defined lifestyle retirement planning instrument, referred to as Holistic Annual Retirement Investment (HARI), a standardized, tradable, futures contract that can alter the way individuals think of and plan for their retirement according to their belief system. HARI is a hypothetical product based on the Eastern value system and needs improvement ideas from other researchers. So, the reader is urged to be imaginative and forgiving.

Keep Calm and Do Nothing - Trading Behavior of Swedish Retirement Investors during the COVID-19 Pandemic

How did investors in the Swedish Premium Pension System (PPS) react to the stock markets shock ignited in 2020 by the COVID-19 pandemic? The share of investors that traded more than doubled, and trades shifted capital from equity funds to low risk interest funds. In economic terms, however, trading activity stayed at very low levels—less than two percent of investors traded in March 2020 and there was no effect on pension withdrawals. Given the vast evidence on retail investors’ strongly increasing trading volume in crisis times, the reaction of PPS investors looks surprisingly smart, i.e., avoiding the many mistakes that investors incur when they try to outsmart the market. Potentially, the often-criticized choice architecture of the PPS that induces strong inertia provided positive side effects in times of a severe market shock.

The Effects of Income Tax Timing on Retirement Investment Decisions

ABSTRACTIn an online experiment, the immediate (Roth) versus deferred taxation of retirement income affects taxpayers' investment decisions such that tax-deferred plan investors under-adjust for future tax burdens and overestimate their future wealth compared to Roth investors. When presented with a specific after-tax monetary goal, Roth account holders invest more in higher-risk, higher-return assets than tax-deferred account holders. We investigate four aspects of this investment context that could alleviate these differences: (1) implementing a “do-your-best” goal, (2) reframing specific goals in pre-tax dollars, (3) explicitly prompting investors to estimate future tax burdens, and (4) providing performance feedback. These interventions reduce differences between Roth and tax-deferred investor behaviors, but do not entirely close the gap on their own. In combination, reframing goals and prompting future tax estimations encourage tax-deferred account holders to invest in risky assets to the same degree as Roth investors only when paired with performance feedback.

Affectivity and riskiness of retirement investment decisions

PurposeDrawing on broaden-and-build theory and promotion- and prevention-focus theory, the authors examined the role of positive and negative affectivity (PANA) on the riskiness of investment decisions. The authors also examined the mediating impact of financial knowledge network intensity (i.e. the level of communication with financially literate others in employees' social network) on the PANA—riskiness of investment decisions relationship.Design/methodology/approachStudy 1 used a sample of undergraduate students and operationalized risk using a hypothetical investment scenario. Study 2 replicated and extended the Study 1 findings using employees and operationalized risk using their real-world investment allocations.FindingsBoth Studies 1 and 2 provided support for the negative direct relationship between NA and the riskiness of investment decisions. Study 2 found PA was marginally positively related to the riskiness of investment decisions. Financial knowledge network intensity mediated the relationship between NA and the riskiness of investment decisions in Study 2.Research limitations/implicationsThe findings suggest that employees who see the world in a generally negative light tended to have weaker financial knowledge networks, and this may be one mechanism that explains why they make low-risk investments.Practical implicationsFinancial knowledge networks can provide access to critical information regarding investment opportunities. Socialization training or social mixers can be used to help employees build and improve their financial knowledge networks.Originality/valueThe authors integrate the research on PANA, social networks, and investment decisions to illuminate the social network processes that explain how affectivity impacts the riskiness of retirement investment decisions.

Practical Applications of Utilizing Low-Volatility Assets to Mitigate Sequence Risk in Retirement Investing

<h3>Practical Applications Summary</h3> In <b><i>Utilizing Low-Volatility Assets to Mitigate Sequence Risk in Retirement Investing</i></b>, from the August 2019 issue of <b><i>The Journal of Investing</i></b>, <b>Wei Ge</b> of <b>Parametric Portfolio Associates</b> investigates the relationship between low-volatility assets and sequence risk in retirement investment portfolios. Ge finds that constructing a 60/40 portfolio in which the 60% growth asset allocation was invested in a low-volatility asset significantly reduced the uncertainty associated with retirement investment outcomes. This reduction in sequence risk was reflected in narrower final wealth ranges and reduced failure rates. Ge suggests that retirement plan managers incorporate low-volatility assets into the portfolios they manage in order to mitigate sequence risk. <b>TOPICS</b>: Retirement, portfolio construction, simulations, performance measurement