Optimal trading: The importance of being adaptive

We compare optimal static and dynamic solutions in trade execution. An optimal trade execution problem is considered where a trader is looking at a short-term price predictive signal while trading. When the trader creates an instantaneous market impact, it is shown that transaction costs of optimal adaptive strategies are substantially lower than the corresponding costs of the optimal static strategy. In the same spirit, in the case of transient impact, it is shown that strategies that observe the signal a finite number of times can dramatically reduce the transaction costs and improve the performance of the optimal static strategy.

Design and comparison of scheduling strategy for teleconsultation

BACKGROUND: Telemedicine is playing an increasingly more important role in disease diagnosis and treatment. The market of telemedicine application is continuously promoted, thus bringing some issues on telemedicine operations management. OBJECTIVE: We aimed to compare the teleconsultation scheduling performance of newly designed proactive strategy and existing static strategy and explore the decision-making under different conditions. METHODS: We developed a discrete-event simulation model based on practical investigation to describe the existing static scheduling strategy of teleconsultation. The static strategy model was verified by comparing it with the historical data. Then a new proactive strategy was proposed, whose average waiting time, variance of waiting time and completed numbers were compared with the static strategy. RESULTS: The analysis indicated that the proactive strategy performed better than static under the current resource allocation. Furthermore, we explored the impact on the system of both strategies varying arrival rate and experts’ shift time. CONCLUSIONS: Under different shift times and arrival rates, the managers of telemedicine center should select different strategy. The experts’ shift time had a significant impact on all system performance indicators. Therefore, if managers wanted to improve the system performance to a greater extent, they needed to reduce the shift time as much as possible.

Robustness Study of Electro-Nuclear Scenario under Disruption

As the future of nuclear power is uncertain, only choosing one development objective for the coming decades can be risky; while trying to achieve several possible objectives at the same time may lead to a deadlock due to contradiction among them. In this work, we study a simple scenario to illustrate the newly developed method of robustness study, which considers possible change of objectives. Starting from the current French fleet, two objectives are considered regarding the possible political choices for the future of nuclear power: A. Complete substitution of Pressurized Water Reactors by Sodium-cooled Fast Reactors in 2180; B. Minimization of all potential nuclear wastes without SFR deployment in 2180. To study the robustness of strategies, the disruption of objective is considered: the objective to be pursued is possibly changed abruptly from A into B at unknown time. To minimize the consequence of such uncertainty, the first option is to identify a robust static strategy, which shows the best performance for both objectives A and B in the predisruption situation. The second option is to adapt a trajectory which pursues initially objective A, for objective B in case of the disruption. To identify and to analyze the adaptively robust strategies, outcomes of possible adaptations upon a given trajectory are compared with the robust static optimum. The temporality of adaptive robustness is analyzed by investigating different adaptation times.

A MAXIMAL PREDICTABILITY PORTFOLIO SUBJECT TO A TURNOVER CONSTRAINT

The authors demonstrated in earlier papers that a maximal predictability portfolio (MPP) using a dynamic strategy leads to a significantly better ex-post performance than the one based on a static strategy and the index. In this paper, we will consider a maximal predictability portfolio subject to transaction cost. To reduce transaction cost, we employ turnover constraint. It will be shown that this approach leads to a significantly better performance than the standard MPP and the index.

Towards a New Pattern of Strategy Formation in the Public Sector: First Experiences with National Strategies for Sustainable Development in Europe

Despite lengthy debates about planning versus incrementalism, there is still no consensus on what strategy processes should look like in the public sector. In the environmental policy field, the decline of formal policy planning was nonetheless followed by a surge of national strategies for sustainable development (NSSDs). After summarizing this development, we highlight some key characteristics, good practices, and weaknesses of NSSDs with regard to participation, horizontal and vertical policy integration, policy implementation, and monitoring. It is shown that NSSDs go well beyond former environmental policy plans, not just in terms of their thematic scope, but foremost because they resemble evolving rather than static strategy processes. Finally, we explore what model of strategy formation may be adequate for the public sector in general. Based on the empirical evidence presented here and by drawing on strategic management theory, strategic public management is proposed as an ideal pattern for strategy formation, which reconciles planning and incremental learning.

Dynamic Cancellation: Selecting Time Warp Cancellation Strategies at Runtime

The performance of Time Warp parallel discrete event simulators can be affected by the cancellation strategy used to send anti-messages. Under aggressive cancellation, antimessage generation occurs immediately after a straggler message is detected. In contrast, lazy cancellation delays the sending of anti-messages until forward processing from a straggler message confirms that the premature computation did indeed generate an incorrect message. Previous studies have shown that neither approach is clearly superior to the other in all cases (even within the same application domain). Furthermore, no strategy exists to make a priori determination of the more favorable cancellation strategy. Most existing Time Warp systems merely provide a switch for the user to select the cancellation strategy employed. This paper explores the use of simulation time decision procedures to select cancellation strategies. The approach is termed Dynamic Cancellation and it assigns the capability for selecting cancellation strategies to the Logical Processes (LPs) in a Time Warp simulation. Thus, within a single parallel simulation both strategies may be employed by distinct LPs and even across the simulation lifetime of an LP. Empirical analysis using several control strategies show that dynamic cancellation always performs with the best static strategy and, in some cases, dynamic cancellation provides some nominal (5–10%) performance gain over the best static strategy.