A Polynomial Optimization Approach to Constant Rebalanced Portfolio Selection

We address the multi-period portfolio optimization problem with the constant rebalancing strategy. This problem is formulated as a polynomial optimization problem (POP) by using a mean-variance criterion. In order to solve the POPs of high degree, we develop a cutting-plane algorithm based on semidefinite programming. Our algorithm can solve problems that can not be handled by any of known polynomial optimization solvers.

Digitalization or flexibilization? The changing role of technology in the political economy of Japan

We are increasingly surrounded by talk of digitalization. Yet, we remain unsure about what impact this digitalization will have upon socio-economic institutions, how the introduction of this digitalization will be contested, the likely role of the state in managing the adoption of digital technology, and the likely consequences for the broader political economy if and when it is introduced. This article examines the process of digitalization as it has unfolded in the service sector in Japan. Based on qualitative interviews with managers in the hospitality industry and union officials, the paper depicts a process that contrasts starkly with the more optimistic view adopted by some commentators, according to which digitalization has the potential to improve working conditions and contribute to a more stable form of growth. Instead, the paper draws on Regulation Theory to argue that the introduction of digitalization is part of a wider process of neoliberalization. As such, digitalization has contributed to deskilling, the fragmentation of work tasks, a digital divide, the intensification of work, and higher levels of workplace surveillance. This represents a further dismantling of the social compromise that underpinned Japan’s earlier period of economic growth

An evolutionary algorithm for deriving withdrawal rates in defined contribution schemes

Risk-averse investors typically adopt a fixed spending strategy during retirement to prevent against the premature depletion of their retirement portfolio. But a constant withdrawal rate means that retirees accumulate unspent surpluses when markets outperform and face spending shortfalls when markets underperform. The opportunity cost of unspent surpluses associated with this strategy can be extreme. We employ a genetic algorithm to find optimal asset allocation and withdrawal levels for a retirement portfolio. Using US and international data we compare this approach to existing strategies that use basic investment decision rules. Our results show that allocations to riskier assets early in retirement generates rising incomes later in retirement, without increasing the probability of ruin. A rising income profile remains optimal under different levels of risk aversion. This finding disputes the safe withdrawal rate conventions used in contemporary financial advice models