The 4% strategy revisited: a pre-commitment mean-variance optimal approach to wealth management

In contrast to single-period mean-variance (MV) portfolio allocation, multi-period MV optimal portfolio allocation can be modified slightly to be effectively a down-side risk measure. With this in mind, we consider multi-period MV optimal portfolio allocation in the presence of periodic withdrawals. The investment portfolio can be allocated between a risk-free investment and a risky asset, the price of which is assumed to follow a jump diffusion process. We consider two wealth management applications: optimal de-accumulation rates for a defined contribution pension plan and sustainable withdrawal rates for an endowment. Several numerical illustrations are provided, with some interesting implications. In the pension de-accumulation context, Bengen (1994)’s [J. Financial Planning, 1994, 7, 171–180], historical analysis indicated that a retiree could safely withdraw 4% of her initial retirement savings annually (in real terms), provided that her portfolio maintained an even balance between diversified equities and U.S. Treasury bonds. Our analysis does support 4% as a sustainable withdrawal rate in the pension de-accumulation context (and a somewhat lower rate for an endowment), but only if the investor follows an MV optimal portfolio allocation, not a fixed proportion strategy. Compared with a constant proportion strategy, the MV optimal policy achieves the same expected wealth at the end of the investment horizon, while significantly reducing the standard deviation of wealth and the probability of shortfall. We also explore the effects of suppressing jumps so as to have a pure diffusion process, but assuming a correspondingly larger volatility for the latter process. Surprisingly, it turns out that the MV optimal strategy is more effective when there are large downward jumps compared to having a high volatility diffusion process. Finally, tests based on historical data demonstrate that the MV optimal policy is quite robust to uncertainty about parameter estimates.     

Differentiation and dynamism within the IT development program

Information technology (IT) developments of large magnitude organize as collections of multiple projects into a single program, especially under dynamic conditions of market uncertainty that frequently change requirements or solutions midstream. Successful completion of an IT development program requires that the multiple teams work effectively together as well as independently in response to changes by relying on the differentiation of talent and knowledge available to the program manager. We consider and empirically support a model derived from principles in the multi-team systems (MTS) literature to determine the influence of differentiation among the IT program in the sharing of knowledge and information. The relationship from differentiation to program success is mediated by knowledge and information sharing, showing how to manage change through the dissemination of information and knowledge. Uncertainty of the market positively moderates the relation from differentiation among projects to information sharing. These findings contribute to the literature by empirically validating that MTS frameworks are exceptionally well suited for dealing with complex environments in the context of IT development.     

Self-coordination in time inconsistent stochastic decision problems: A planner–doer game framework

Time inconsistency has been a thorny issue in many economic and financial decision making problems, especially when risk measures are involved in performance criteria. We develop in this paper a two-tier planner–doer game framework with self-coordination. By aligning the global interest of the planner and the local interests of the doers by applying suitable penalty functions, a degree of internal harmony (measured quantitatively by the expected cost of self-coordination) can be achieved by the self-coordination policy. We establish an axiom system for modified preferences, under which the self-coordination policy can be obtained by solving a corresponding optimization problem. We then apply our game framework successfully in dynamic mean-variance portfolio selection.     

International diversification and Microfinance

International commercial banks, institutional investors, and private investors have become increasingly interested in financing microfinance institutions (MFIs). This paper investigates whether adding microfinance funds to a portfolio of risky international assets yields diversification gains. By using mean-variance spanning tests with short-sale constraints, we find that investing in microfinance may be attractive for investors seeking a better risk-return profile. Specifically, the analysis suggests that investing in MFIs from Latin America, or microfinance and rural banks yields more efficient portfolios. In contrast, adding MFIs from Africa or microfinance NGOs to a portfolio of international assets is not beneficial for a mean-variance investor.     

A mean-variance approach to forecasting with the consumer confidence index

This article refines the way consumer confidence survey data are used in forecasting models. The refinement is easy to describe: it extends existing models by controlling for statistically significant changes in consumer confidence index values. The motivation behind this refinement is simply that not all changes in the confidence index are statistically significant, and mean index values alone provide a noisy signal. Using Michigan Index of Consumer Confidence from 1967 through 2013, we show that controlling for significant versus insignificant changes in the consumer confidence index materially enhances the explanatory power of household expenditure forecasting models.     

Delegated portfolio management and optimal allocation of portfolio managers

In this article, we investigate whether the application of the mean-variance framework on portfolio manager allocation offers any out-of-sample benefits compared to a naïve strategy of equal weighting. Based on an exclusive data-set of high-net-worth (HNW) investors, we utilize a wide variety of methodologies to estimate the input parameters including exponentially weighted moving average (EWMA), generalized autoregressive conditional heteroscedasticity (GARCH) and Bayes–Stein shrinkage estimation. We apply nine different mean-variance models, but find that none of these present any consistent benefit over a naïve strategy of equal weighting.     

International equality of stock market returns

Real returns, excess returns, and nominal returns from stock markets in 11 developed countries are compared for the difference in their means and variances by using a new procedure to test their equality and to determine if one stock market dominates another. The sample period from January 1973 to September 1989 is divided into three subperiods. Results show that stock markets in the United States and Germany dominate those in the other countries in early sub-periods, but not in a recent sub-period, to indicate an increasing capital market integration. Integration with Germany has increased more than with the United States, due possibly to the European Monetary System.     

DYNAMIC SPANNING: ARE OPTIONS AN APPROPRIATE INSTRUMENT?1

Ross (1976) has shown, in a static framework, how options can complete financial markets. This paper examines the possible extensions of Ross's idea in a dynamic setup. Surprisingly enough, we find that the answer is very sensitive to the choice of the stochastic model for the underlying security returns. More specifically we obtain the following results: In a discrete-time model, classical European options typically become redundant with some probability (Proposition 2.1). Obnly path dependent (“exotic”) options may generate dynamic spanning (Proposition 4.1). In a continuous-time model with stochastic volatility of the underlying security, and under reasonable assumptions, a European option is always a good instrument for completing markets (Proposition 5.2).     

Utility and the Skewness of Return in Gambling

This paper demonstrates that the intuitively appealing argument based on the postulated trade-off between expected return, variance and skewness of return of a risk-averse gambler does not provide an explanation of observed betting behaviour. It is shown how the expected utility of a representative gambler faced with a single-prized outcome event can be expressed in terms of the mean and variance of return, the mean and skewness of return or, generally, of the mean and any other single moment of return: and the standard practice of taking a Taylor series expansion/approximation of the expected utility involving moments of return is usually incorrect. Previous analyses have suggested that a punter will accept a lower mean return for higher skewness and this work seems to have involved invalid expansions of the utility function. The upshot is that with certain utility functions which have been used in a number of studies, any analysis based on expansion and estimation of the derivatives of the utility function may be valid only for data based on odds-on favourites and not for longshots.