DYNAMIC ASSET ALLOCATION FOR TARGET DATE FUNDS UNDER THE BENCHMARK APPROACH

2021 ◽  
pp. 1-26
Author(s):  
Jin Sun ◽  
Dan Zhu ◽  
Eckhard Platen

ABSTRACT 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.

The retirement goals of many Americans are underfunded. The problem is compounded by the complexity of self-managing distribution portfolios, particularly as DC plans replace DB plans. We believe most retirement glide paths are satisfactory but suboptimal solutions. We introduce a glide path of financial assets over the life cycle based on a retirement goal and depleting human capital. The method is anchored to the foundational principles of intertemporal portfolio theory while borrowing heavily from goals-based asset allocation. The result is a dynamic asset allocation over the life cycle that is a function of critical input variables relevant to retirement planning such as retirement savings, retirement consumption and risk aversion. The glide path can be customized to individuals, or semi-customized to discrete subpopulations of DC plan participants.


Author(s):  
Ricardo Laborda ◽  
Jose Olmo

Abstract We derive a closed-form expression for the mean and marginal hedging demand on risky assets in long-term asset allocation problems for individuals with constant relative risk aversion preferences. Our parametric portfolio policy rule accommodates an arbitrarily large number of state variables for predicting the state of nature and number of assets in the portfolio. The closed-form expression for the hedging demand is exact under polynomial specifications of the portfolio policy rule and a suitable approximation for unknown smooth parametric portfolio policy rules using Taylor expansions. The hedging demand on risky assets depends positively on the predictability of the risky asset and the persistence of the predictors, and negatively on the degree of investor’s relative risk aversion. We illustrate these insights empirically for a basket of currencies by showing the outperformance of rebalancing carry trade strategies over different investment horizons against a short-term (myopic) portfolio.


2009 ◽  
Vol 15 (3) ◽  
pp. 573-655 ◽  
Author(s):  
S. Jarvis ◽  
A. Lawrence ◽  
S. Miao

ABSTRACTInvestment strategy is often static, punctuated by infrequent reviews. For most long-term investors, this practice results in large risks being taken that could otherwise be managed with a more dynamic investment policy. The bulk of this paper is aimed at analysing and describing two multi-period investment strategy problems — in order to derive potential dynamic strategies. Along the way, we show how static investment strategies can fail to deliver an investor's long-term objectives and describe the relationship of our work to other areas of the finance literature. This paper does not cover trading strategies such as Tactical Asset Allocation.This paper sets out two main approaches to the multi-period problem. The first approach optimises a utility function. The second approach uses partial differential equation (PDE) technology to optimise a target statistic (in this case, TailVaR) subject to return and long-only constraints.


PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249857
Author(s):  
Andrés García-Medina ◽  
Norberto A. Hernández-Leandro ◽  
Graciela González Farías ◽  
Nelson Muriel

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.


1987 ◽  
Vol 1987 (1) ◽  
pp. 82-85, 93
Author(s):  
H. Gifford Fong

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