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We propose target date funds modified to exploit stock return predictability driven by the variance risk premium. The portfolio rule of these tactical target date funds (TTDFs) is extremely simplified relative to the optimal one, making it easy to implement and to communicate to investors. We show that saving for retirement in TTDFs generates economically large welfare gains, even after we introduce turnover restrictions and transaction costs, and after taking into account parameter uncertainty. This predictability also appears to be uncorrelated with individual household risk, suggesting that households are in a prime position to exploit it. This paper was accepted by Tomasz Piskorski, finance.

Demographic changes increase the necessity to base the pension system more and more on the second and the third pillar, namely the occupational and private pension plans; this paper deals with Target Date Funds (TDFs), which are a typical investment opportunity for occupational pension planners. TDFs are usually identified with a decreasing fraction of wealth invested in equity (a so-called glide path) as retirement comes closer, i.e., wealth is invested more risky the younger the saver is. We investigate whether this is actually optimal in the presence of non-tradable income risk in a stochastic volatility environment. The retirement planning procedure is formulated as a stochastic optimization problem. We find it is the (random) contributions that induce the optimal path exhibiting a glide path structure, both in the constant and stochastic volatility environment. Moreover, the initial wealth and the initial contribution made to a retirement account strongly influence the fractional amount of wealth to be invested in risky assets. The risk aversion of an individual mainly determines the steepness of the glide path.

This paper studies how professional asset allocators such as endowments, fund-of-funds, or pension funds select fund managers for investments. We develop a simple model of their due-diligence process to motivate predictions about the timing of investment decisions. We then test these predictions using a unique dataset with detailed information on the interactions between a large institutional investor and 1,093 hedge funds over the course of 8 years. Soft information conveyed during the meetings with fund managers strongly influences the decisions. A one standard deviation increase in our proxy for positive soft information doubles the probability of fund selection and reduces the due-diligence time by 20%. Contrary to prior research, we find no evidence that relying on these subjective judgements is wasteful. Instead, in a matched sample, conditioned on the fund characteristics and past performance, the 12-month average peer-adjusted returns are 1.5% higher for the selected funds.

Although target date mutual funds (TDFs) have only been around since the mid-1990s, they are now common vehicles for retirement investing. Sixty percent of US companies now automatically funnel employees’ non-directed retirement funds into TDFs, which account for nearly one-quarter of all savings US workers have in 401(k)s. Helping investors pick among TDFs, Morningstar rates past risk-adjusted performance using a star system and provides forward-looking evaluations of more than 2,500 TDFs using either Analyst Ratings or a newly implemented machine-learning-based Quantitative Ratings. Morningstar assigns Analyst Ratings to a smaller subset of TDFs that tend to have been in existence the longest and have the largest size. We find that TDFs with lower fees have significantly higher star ratings than their higher expense counterparts. No-load TDFs have significantly higher star ratings than their load-charging counterparts. In assessing future fund prospects, TDFs with low expense ratios are favored by both analysts and artificial intelligence. TDFs without load charges have significantly better Quantitative Ratings than their load charging counterparts. TDFs with Quantitative Ratings tend to be smaller, younger, and have poorer prior performance than TDFs with Analyst Ratings. TOPICS:Long-term/retirement investing, mutual funds/passive investing/indexing, information providers/credit ratings Key Findings ▪ Target date funds (TDFs) with low expenses and without load charges have significantly higher Morningstar star ratings of past risk-adjusted performance. These same low-cost funds have higher Morningstar Analyst ratings and Quantitative ratings, which estimate future fund prospects of performance. ▪ Regression results suggest Morningstar’s two forward-looking fund ratings are not perfect substitutes. Analyst ratings weight fund expense and fund age more heavily (both negatively) while the computer-generated Quantitative ratings are more positively influenced by past fund performance. ▪ Morningstar’s star ratings, Analyst ratings, and Quantitative ratings all suggest that retirement investing will result in a larger nest egg when attention is restricted to no-load, low-expense TDFs. Additionally, the ratings suggest investors should favor larger but relatively younger funds.

This article presents a thorough evaluation of target date funds for the period 2010–2020. Target date funds have grown enormously in assets, reaching $1.4 trillion at the end of 2019, and account for approximately 24% of all assets in 401(k) accounts. We report on the results of a style analysis evaluation of TDFs that determines their effective asset allocation. It examines both the constant in the style analysis regressions and resulting Sharpe ratios, which reflect the over- or under-performance of the funds relative to a passive benchmark with the same asset allocation. Lower cost TDFs tend to match the benchmark returns, while higher cost TDFs deviate from them considerably. We examine how TDFs performed in the stock market crash between February 19 and March 23, 2020, during which five-week period broad market averages fell by about one-third. We find that the value of long-dated TDFs (those with a target date of 2045 and beyond) fell by between 30% and 35%, while the 2025 funds, designed for people roughly 60 years old, lost between 20% and 25% of their value. We find that past performance only weakly influences future expected performance. As with equity funds in general in this period, TDFs with actively managed ingredient funds, on average, trailed the performance of their cheaper passively managed counterparts. TOPICS:Pension funds, portfolio theory, risk management, performance measurement Key Findings ▪ Even near term TDFs have considerable equity exposure. For instance, 2025 TDFs lost between 20 and 25% of their value in the five weeks between February 19 and March 23, 2020. Many longer horizon TDFs did no better than pure equity funds in this period. ▪ 75% of actively managed TDFs failed to do as well as the best fitting set of reference ETFs. ▪ Past performance is only a weak predictor of future performance for TDFs. An extra 1% per year return in 2010–14 period only increases the expected return in 2015–19 by 9 basis points per year.

