E-Fast & CloudPower: Towards High Performance Technical Analysis for Small Investors

International audienceAbout 80% of the financial market investors fail, the main reason for this being their poor investment decisions. Without advanced financial analysis tools and the knowledge to interpret the analysis, the investors can easily make irrational investment decisions. Moreover, investors are challenged by the dynamism of the market and a relatively large number of indicators that must be computed. In this paper we propose E-Fast, an innovative approach for on-line technical analysis for helping small investors to obtain a greater e on the market by increasing their knowledge. The E-Fast technical analysis platform prototype relies on High Performance Computing (HPC), allowing to rapidly develop and extensively validate the most sophisticated finance analysis algorithms. In this work, we aim at demonstrating that the E-Fast implementation , based on the CloudPower HPC infrastructure, is able to provide small investors a realistic, low-cost and secure service that would otherwise be available only to the large financial institutions. We describe the architecture of our system and provide design insights. We present the results obtained with a real service implementation based on the Exponential Moving Average computational method, using CloudPower and Grid5000 for the computations' acceleration. We also elaborate a set of interesting challenges emerging from this work, as next steps towards high performance technical analysis for small investors

Innovation in Energy Systems

It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field

Smart Sustainable Mobility: Analytics and Algorithms for Next-Generation Mobility Systems

To this date, mobility ecosystems around the world operate on an uncoordinated, inefficient and unsustainable basis. Yet, many technology-enabled solutions that have the potential to remedy these societal negatives are already at our disposal or just around the corner. Innovations in vehicle technology, IoT devices, mobile connectivity and AI-powered information systems are expected to bring about a mobility system that is connected, autonomous, shared and electric (CASE). In order to fully leverage the sustainability opportunities afforded by CASE, system-level coordination and management approaches are needed. This Thesis sets out an agenda for Information Systems research to shape the future of CASE mobility through data, analytics and algorithms (Chapter 1). Drawing on causal inference, (spatial) machine learning, mathematical programming and reinforcement learning, three concrete contributions toward this agenda are developed. Chapter 2 demonstrates the potential of pervasive and inexpensive sensor technology for policy analysis. Connected sensing devices have significantly reduced the cost and complexity of acquiring high-resolution, high-frequency data in the physical world. This affords researchers the opportunity to track temporal and spatial patterns of offline phenomena. Drawing on a case from the bikesharing sector, we demonstrate how geo-tagged IoT data streams can be used for tracing out highly localized causal effects of large-scale mobility policy interventions while offering actionable insights for policy makers and practitioners. Chapter 3 sets out a solution approach to a novel decision problem faced by operators of shared mobility fleets: allocating vehicle inventory optimally across a network when competition is present. The proposed three-stage model combines real-time data analytics, machine learning and mixed integer non-linear programming into an integrated framework. It provides operational decision support for fleet managers in contested shared mobility markets by generating optimal vehicle re-positioning schedules in real time. Chapter 4 proposes a method for leveraging data-driven digital twin (DT) frameworks for large multi-stage stochastic design problems. Such problem classes are notoriously difficult to solve with traditional stochastic optimization. Drawing on the case of Electric Vehicle Charging Hubs (EVCHs), we show how high-fidelity, data-driven DT simulation environments fused with reinforcement learning (DT-RL) can achieve (close-to) arbitrary scalability and high modeling flexibility. In benchmark experiments we demonstrate that DT-RL-derived designs result in superior cost and service-level performance under real-world operating conditions

