Search Results (56)

Pension funds’ growth highlights the need to emphasize fiduciary duty and investment sustainability, considering the current and future participants’ interests (priority stakeholders) and systemic risk reduction (environmental, social, economic, and governance effects). Therefore, this study builds sustainability indicators based on the interests of pension fund stakeholders. The methodology comprised five stages: the first consisted of analyzing Annual Information Reports to create a preliminary list of indicators; the second involved examining specific legislation on pension fund disclosure and identifying mandatory information; the third involved submitting the updated list to experts; and the fourth involved submitting it to priority stakeholders for evaluation and validation. After its updates, the indicators list was evaluated using Principal Component Analysis. All these stages allowed for the triangulation of information and the creation of a final list containing 48 sustainability indicators for pension funds, with information requested by priority stakeholders. This allows regulators to adjust disclosure rules, including those required by stakeholders and good governance practices. It also allows pension funds to identify the indicators required by stakeholders, reducing information asymmetry. The adoption of the list of indicators would promote trust, legitimacy, and sustainability for pension funds. Full article

The world’s 300 largest pension funds manage assets for more than USD 21 trillion. A strict orientation to environmental, social, and good governance (ESG) in the investment portfolio of pension funds can play a key role in triggering the economy toward a sustainable transition. Can responsible pension plans be an attractive investment opportunity for young people? Since the performance of pension funds depends on the demographic characteristics of investors, other than the financial results of investment portfolios, this study aimed to test the convenience of ESG-oriented pension plans for young contributors aged 20–29 with different risk propensities and attitudes towards sustainability. The analysis was started using accurate data provided by an Italian pension fund, observed from 2012 to 2022. The methods applied were a Monte Carlo simulation of the individual actuarial balances, the expected utility, and the willingness to pay. The results show that ESG-oriented pension funds are convenient for young people who invest in riskier lines. Still, it is sufficient for a light green preference to persuade young contributors to invest in ESG-oriented funds and balanced lines. The results of the study can support pension fund managers in defining and offering appropriate ESG lines suitable for younger investors. Full article

Prior research empirically finds that the systematic equity risk for US firms as measured by beta reflects the risk of their defined benefit pension plans, despite opaque and complicated pension accounting rules. This paper re-examines this question in the context of subsequent clarification of these rules, and the growing importance of non-defined benefit pension funds. This issue is examined by comparing standard equity-based models with a broader pre-existing shareholder model of the reporting entity to re-examine the relationship between firm equity risk and pension plan risk. The empirical tests are conducted on a sample of S&P 500 firms during the first three years of the introduction of the revised pension accounting rules (2006–2008), based on panel data regression relating firm risk to pension risk and controlling for other variables. In contrast to the prior findings of JMB, the estimated cost of capital is additionally sensitive to the following: (a) alternative explicit versus implicit definitions of pension liability; (b) the nature and scope of long-term deferred compensation arrangements; and (c) the scope and nature of investment-related risks through investment in sponsoring company stock that are associated with these pension arrangements. Full article

This paper studies the optimal asset allocation problem of a defined contribution (DC) pension plan with a stochastic salary and value under a constraint within a stochastic volatility model. It is assumed that the financial market contains a risk-free asset and a risky asset whose price process satisfies the Stein–Stein stochastic volatility model. To comply with regulatory standards and offer a risk management tool, we integrate the dynamic versions of Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and worst-case CVaR (wcCVaR) constraints into the DC pension fund management model. The salary is assumed to be stochastic and characterized by geometric Brownian motion. In the dynamic setting, a CVaR/wcCVaR constraint is equivalent to a VaR constraint under a higher confidence level. By using the Lagrange multiplier method and the dynamic programming method to maximize the constant absolute risk aversion (CARA) utility of terminal wealth, we obtain closed-form expressions of optimal investment strategies with and without a VaR constraint. Several numerical examples are provided to illustrate the impact of a dynamic VaR/CVaR/wcCVaR constraint and other parameters on the optimal strategy. Full article

The optimal investment problem for defined contribution (DC) pension plans with partial information is the subject of this paper. The purpose of the return of premium clauses is to safeguard the rights of DC pension plan participants who pass away during accumulation. We assume that the market price of risk consists of observable and unobservable factors that follow the Ornstein-Uhlenbeck processes, and the pension fund managers estimate the unobservable component from known information through Bayesian learning. Considering maximizing the expected utility of fund wealth at the terminal time, optimal investment strategies and the corresponding value function are determined using the dynamical programming principle approach and the filtering technique. Additionally, fund managers forsake learning, which results in the presentation of suboptimal strategies and utility losses for comparative analysis. Lastly, numerical analyses are included to demonstrate the impact of model parameters on the optimal strategy. Full article