This paper introduces a portfolio construction framework for risk-averse investors that aim to meet or exceed a client’s capital accumulation needs for a future event, such as retirement. Risk Capacity Portfolio Construction (RCPC) presents a risk-optimized alternative to Target Date Funds (TDFs). Risk Capacity Portfolio Construction is an economic sciences innovation that is validated by Skew-Risk Modeling, which was first presented in Targeted Return Portfolio Construction (Sherwood, 2019) and is detailed within this paper in its application to retirement-focused investors. Risk Capacity Portfolio Construction factors skewness and kurtosis into the risk management and asset allocation of an individual’s life cycle and can optimize risk beyond simply accounting for the equity risk premium and human capital. TOPICS:Portfolio theory, wealth management, retirement, risk management, portfolio construction, options, equity portfolio management, tail risks Key Findings ▪ This paper highlights an alternative portfolio construction methodology to Target Date Funds (TDFs) in order to better prepare individuals for retirement, on both a risk-adjusted and absolute basis. ▪ This paper highlights an investor’s ability to incorporate skewness and kurtosis within the asset allocation process of a portfolio that is intended to prepare an individual or group for a future dated event. ▪ This paper highlights how the implied risk probabilities within the options market, referred to herein as Tail Risk Ratios (TRR), can be incorporated in the investment process.

The benefit of investment advice depends on the quality of advice and the investor's counterfactual portfolio. We use changes in the Oregon University System Optional Retirement Plan to highlight the impact of plan design on the counterfactual portfolios of advice seekers. When brokers are available and target date funds (TDFs) are not, brokers help participants with high predicted demand for advice bear market risk, but they recommend higher-commission options. When brokers are removed and TDFs are added, new high-predicted-demand participants primarily invest in TDFs, which offer similar market risk but higher Sharpe ratios than the broker-advised portfolios within our sample.

By analyzing the portfolio allocations of target date funds (TDFs), we document that the observed durations of TDF portfolios are inconsistent with the durations predicted by classical portfolio theory. We call this stylized fact the duration puzzle. We investigate to what extent several extensions of classical portfolio theory can explain the duration puzzle. More specifically, we consider the impact of human capital, inflation risk, and portfolio restrictions on the duration of the optimal portfolio. We find that it is difficult to explain the duration puzzle, especially for individuals aged between 35 and 65 years.

The authors compare the performance of retirement portfolios using the average glide path of five popular target date funds to general rules of thumb for asset allocation. Surprisingly, the industry average target date fund has similar return and risk as the “120 minus your age rule”. In addition, a simple “140 minus your age rule” produces greater expected savings at retirement and a lower failure rate for average US investors retiring in their early 60s. A naive approach such as the “120 minus your age” rule or the “140 minus your age” can benefit average US employees by reducing transaction costs, improving retirement balances and increasing the probability of a comfortable retirement through an easy-to-understand investing rule. TOPICS:Wealth management, retirement, performance measurement, portfolio construction Key Findings • Rule of thumb asset allocation strategies such as 120 minus your age rule and 140 minus your age rule are superior to the industry average glide path in terms of retirement balances and failure rates. • Target date fund glide paths tend to perform better than rules of thumb only for investors retiring in their late 60s and receiving social security payments or those willing to take a reduction in their retirement income. • Rule of thumb strategies are easy to understand and save transaction costs over an average industry glide path.

To supplement retirement benefits received from public and private pension systems, individuals need to make voluntary contributions and decide how to efficiently invest these contributions. In this article, the authors analyze the problem of how to secure minimum levels of replacement income in retirement while offering attractive probabilities of reaching higher levels. Such strategies can offer an interesting alternative to target date funds, which have no focus on the generation of replacement income, or annuities, which can be used to secure replacement income but at the cost of substantial rigidity. TOPICS:Retirement, pension funds, wealth management Key Findings • Goal-based investing principles can be used to create retirement solutions that secure a minimum level of replacement income while delivering a high probability of reaching higher levels defined as aspirational goals. • These “flexicure” retirement solutions use a dedicated safe portfolio, known as a retirement goal-hedging bond portfolio (or retirement bond in short), which is a fixed-income portfolio whose cash flows (or factor exposures) match those of the stream of replacement income for a fixed period of time, say 20 years, in retirement. • Such strategies use liquid building blocks, they reliably secure a clearly identified replacement income goal without requiring ad hoc parametric assumptions, and they offer upside potential; as such they represent an attractive alternative to existing retirement products such as annuities or target date funds.