Climate Adaptation Modelling

This open access book focuses on an issue only marginally tackled by this literature: the still existing gap between adaptation science and modelling and the possibility to effectively access and exploit the information produced by policy making at different levels, international, national and local. To do so, the book presents the proceedings of a high-level expert workshop on adaptation modelling, integrated with main results from the “Study on Adaptation Modelling” (SAM-PS) commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) and implemented by the CMCC Foundation – Euro-Mediterranean Centre on Climate Change, in collaboration with the Institute for Environmental Studies (IVM), Deltares, and Paul Watkiss Associates (PWA). What is the latest development in adaptation modelling? Which tools and information are available for adaptation assessment? How much are they practically usable by the policy community? How their uptake by practitioners can be improved? What are the major research gaps in adaptation modelling that needs to be covered in the next future? How? This book addresses these questions presenting the results of a study on adaptation modelling commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) enriched by the outcomes of a high-level expert workshop on adaptation also part of the research. This book aspires to provide a useful support to academics, policy makers and practitioners in the field of adaptation to orient them in the expanding adaptation modelling assessment literature and suggest practical ways for its application. This book, mainly addressed to academics, policy makers and practitioners in the field of adaptation, aims to providing orientation in the large and expanding methodological/quantitative literature, presenting novelties, guiding in the practical application of adaptation assessments and suggesting lines for future research. This open access book focuses on an issue only marginally tackled by this literature: the still existing gap between adaptation science and modelling and the possibility to effectively access and exploit the information produced by policy making at different levels, international, national and local. To do so, the book presents the proceedings of a high-level expert workshop on adaptation modelling, integrated with main results from the “Study on Adaptation Modelling” (SAM-PS) commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) and implemented by the CMCC Foundation – Euro-Mediterranean Centre on Climate Change, in collaboration with the Institute for Environmental Studies (IVM), Deltares, and Paul Watkiss Associates (PWA)

Climate Adaptation Modelling

This open access book focuses on an issue only marginally tackled by this literature: the still existing gap between adaptation science and modelling and the possibility to effectively access and exploit the information produced by policy making at different levels, international, national and local. To do so, the book presents the proceedings of a high-level expert workshop on adaptation modelling, integrated with main results from the “Study on Adaptation Modelling” (SAM-PS) commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) and implemented by the CMCC Foundation – Euro-Mediterranean Centre on Climate Change, in collaboration with the Institute for Environmental Studies (IVM), Deltares, and Paul Watkiss Associates (PWA). What is the latest development in adaptation modelling? Which tools and information are available for adaptation assessment? How much are they practically usable by the policy community? How their uptake by practitioners can be improved? What are the major research gaps in adaptation modelling that needs to be covered in the next future? How? This book addresses these questions presenting the results of a study on adaptation modelling commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) enriched by the outcomes of a high-level expert workshop on adaptation also part of the research. This book aspires to provide a useful support to academics, policy makers and practitioners in the field of adaptation to orient them in the expanding adaptation modelling assessment literature and suggest practical ways for its application. This book, mainly addressed to academics, policy makers and practitioners in the field of adaptation, aims to providing orientation in the large and expanding methodological/quantitative literature, presenting novelties, guiding in the practical application of adaptation assessments and suggesting lines for future research. This open access book focuses on an issue only marginally tackled by this literature: the still existing gap between adaptation science and modelling and the possibility to effectively access and exploit the information produced by policy making at different levels, international, national and local. To do so, the book presents the proceedings of a high-level expert workshop on adaptation modelling, integrated with main results from the “Study on Adaptation Modelling” (SAM-PS) commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) and implemented by the CMCC Foundation – Euro-Mediterranean Centre on Climate Change, in collaboration with the Institute for Environmental Studies (IVM), Deltares, and Paul Watkiss Associates (PWA)

SIMULATING SEISMIC WAVE PROPAGATION IN TWO-DIMENSIONAL MEDIA USING DISCONTINUOUS SPECTRAL ELEMENT METHODS

We introduce a discontinuous spectral element method for simulating seismic wave in 2- dimensional elastic media. The methods combine the flexibility of a discontinuous finite element method with the accuracy of a spectral method. The elastodynamic equations are discretized using high-degree of Lagrange interpolants and integration over an element is accomplished based upon the Gauss-Lobatto-Legendre integration rule. This combination of discretization and integration results in a diagonal mass matrix and the use of discontinuous finite element method makes the calculation can be done locally in each element. Thus, the algorithm is simplified drastically. We validated the results of one-dimensional problem by comparing them with finite-difference time-domain method and exact solution. The comparisons show excellent agreement