Portfolio size effect in retirement accounts : what does it imply for lifecycle asset allocation funds?

Lifecycle funds offered by retirement plan providers allocate aggressively to risky asset classes when the employee participants are young, gradually switching to more conservative asset classes as they grow older and approach retirement. This approach focuses on maximizing growth of the accumulation fund in the initial years and preserving its value in the later years. The authors simulate terminal wealth outcomes based on conventional lifecycle asset allocation rules as well as on contrarian strategies that reverse the direction of asset switching. The evidence suggests that the growth in portfolio size over time significantly impacts the asset allocation decision. Due to the portfolio size effect that is observed by the authors, the terminal value of accumulation in retirement accounts is influenced more by the asset allocation strategy adopted in later years relative to that adopted in early years. By mechanistically switching to conservative assets in the later years of a plan, lifecycle strategies sacrifice significant growth opportunity and prove counterproductive to the participant's wealth accumulation objective. The authors' conclude that this sacrifice does not seem to be compensated adequately in terms of reducing the risk of potentially adverse outcomes.

Dynamic lifecycle strategies for target date retirement funds

Target date retirement funds have gained favor with retirement plan investors in recent years. Typically, these funds initially have a high allocation to stocks but move towards less volatile assets, such as bonds and cash, as the target retirement date approaches. Empirical research has generally found that a switch to low-risk assets prior to retirement can reduce the risk of confronting the most extreme negative outcomes. This article questions the rationale for lifecycle switching based solely on age or target retirement date as is the prevalent practice among target date funds. The authors argue that a dynamic switching strategy, which takes into consideration achieved investment returns, will produce superior returns for most investors compared to conventional lifecycle switching. In this article, the authors put forward a dynamic lifecycle switching strategy that is conditional on the attainment of the plan member's wealth accumulation objective at every stage of switching.

Asset allocation policy, returns and expenses of superannuation funds : recent evidence based on default options

We examine the asset allocation, returns, and expenses of superannuation funds whose assets are mainly invested in default investment options between 2004 and 2012. A majority of these funds fail to earn returns commensurate with their strategic asset allocation policy. It appears that much of the variation of returns between the funds might be a result of their engaging in significant active management of assets. Our results indicate that returns from active management are negatively related to expenses. We also find strong evidence of economies of scale existing in these superannuation funds across different size categories.

A dynamic bandwidth allocation scheme for interactive multimedia applications over cellular networks

Cellular networks played key role in enabling high level of bandwidth for users by employing traditional methods such as guaranteed QoS based on application category at radio access stratum level for various classes of QoSs. Also, the newer multimode phones (e.g., phones that support LTE (Long Term Evolution standard), UMTS, GSM, WIFI all at once) are capable to use multiple access methods simulta- neously and can perform seamless handover among various supported technologies to remain connected. With various types of applications (including interactive ones) running on these devices, which in turn have different QoS requirements, this work discusses as how QoS (measured in terms of user level response time, delay, jitter and transmission rate) can be achieved for interactive applications using dynamic bandwidth allocation schemes over cellular networks. In this work, we propose a dynamic bandwidth allocation scheme for interactive multimedia applications with/without background load in the cellular networks. The system has been simulated for many application types running in parallel and it has been observed that if interactive applications are to be provided with decent response time, a periodic overhauling of policy at admission control has to be done by taking into account history, criticality of applications. The results demonstrate that interactive appli- cations can be provided with good service if policy database at admission control is reviewed dynamically.

First real-time experimental demonstrations of 11.25Gb/s optical OFDMA PONs with adaptive dynamic bandwidth allocation.

End-to-end real-time experimental demonstrations are reported, for the first time, of aggregated 11.25Gb/s over 26.4km standard SMF, optical orthogonal frequency division multiple access (OOFDMA) PONs with adaptive dynamic bandwidth allocation (DBA). The demonstrated intensity-modulation and direct-detection (IMDD) OOFDMA PON system consists of two optical network units (ONUs), each of which employs a DFB-based directly modulated laser (DML) or a VCSEL-based DML for modulating upstream signals. Extensive experimental explorations of dynamic OOFDMA PON system properties are undertaken utilizing identified optimum DML operating conditions. It is shown that, for simultaneously achieving acceptable BERs for all upstream signals, the OOFDMA PON system has a >3dB dynamic ONU launch power variation range, and the BER performance of the system is insusceptible to any upstream symbol offsets slightly smaller than the adopted cyclic prefix. In addition, experimental results also indicate that, in addition to maximizing the aggregated system transmission capacity, adaptive DBA can also effectively reduce imperfections in transmission channel properties without affecting signal bit rates offered to individual ONUs.