This paper investigates dynamic and causal relations between stock returns and mutual fund flows in Korea using a system method that utilizes information from the stock, bond, and money markets. Fo...

This paper quantifies the business cycle effects and distributional implications of pension fund restoration policy after the economy has been hit by a financial shock. We extend a canonical New-Keynesian dynamic general equilibrium model with a tractable demographic structure and a pension fund. Numerical simulations show that economies with pension funds that primarily write off accumulated pension wealth to restore financial adequacy behave similarly to an economy without a pension fund. Significant deviations from laissez-faire arise when the pension fund increases the pension fund contribution rate to close the funding gap or postpones the closure of the funding gap. At a cost of significantly distorting aggregate labour supply and output, the pension fund can shelter the group of retirees from unanticipated shocks by guaranteeing the value of their accumulated pension wealth. A defined benefit pension fund can be welfare improving to the group of agents that is already born in the period the financial shock hits. However, since pension funding gaps are typically closed over an extended period of time, a part of the welfare gains to currently alive agents comes at the expense of future, currently unborn, generations.

Little is known about whether employee retirement saving patterns change when public sector employers implement Target Date Funds (TDFs) as the default plan investment. We use administrative and survey data from a large government entity to track participation, contributions, and asset allocation impacts of TDF introduction. We show that those mapped into TDFs did not alter their holdings so that the reform resulted in higher equity shares, especially for women, younger workers, and low‐seniority employees. The least risk‐tolerant and financially literate employees held 12 percentage points more equity than previously. Moreover, defaulting public employees into TDF had a profoundly sticky effect on their subsequent investment behavior.

We study optimal life-cycle portfolio allocation and its application to target-date fund (TDF) design. We show that optimal TDF allocation must be explicitly linked to a savings rate; for example, a higher savings rate generating higher financial wealth accumulation should necessarily come with a more conservative TDF. Further, we quantify the extent to which accumulated wealth, the investing environment, and participant characteristics affect TDF allocations and compare the resulting optimal allocations against the observed universe of US TDF products. Plan sponsors and asset managers can use these findings to improve TDF selection and design. Key Findings ▪ We quantify how observed savings rates in 401k plans affect a TDF’s optimal allocation. Using a state-of-the-art life-cycle academic model, we find strong effects: for a moderately risk-averse participant, a halving in savings rate from 10% to 5% increases its optimal equity allocation by 10%–15%. ▪ We document the effects of real-life variations in other key determinants of TDF optimal allocations: participant’s risk aversion, relation between wages and equity returns, outside retirement income, start of savings, and expected returns. We measure the resulting wealth and consumption experience at and in retirement. ▪ We set these optimal glide paths against the glide paths pursued by US TDF mutual funds and observe a much narrower range for the observed ones, thus leaving some constituencies without an appropriate investment choice. Further, the optimal glide paths tend to slow the equity decline as they approach retirement; most observed ones do the opposite.

Target date funds (TDFs) are becoming increasingly popular investment choices among investors with long-term prospects. Examples include members of superannuation funds seeking to save for retirement at a given age. TDFs provide efficient risk exposures to a diversified range of asset classes that dynamically match the risk profile of the investment payoff as the investors age. This is often achieved by making increasingly conservative asset allocations over time as the retirement date approaches. Such dynamically evolving allocation strategies for TDFs are often referred to as glide paths. We propose a systematic approach to the design of optimal TDF glide paths implied by retirement dates and risk preferences and construct the corresponding dynamic asset allocation strategy that delivers the optimal payoffs at minimal costs. The TDF strategies we propose are dynamic portfolios consisting of units of the growth-optimal portfolio (GP) and the risk-free asset. Here, the GP is often approximated by a well-diversified index of multiple risky assets. We backtest the TDF strategies with the historical returns of the S&P500 total return index serving as the GP approximation.

Regulations often cause concurrent changes to both disclosure and enforcement, meaning that companies will be subject to different disclosure requirements and to a different likelihood of being penalized for any infractions. Because these changes are implemented concurrently, it is difficult to determine how each factor affects the outcomes of the regulation. Recent US hedge fund regulation provides a unique setting to examine this question because, among the funds affected by the mandatory regulation, some were only subject to disclosure requirements, some only to increased enforcement, and others to both disclosure and increased enforcement. Using three shocks that caused hedge funds to be regulated, then deregulated, and then regulated again, I first document that mandatory hedge fund regulation as a whole reduces misreporting. Then, more relevant to my research question, I find that the decrease in misreporting is driven by the mandatory disclosure portion of the regulation.