Defined benefit (DB) pension plans are a primary type of pension schemes with the sponsor assuming most of the risks. Longevity-indexed bonds have been used to hedge or transfer risks in pension plans. Our objective is to study an aggregated DB pension plan’s optimal risk management problem focusing on minimizing the solvency risk over a finite time horizon and to investigate the investment strategies in a market, comprising a longevity-indexed bond and a risk-free asset, under stochastic nominal interest rates. Using the dynamic programming technique in the stochastic control problem, we obtain the closed-form optimal investment strategy by solving the corresponding Hamilton–Jacobi–Bellman (HJB) equation. In addition, a comparative analysis implicates that longevity-indexed bonds significantly reduce solvency risk compared to zero-coupon bonds, offering a strategic advantage in pension fund management. Besides the closed-form solution and the comparative study, another novelty of this study is the extension of actuarial liability (AL) and normal cost (NC) definitions, and we introduce the risk neutral valuation of liabilities in DB pension scheme with the consideration of mortality rate. Full article

Using stochastics in stock market analysis is widely accepted for index estimation and ultra-high-frequency trading. However, previous studies linking index estimation to actual trading without applying low-frequency trading are limited. This study applied William%R to the existing research and used fixed parameters to remove noise from stochastics. We propose contributing to stock market stakeholders by finding an easy-to-apply algorithmic trading methodology for individual and pension fund investors. The algorithm constructed two oscillators with fixed parameters to identify when to enter and exit the index and achieved good results against the benchmark. We tested two ETFs, SPY (S&P 500) and EWY (MSCI Korea), from 2010 to 2022. Over the 12-year study period, our model showed it can outperform the benchmark index, having a high hit ratio of over 80%, a maximum drawdown in the low single digits, and a trading frequency of 1.5 trades per year. The results of our empirical research show that this methodology simplifies the process for investors to effectively implement market timing strategies in their investment decisions. Full article

This paper investigates a dynamic liability-driven investment policy for defined-benefit (DB) plans by incorporating the loss aversion of a sponsor, who is assumed to be more sensitive to underfunding than overfunding. Through the lens of prospect theory, we first set up a loss-aversion utility function for a sponsor whose utility depends on the funding ratio in each period, obtained from stochastic processes of pension assets and liabilities. We then construct a multi-horizon dynamic control optimization problem to find the optimal investment strategy that maximizes the expected utility of the plan sponsor. A genetic algorithm is employed to provide a numerical solution for our nonlinear dynamic optimization problem. Our results suggest that the overall paths of the optimal equity allocation decline as the age of a plan participant reaches retirement. We also find that the equity portion of the portfolio increases when a sponsor is less loss-averse or the contribution rate is lower. Full article

The private pension is a system designed to maintain an income level during passive periods by utilizing the income earned during active working years. It complements the mandatory retirement systems of the public sector and is based on a voluntary participation structure. Additionally, it serves as an investment and savings tool with the ability to provide long-term funds. The legislation for the private pension system was enacted in Türkiye in 2001, and it was implemented in 2003. In addition, a government contribution program was initiated to promote the system in 2013. An automatic enrollment system was introduced in 2017. The effectiveness and performance of individual pension companies play significant roles in the system. This study aims to measure the performance of individual pension companies operating in Türkiye using the gray relational analysis method, which is an effective measurement method, for the years 2016–2022. Subsequently, based on the measurement results, recommendations will be provided. Full article

Using the capital asset pricing model, this article critically assesses the relative importance of computing ‘realized’ betas from high-frequency returns for Bitcoin and Ethereum—the two major cryptocurrencies—against their classic counterparts using the 1-day and 5-day return-based betas. The sample includes intraday data from 15 May 2018 until 17 January 2023. The microstructure noise is present until 4 min in the BTC and ETH high-frequency data. Therefore, we opt for a conservative choice with a 60 min sampling frequency. Considering 250 trading days as a rolling-window size, we obtain rolling betas < 1 for Bitcoin and Ethereum with respect to the CRIX market index, which could enhance portfolio diversification (at the expense of maximizing returns). We flag the minimal tracking errors at the hourly and daily frequencies. The dispersion of rolling betas is higher for the weekly frequency and is concentrated towards values of $\beta$ > 0.8 for BTC ($\beta$ > 0.65 for ETH). The weekly frequency is thus revealed as being less precise for capturing the ‘pure’ systematic risk for Bitcoin and Ethereum. For Ethereum in particular, the availability of high-frequency data tends to produce, on average, a more reliable inference. In the age of financial data feed immediacy, our results strongly suggest to pension fund managers, hedge fund traders, and investment bankers to include ‘realized’ versions of CAPM betas in their dashboard of indicators for portfolio risk estimation. Sensitivity analyses cover jump detection in BTC/ETH high-frequency data (up to 25%). We also include several jump-robust estimators of realized volatility, where realized quadpower volatility prevails. Full article