Dynamic task allocation and coordination in cooperative multi-agent environments

La coordinació i assignació de tasques en entorns distribuïts ha estat un punt important de la recerca en els últims anys i aquests temes són el cor dels sistemes multi-agent. Els agents en aquests sistemes necessiten cooperar i considerar els altres agents en les seves accions i decisions. A més a més, els agents han de coordinar-se ells mateixos per complir tasques complexes que necessiten més d'un agent per ser complerta. Aquestes tasques poden ser tan complexes que els agents poden no saber la ubicació de les tasques o el temps que resta abans de que les tasques quedin obsoletes. Els agents poden necessitar utilitzar la comunicació amb l'objectiu de conèixer la tasca en l'entorn, en cas contrari, poden perdre molt de temps per trobar la tasca dins de l'escenari. De forma similar, el procés de presa de decisions distribuït pot ser encara més complexa si l'entorn és dinàmic, amb incertesa i en temps real. En aquesta dissertació, considerem entorns amb sistemes multi-agent amb restriccions i cooperatius (dinàmics, amb incertesa i en temps real). En aquest sentit es proposen dues aproximacions que permeten la coordinació dels agents. La primera és un mecanisme semi-centralitzat basat en tècniques de subhastes combinatòries i la idea principal es minimitzar el cost de les tasques assignades des de l'agent central cap als equips d'agents. Aquest algoritme té en compte les preferències dels agents sobre les tasques. Aquestes preferències estan incloses en el bid enviat per l'agent. La segona és un aproximació d'scheduling totalment descentralitzat. Això permet als agents assignar les seves tasques tenint en compte les preferències temporals sobre les tasques dels agents. En aquest cas, el rendiment del sistema no només depèn de la maximització o del criteri d'optimització, sinó que també depèn de la capacitat dels agents per adaptar les seves assignacions eficientment. Addicionalment, en un entorn dinàmic, els errors d'execució poden succeir a qualsevol pla degut a la incertesa i error de accions individuals. A més, una part indispensable d'un sistema de planificació és la capacitat de re-planificar. Aquesta dissertació també proveeix una aproximació amb re-planificació amb l'objectiu de permetre als agent re-coordinar els seus plans quan els problemes en l'entorn no permeti la execució del pla. Totes aquestes aproximacions s'han portat a terme per permetre als agents assignar i coordinar de forma eficient totes les tasques complexes en un entorn multi-agent cooperatiu, dinàmic i amb incertesa. Totes aquestes aproximacions han demostrat la seva eficiència en experiments duts a terme en l'entorn de simulació RoboCup Rescue.

Asset allocation, cross-class correlation and the structure of property returns

Practical applications of portfolio optimisation tend to proceed on a “top down” basis where funds are allocated first at asset class level (between, say, bonds, cash, equities and real estate) and then, progressively, at sub-class level (within property to sectors, office, retail, industrial for example). While there are organisational benefits from such an approach, it can potentially lead to sub-optimal allocations when compared to a “global” or “side-by-side” optimisation. This will occur where there are correlations between sub-classes across the asset divide that are masked in aggregation – between, for instance, City offices and the performance of financial services stocks. This paper explores such sub-class linkages using UK monthly stock and property data. Exploratory analysis using clustering procedures and factor analysis suggests that property performance and equity performance are distinctive: there is little persuasive evidence of contemporaneous or lagged sub-class linkages. Formal tests of the equivalence of optimised portfolios using top-down and global approaches failed to demonstrate significant differences, whether or not allocations were constrained. While the results may be a function of measurement of market returns, it is those returns that are used to assess fund performance. Accordingly, the treatment of real estate as a distinct asset class with diversification potential seems justified.

Aligning asset allocation and real estate investment: some lessons from the last cycle

Asset allocation is concerned with the development of multi--‐asset portfolio strategies that are likely to meet an investor’s objectives based on the interaction of expected returns, risk, correlation and implementation from a range of distinct asset classes or beta sources. Challenges associated with the discipline are often particularly significant in private markets. Specifically, composition differences between the ‘index’ or ‘benchmark’ universe and the investible universe mean that there can often be substantial and meaningful deviations between the investment characteristics implied in asset allocation decisions and those delivered by investment teams. For example, while allocation decisions are often based on relatively low--‐risk diversified real estate ‘equity’ exposure, implementation decisions frequently include exposure to higher risk forms of the asset class as well as investments in debt based instruments. These differences can have a meaningful impact on the contribution of the asset class to the overall portfolio and, therefore, lead to a potential misalignment between asset allocation decisions and implementation. Despite this, the key conclusion from this paper is not that real estate investors should become slaves to a narrowly defined mandate based on IPD / NCREIF or other forms of benchmark replication. The discussion suggests that such an approach would likely lead to the underutilization of real estate in multi--‐asset portfolio strategies. Instead, it is that to achieve asset allocation alignment, real estate exposure should be divided into multiple pools representing distinct forms of the asset class. In addition, the paper suggests that associated investment guidelines and processes should be collaborative and reflect the portfolio wide asset allocation objectives of each pool. Further, where appropriate they should specifically target potential for ‘additional’ beta or, more marginally, ‘alpha’.