Target date funds (TDFs) provide a simple way to obtain an asset allocation that matches the current and future needs of an average investor with a specific retirement date. This article examines the differences between TDFs with the same target date but from different fund providers and finds considerable differences in asset allocations, risk, performance, and other fund characteristics. These differences are partially predictable based on the information in fund prospectuses; however, TDFs often deviate from the planned asset allocations. Investors and advisors should be aware that TDFs with the same target date can vary dramatically, warranting additional research when selecting between TDFs and then monitoring chosen TDFs’ asset allocations in the future. Potential solutions to these concerns include increased guidance from regulators, greater discernment from employers in employer retirement plan investment options, and more descriptive fund names. TOPICS:Retirement, portfolio construction, performance measurement, legal/regulatory/public policy

Individuals preparing for retirement are currently left with an unsatisfactory choice between security with no flexibility with annuity products and flexibility without security with investment products such as balanced funds or target date funds. To get out of this impasse, the authors introduce a range of flexicure retirement goal-based investing strategies that offer both security and flexibility with respect to the objective of generating replacement income in decumulation. Recent advances in financial engineering and digital technologies make it possible to apply goal-based investing principles to a much broader population of investors than the few traditional clients who can afford customized mandates or private banking services, which suggests that these flexicure retirement solutions can be used as part of the solution to the global pension crisis. TOPICS: Long-term/retirement investing, portfolio construction, quantitative methods

Given any set of exogenously provided efficient portfolios, we develop a dynamic programming algorithm that constructs an optimal portfolio trading strategy to maximize the probability of attaining an investor’s specified goal wealth at the end of a designated timeframe. Our algorithm can also accommodate periodic infusions or withdrawals of any size with no degradation in runtime performance. We explore how the terminal wealth distribution is sensitive to restrictions on the segment of the portfolio’s efficient frontier made available to the investor. Because our algorithm’s optimal strategy is on the efficient frontier, allowed to depend on the investor’s wealth, and allowed to depend on the investor’s individual goals and specifications, we show that it soundly beats the performance of target date funds for attaining investors’ goals. These optimal goals-based wealth management strategies are useful for modern day FinTech offerings, both advisor-driven or robo-driven.

We examine, for various educational characteristics of hedge fund managers, the performance profile of hedge fund portfolios along their managers’ professional experience path. We find that during the initial years following their graduation, hedge fund managers who majored in business or economics outperform other managers. However, in subsequent years, hedge fund managers who studied science or engineering improve their performance and eventually outperform all other managers. These results are consistent with the view that business education is a substitute for, while science education is a complement to, job experience in acquiring the skills that help hedge fund managers generate excess returns. Consistent with Chevalier and Ellison’s (1999b) findings for mutual fund managers, we find a positive and significant relation between the academic ability of hedge fund managers (as measured by the average SAT scores of the students in the school that the managers attended) and their fund performance. However, a significant positive relation does not exist between fund performance and other school characteristics such as tuition, school ranking, and student-faculty ratio.

The authors describe and showcase a framework to analyze life-cycle, or target-date, investment strategies with intuitive, practical metrics. Anchored in the complex theory of life-cycle investing, we propose a comprehensive collection, or “dashboard,“ of measures to capture various aspects of the problem: wealth-focused versions of return and risk concepts; the link between retirement contributions and portfolio returns; the strategy’s ability to support income in retirement; and behavior around retirement, a period when risk to invested wealth is greatest. These metrics are synthesized into one holistic view based on investor-specific preferences, highlighting the connection between investor characteristics and the life-cycle investment problem. TOPICS:Wealth management, long-term/retirement investing, pension funds

Traditional employer-sponsored defined-benefit pension plans in the private sector that provided lifetime benefits have declined precipitously since 1985. They have been largely replaced by Section 401(k) plans in which investment control, market risk and longevity risk have been transferred from the employer to the participant. Most participants opted for the low-yielding money market plan default option, which proved inadequate for providing viable retirement income. The Pension Reform Act of 2006 made two important changes to 401(k) plans: (1) allowed automatic enrollment and (2) allowed target-date funds as a “qualified default investment alternative.” This article examines the evolution from defined-benefit pensions to target-date funds and the closely related collective investment trusts.

We propose an approach to portfolio management over a finite time horizon that (i) does not require the precise knowledge of the underlying probability distributions, instead relying on range forecasts for the stock returns, and (ii) allows the fund manager to capture the degree of the investor’s risk aversion through a single, intuitive parameter called the budget of uncertainty. This budget represents the worst-case number of time periods with poor performance that the investor is willing to plan for. An application of this setting is target-date funds for pension fund management. We describe an efficient procedure to compute the dynamic allocation between (riskless) bonds and (riskier) stocks at each time period, and we illustrate the risk-to-time-horizon tradeoff on optimal allocation tables, which can easily be provided to fund participants to help them select their strategy. The proposed approach refines rules implemented by practitioners and provides an intuitive framework to incorporate risk in applications with end of horizon effects. In contrast with existing literature providing robust fund management approaches to mathematically sophisticated finance professionals, our goal is to provide a simple framework for less quantitative fund participants who seek to understand how stock return uncertainty and planned retirement date affect the optimal stock-vs-bond allocation in their portfolio. We extend our procedure to the case when the investor’s wealth is penalized for falling short of performance benchmarks across the time horizon. We also discuss the case where the manager can invest in multiple stocks. Numerical results are provided.