This study proposes a structured product (SP) for hedging defined contribution pension fund members against capital market risk. Using Monte Carlo simulations on three different guaranteed returns to test the investment strategy of the SP against a balanced investment portfolio, we measure their performance across a wide variety of capital market returns and risk scenarios. The results show that the SP guarantees a minimal return on the pension savings portfolio and offers a higher portfolio return at a lower investment risk, compared with the balanced investment portfolio. We conclude that the SP may become popular among pension fund members, potentially leading to improved risk management, greater competition, and investment strategy innovations for defined contribution pension schemes. Full article

We study the valuation of a pension fund’s obligations in a discrete time and space incomplete market model. The market’s incompleteness stems from the non-replicability of the wage process that finances the pension plan through time. The contingent defined-benefit liability of the pension fund is a function of the wages, which can be seen as the payoff of a path-dependent derivative security. We apply the notion of the super-hedging value and propose its difference from the current pension’s fund capital as a measure of distance to liability hedging. The induced closed-form expressions of the values and the related investment strategies provide insightful comparative statistics. Furthermore, we use a utility-based optimization portfolio to point out that in cases of sufficient capital, the application of a subjective investment criterion may result in heavily different strategies than the super-hedging one. This means that the pension fund will be left with some liability risk, although it could have been fully hedged. Finally, we provide conditions under which the effect of a possible early exit leaves the super-hedging valuation unchanged. Full article

Pension plans play a vital role in the economy by impacting savings, consumption, and investment allocation. Despite declining mortality rates and increasing life expectancy, pension enrollment remains low, affecting the long-term financial stability and well-being of populations. To address this issue, this study was conducted to explore the potential of predictive modeling techniques in improving pension participation. The study utilized three tree-based machine learning algorithms and a logistic regression classifier to analyze data from a nationally representative 2019 Kenya FinAccess Household Survey. The results indicated that ensemble tree-based models, particularly the random forest model, were the most effective in predicting pension enrollment. The study identified the key factors that influenced enrollment, such as National Health Insurance Fund (NHIF) usage, monthly income, and bank usage. The findings suggest that collaboration among the NHIF, banks, and pension providers is necessary to increase pension uptake, along with increased financial education for citizens. The study provides valuable insight for promoting and optimizing pension participation. Full article

The role of the voluntary pension fund is to ensure the preservation and increase of their value by investing the collected payments and contributions, and thus the later amount of private pensions for payment. Savings for a private pension is a long-term investment and aims to preserve a certain level of the investor's standard of living even in times when monthly incomes begin to fall due to retirement. The advantage of investing in a voluntary pension fund compared to individual investment is that it is possible to diversify the risk on a larger number of securities with larger funds invested. Full article

The allocation of pension funds has important theoretical value and practical significance, which improves the level of pension investment income, achieves the maintenance and appreciation of pension funds, and resolves the pension payment risk caused by population aging. The asset allocation of pension funds is a long-term asset allocation problem. Thus, the long-term risk and return of the assets need to be estimated. The covariance matrix is usually adopted to measure the risk of the assets, while calculating the long-term covariance matrix is extremely difficult. Direct calculations suffer from the insufficiency of historical data, and indirect calculations accumulate short-term covariance, which suffers from the dynamic changes of the covariance matrix. Since the returns of main assets are highly autocorrelated, the covariance matrix of main asset returns is time-varying with dramatic dynamic changes, and the errors of indirect calculation cannot be ignored. In this paper, we propose a novel Black–Litterman model with time-varying covariance (TVC-BL) for the optimal asset allocation of pension funds to address the time-varying nature of asset returns and risks. Firstly, the return on assets (ROA) and the covariance of ROA are modeled by VARMA and GARCH, respectively. Secondly, the time-varying covariance estimation of ROA is obtained by introducing an effective transformation of the covariance matrix from short-term to long-term. Finally, the asset allocation decision of pension funds is achieved by the TVC-BL model. The results indicate that the proposed TVC-BL pension asset allocation model outperforms the traditional BL model. When the risk aversion coefficient is 1, 1.5, and 3, the Sharp ratio of pension asset allocation through the TVC-BL pension asset allocation model is 13.0%, 10.5%, and 12.8% higher than that of the traditional BL model. It helps to improve the long-term investment returns of pension funds, realize the preservation and appreciation of pension funds, and resolve the pension payment risks caused by the aging of the population. Full article