In this paper we consider the problem of choosing the optimal pension fund in the second pillar of Lithuanian pension system by providing some guidelines to individuals with defined contribution pension plans. A multistage risk-averse stochastic optimization model is proposed that can be used to plan a long-term pension accrual under two different cases: minimum and maximum accumulation plans as possible options in the system. The investment strategy of personal savings is based on the optimal solutions over possible scenario realizations generated for a particular participant. The concept of the risk-averse decision-maker is implemented by choosing the conditional value at risk as the risk measure defined by a nested formulation that guarantees the time consistency in the multistage model. The paper focuses on three important decision-making moments corresponding to the duration of periods to be modelled. The first period is a short-term accumulation, while the second period is a long-term accumulation with possibly high deviation of objective function value. The third period is designed to implement the concept of target date fund in the second pillar pension scheme as the subsequent need to protect against potential losses at risky pension funds. The experimental findings of this research provide insights for individuals as decision-makers to select pension funds, as well as for policy-makers by revealing the vulnerability of pension system.

Managing equity volatility exposure is fundamental to fund managers, insurance companies and pension funds. This is especially important for product developments including target-date portfolios and variable annuities where volatility management is critical. Empirical evidence shows asymmetry between equity market return and volatility, with returns and conditional volatility negatively correlated. We develop an approach that targets constant volatility in equity market portfolios and assess its performance with U.S., U.K., German and Australian data focusing on long term accumulation investment strategies popular with DC pension plans. Our approach to volatility management is univariate, in contrast to most of the existing approaches in the literature that are multivariate and more complex. Of particular relevance to pension funds is that we show substantial risk adjusted outperformance (in the range of an additional 100 to 350 basis points on average) relative to stock market index benchmarks, after transaction costs. Other features of the targeted constant volatility portfolios, relevant to insurers and pension funds, are a significantly reduced exposure to stock market crashes and low transaction costs relative to other approaches.

Insurers and pension funds face the challenges of historically low interest rates and volatility in equity markets, that have been accentuated due to the COVID-19 pandemic. Recent advances in equity portfolio management with a target volatility have been shown to deliver improved on average risk adjusted return, after transaction costs. This paper studies these targeted volatility portfolios in applications to equity, balanced and target-date funds with varying constraints on leverage. Conservative leverage constraints are particularly relevant to pension funds and insurance companies, with more aggressive leverage levels appropriate for alternative investments. We show substantial improvements in fund performance for differing leverage levels and that the return per unit of risk is not significantly impacted by the leverage constraint. Of most interest to insurers and pensions funds, we show that the highest return per unit of risk is in targeted volatility balanced portfolios with equity and bond allocations. Furthermore, we demonstrate the outperformance of targeted volatility portfolios during major stock market crashes, including the crash from the COVID-19 pandemic.

The problem of multistage allocation is solved using the Target Date Fund (TDF) strategy subject to a set of restrictions which model the latest regulatory framework of the Mexican pension system. The investment trajectory or glide-path for a representative set of 14 assets of heterogeneous characteristics is studied during a 161 quarters long horizon. The expected returns are estimated by the GARCH(1,1), EGARCH(1,1), GJR-GARCH(1,1) models, and a stationary block bootstrap model is used as a benchmark for comparison. A fixed historical covariance matrix and a multi-period estimation of DCC-GARCH(1,1) are also considered as inputs of the objective function. Forecasts are evaluated through their asymmetric dependencies as quantified by the transfer entropy measure. In general, we find very similar glide-paths so that the overall structure of the investment is maintained and does not rely on the particular forecasting model. However, the GARCH(1,1) under a fixed historical covariance matrix exhibits the highest Sharpe ratio and in this sense represents the best trade-off between wealth and risk. As expected, the initial stages of the obtained glide-paths are initially dominated by risky assets and gradually transition into bonds towards the end oof the trajectory. Overall, the methodology proposed here is computationally efficient and displays the desired properties of a TDF strategy in realistic settings.

The paper examines Target Date Fund glidepath construction as well as asset allocation strategies. We consider characteristics, features, and assumptions in solving the multi-period portfolio selection problem. This paper discusses the theoretical underpinnings of deterministic, adaptive, and stochastic models as well as some interesting alternative strategies. Furthermore, we also propose research topics for future consideration that the author believes may improve upon the existent model frameworks.

The bulk of 401(k) assets were invested in stocks. On average, at year-end 2018, 63 percent of 401(k) participants’ assets were invested in equity securities through equity funds, the equity portion of balanced funds, and company stock. Twenty-eight percent of assets were in fixed-income securities such as stable value investments, bond funds, money funds, and the fixed-income portion of balanced funds. More 401(k) plan participants held equities at year-end 2018 than before the financial market crisis (year-end 2007), and most had the majority of their accounts invested in equities. For example, about three-quarters of participants in their twenties had more than 80 percent of their 401(k) plan accounts invested in equities at year-end 2018, up from less than half of participants in their twenties at year-end 2007. Overall, more than 90 percent of 401(k) participants had at least some investment in equities at year-end 2018. More than three-quarters of 401(k) plans, covering more than three-quarters of 401(k) plan participants, included target date funds in their investment lineup at year-end 2018. At year-end 2018, 27 percent of the assets in the EBRI/ICI 401(k) database were invested in target date funds and more than half of 401(k) participants in the database held target date funds. Also known as lifecycle funds, these funds are designed to offer a diversified portfolio that automatically rebalances to be more focused on income over time. In an ongoing collaborative effort, the Employee Benefit Research Institute (EBRI) and the Investment Company Institute (ICI) collect annual data on millions of 401(k) plan participants as a means to examine how these participants manage their 401(k) plan accounts. This report is an update of EBRI and ICI’s ongoing research into 401(k) plan participants’ activity through year-end 2018. The report is divided into four sections: the first describes the EBRI/ICI 401(k) database; the second presents a snapshot of participant account balances at year-end 2018; the third looks at participants’ asset allocations, including analysis of 401(k) participants’ use of target date, or lifecycle, funds; and the fourth focuses on participants’ 401(k) loan activity.

We study optimal life-cycle portfolio allocation and its application to target-date fund (TDF) design. We show that optimal TDF allocation must be explicitly linked to a savings rate; for example, a higher savings rate generating higher financial wealth accumulation should necessarily come with a more conservative TDF. Further, we quantify the extent to which accumulated wealth, the investing environment, and participant characteristics affect TDF allocations and compare the resulting optimal allocations against the observed universe of U.S. TDF products. Plan sponsors and asset managers can use these findings to improve TDF selection and design.

This paper considers investors who are looking to maximize their probability of remaining solvent throughout their lifetime by using an algorithm that aims to optimize their investment allocation strategy and optimize their tax strategy for withdrawal allocations between tax deferred accounts (TDAs), Roth accounts, and taxable stock and bond accounts. This optimization works with stochastic investment returns and stochastic mortality, extending and combining different investment and tax-efficiency paradigms. We find that optimizing the investment strategy has a much larger impact on the investor remaining solvent than optimizing the tax strategy. This result is key to effectively optimizing both strategies simultaneously. This optimized investment strategy soundly beats a standard target date fund strategy, and the novel optimized tax strategy displays optimal desired properties suggested by non-stochastic tax optimization research.

We document a reduction in both the level and cross-sectional dispersion of systematic risk in the target-date fund (TDF) market after 2008, which resulted in better performance of TDFs during the COVID-19 selloff compared to the 2008 selloff and a reduction in TDF return dispersion. We find that the shift is more pronounced in close-to-retirement funds and driven by the TDF series investing more in equities in the early period, consistent with TDFs catering to the market demand for lower risk exposure after the 2008 crisis. In addition, TDF systematic risk shifters do not exhibit more idiosyncratic risk-taking.

Pension program participants need an effective pension plan that can give them adequate income replacement to maintain a similar standard of living in retirement. However, the Financial Services Authority report from 2015–2018 reveals that the voluntary pension program participants in Indonesia tend to be riskaverse. They prefer lower risks and lower returns; as shown in the total portfolio, only 3.9% is invested in a riskier instrument with potentially higher returns like stocks while the rest investments are in the money market and fixed income. In countries where the pension industry is more advanced, like the United States, UK, and Canada, pension managers offer target date funds (TDF) for participants who seek to grow assets over a specified period. At the time this study was done, there was no TDF in the Indonesia pension market nor research in Indonesia that focused on them. The objective of this study is to find out whether TDF improves the pension investment returns, TDF response to volatility in the capital market, and TDF cost efficiency. The methodology of this study was a documentary analysis and scenario observation of what the results would be if TDF applies Indonesian capital market historical data. Therefore, the conclusions are rather indicative than definitive. The scenario considered two hypothetical glide paths taken from the U.S. TDF universe, the maximum and the minimum allocation of stocks in the portfolio. The data used Jakarta stock exchange composite index to represent the growth objective in TDF and time deposit to serve the stability objective. The result indicated all of the TDF approaches during the accumulation period had higher average end balances with no worst-case end balances.

The rise of Target Date Funds (TDFs) has moved a significant share of retail investors into contrarian trading strategies that rebalance between stocks and bonds so as to maintain age-appropriate portfolio shares. We show that i) TDFs actively rebalance within a few months following differential asset-class returns to maintain stable portfolio shares, ii), this rebalancing drives contrarian rebalancing flows across funds held by TDFs, iii) investors do not move funds into or out of TDFs to offset these flows, and iv) these flows impact the prices of stocks. Across otherwise similar stocks, those with higher (indirect) TDF ownership experience lower returns after higher market-wide performance, a results that holds when looking only at variation in TDF ownership driven by S&P index inclusion. Consistent with this price impact, the stock market exhibits more reversion at the monthly frequency during the recent TDF era. Together, our results suggest that continued growth in TDFs may affect return dynamics and the relation between stock and bond returns.

We analyze the behavior of 401(k) plan participants during the first quarter of 2020, when COVID-19 generated historic volatility, large negative returns, and significant unemployment. Only 2.1% of participants invested in TDFs made any changes to their portfolios, with even lower rates of change among those defaulted into robo-advised managed accounts, suggesting that delegation can decrease the likelihood of portfolio mistakes by less sophisticated participants. While 16.6% of non-delegated participants made portfolio changes, these changes were more likely among more sophisticated participants and appear not to have reduced participants’ quarterly returns. Consistent with liquidity constraints, however, withdrawals spike following job loss.

Target-date funds (TDFs) are popular vehicles that provide investors with an evolving asset allocation to meet their needs at some future date (e.g., retirement). While TDFs provide investors with extensive diversification and active rebalancing, TDFs are also a type of fund-of-funds. As such, investors pay multiple layers of fees as most TDFs charge fund-of-funds' fees and also hold funds that collect additional fees. We show that TDFs are easy to emulate with a portfolio of cost-efficient exchange-traded funds (ETFs) and we coin these portfolios Replicating Funds (RFs). RFs substantially outperform TDFs, exhibit low tracking error, do not suffer from cash drag, and require infrequent rebalancing. Our analysis shows that TDF sponsors collectively charged nearly $2.5 billion in excess fees in 2017 alone. We provide a normative rule-of-thumb for investors to construct their own RFs using low-cost ETFs.

We document an overall trend of reduced risk exposure in the target date fund (TDF) market which explains the better performance of TDFs in the COVID-19 than the 2008 crisis. The overall shift of the glide path towards less equity allocation causes TDFs to achieve significantly less during normal times when the market exhibit positive returns. We find that the shift is driven by the TDF series investing more in equities in the early period, consistent with TDFs catering to the market demand for lower risk exposure post the crisis. In addition, TDF shifters do not exhibit more idiosyncratic risk taking. Neither is aggregate glide path shift informative about subsequent equity market returns.

Target date funds in corporate retirement plans grew from $5B in 2000 to $734B in 2018, partly because federal regulation sanctioned these as default investments in automatic enrollment plans. We show that adopters delegated pension investment decisions to fund managers selected by plan sponsors. Including these funds in retirement saving menus raised equity shares, boosted bond exposures, curtailed cash/company stock holdings, and reduced idiosyncratic risk. The adoption of low-cost target date funds may enhance retirement wealth by as much as 50 percent over a 30-year horizon.

We study how managers of funds created to invest for the long run behave when shielded from liquidity constraints and their investors' short-term needs. Using the universe of US target-date funds (TDFs), we document that asset managers exploit lower investor attention to deliver lower performance. This results in a hypothetical cumulative return loss of 21% for the average investor holding the fund for 50 years. This underperformance is driven by fund families using the TDFs to smoothen the flow shocks of the affiliated open-ended funds. It is also due to higher fees arising from investing in the affiliated expensive share classes. We use the Pension Protection Act of 2006 as an exogenous shock that made TDFs the default investment options within 401(k) retirement plans.

How a portfolio manager allocates own investment in a target date fund (TDF) series is informative about managerial commitment to the TDF investment principle. We find that TDFs whose managers choose to have zero ownership are associated with more idiosyncratic risk taking. In addition, TDFs with managers investing in remote funds and diversifying across TDFs exhibit high idiosyncratic risk taking. Overall, managerial commitment helps explain TDF heterogeneity; the impact of managerial discretion on fund investment strategies demonstrates externalities to 401(k) participants using TDFs as their default option.

Is it possible to achieve almost riskless, nonfluctuating investment payoffs in the long run, at a fraction of the traditional funding requirement, using equity investments? The persistence of low interest rates is spurring research on this question because of the need to increase yields, while limiting the variability of investment results. Payouts of savings account units aim to achieve an almost riskless outcome over a long horizon. We show that they can be managed as contingent claims and, when denominated in units of a stock index, less expensively than under classical risk-neutral assumptions. To assess the robustness of the proposed hedge portfolios, we introduce a simple overfunded scheme and show its reliability using bootstrapping. The results show that by applying an overfunding of 6%, the probability of not achieving the target is less than 1%. At the heart of this result are the mean-reversion and the leverage effect of the minimal market model, together with the supermartingale property of the benchmarked savings account.

There is a looming retirement crisis, as individuals are increasingly being asked to take responsibility for their own retirement planning and a majority of these individuals are financially unsophisticated. They cannot perform basic compounding calculations and do not understand the impact of inflation, both critical aspects of retirement planning. Yet, these individuals are being tasked with the responsibility for three complex, interconnected decisions: how much to save, how to invest (with many additional decisions), and how to decumulate one’s portfolio at retirement. Compounding these challenges, current financial instruments and products (e.g. T-Bills, TIPs, or Target Date Funds) are risky because they focus on the wrong goal - wealth at retirement, as opposed to how much retirement income can be guaranteed to support pre-retirement standard-of-living. Moreover, annuities are complex, costly, and illiquid and seldom used. Without financial innovation and a change in the metric for measuring retirement success, many individuals will retire poor – a financially and socially undesirable outcome for any country. This paper presents an easy, quick and efficient solution for countries to address all these challenges and improve retirement security by creating and issuing an innovative new bond – SeLFIES (Standard-of-Living indexed, Forward-starting, Income-only Securities). The SeLFIES bond is a single, liquid, low-cost, low-risk instrument, easy-to-understand for even the most financially unsophisticated individual, because it embeds accumulation, decumulation, compounding and inflation-adjustments. SeLFIES is good for governments too, as the bond lowers the risk of individuals retiring poor, improves balance sheet management, and funds infrastructure. The paper also discusses key design aspects of SeLFIES to show how they can ensure longevity risk protection and hedge standard-of-living risk, a key unmanaged risk globally today. Additionally, the paper by concludes by demonstrating the universality of the SeLFIES design as well as by showing how it serves a useful purpose by becoming the “currency of retirement.”

We investigate the role of extreme positive payoffs in the distribution of monthly fund returns in investors’ mutual fund preferences. We document a positive and significant relationship between the maximum style-adjusted monthly return (MAX) and future fund flows. The relationship is robust to controlling for average performance, volatility, skewness, and various other fund characteristics. Our findings are consistent with the notion that fund investors overweight the probability of high payoff states in the past return distribution. We further show that MAX is not a useful predictor of future performance and that an increase in a fund’s visibility does not explain our findings.

Mutual fund is a popular investment vehicle for investors. Investors usually judge fund manager performance relative to target benchmarks. Fund managers, on the other hand, are interested in knowing how/why they perform well or poorly relative to their peers in different aspects of fund management as well. To acquire more insights about this issue and design a comprehensive performance measure, fund management function is conceptualised as a three-stage production process. To assess overall and stage-level performance, a network data envelopment analysis model is developed. The stage-level processes are deemed to operate under two different environmental conditions—levels of risk exposure. Operation under different levels of risk exposure is modelled through conditions imposed on the intermediate measures. A new index proposed to assess linkage performance is demonstrated empirically to improve discriminatory power of performance. Further applications of the proposed model are discussed.

The use of target date funds (TDFs) as default options in 401(k) plans increased sharply following the Pension Protection Act of 2006. We document large differences in the realized returns and ex ante risk profiles of TDFs with similar target retirement dates. Analyzing fund-level data, we find evidence that this heterogeneity reflects strategic risk-taking by families with low market share, especially those entering the TDF market after 2006. Analyzing plan-level data, we find little evidence that 401(k) plan sponsors consider, to any economically meaningful degree, the risk profiles of their firms when choosing among TDFs. Received June 13, 2013; editorial decision March 20, 2018 by Editor Laura Starks. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

In over-the-counter markets, many options on a defaultable instrument are subject to default risks stemming from the possibility that the option writer may not carry out its contractual obligations. In this study, we examine the valuation of dynamic fund protection with an issuer’s credit risk. By using double Mellin transforms and the method of images, we obtain the closed-form solution of vulnerable dynamic fund protection. Moreover, we analyze the value of dynamic fund protection under the default risk of firms with respect to the model parameters and demonstrate that our closed-form solution has been derived accurately and efficiently by comparing it with the solution from the Monte-Carlo simulation.

Investing is a complicated affair, particularly for people with low financial literacy. Target-date funds are designed to make investing easy for pension participants. To simplify the employee’s decision, many defined contribution plans offer employees a target-date fund based on only one piece of data—the employee’s expected retirement date. The employee may be placed in a target-date fund as the default plan if the employee does not make an active choice. Target-date funds’ one-size-fits-all approach generally does not provide the appropriate level of risk for all employees who plan to retire in a given year. The authors address that issue in this article. Their proposal has three parts. First, they propose that target-date funds should allow greater personalization of investments by offering participants a conservative, moderate, and risky fund for each target-date. While pension participants currently have the option of choosing a more or less risky target-date fund by choosing a later or earlier target-date than their actual retirement date, many pension participants lack the sophistication to take advantage of that option. Second, they suggest that pension plans incorporate robo advisers to help participants identify the appropriate level of risk and appropriate target-date fund based on their personal circumstances. Third, they propose on-the-spot financial education, to be provided when a participant is selecting a target-date fund, to help participants understand the implications of risk level and target-date fund choice for both pension growth and the range of possible outcomes.

We extend Cass and Stiglitz's analysis of preference-based mutual fund separation. We provide a complete characterization of the general K-fund separation. We show that some instances of separation with many funds can be constructed by adding inverse marginal utility functions having separation with one or a few funds. We also show that there is money separation (in which we can choose the riskless asset as one of the funds) if and only if there is a fund (which may or may not be the riskless asset) with a constant allocation as wealth changes. In general, we do not know how to write the separating utility functions in closed form, but we can do so in the special case of SAHARA utility defined by Chen et al. and for a new class of GOBI preferences introduced here.