The financial clouds review

This paper demonstrates financial enterprise portability, which involves moving entire application services from desktops to clouds and between different clouds, and is transparent to users who can work as if on their familiar systems. To demonstrate portability, reviews for several financial models are studied, where Monte Carlo Methods (MCM) and Black Scholes Model (BSM) are chosen. A special technique in MCM, Least Square Methods, is used to reduce errors while performing accurate calculations. The coding algorithm for MCM written in MATLAB is explained. Simulations for MCM are performed on different types of Clouds. Benchmark and experimental results are presented for discussion. 3D Black Scholes are used to explain the impacts and added values for risk analysis, and three different scenarios with 3D risk analysis are explained. We also discuss implications for banking and ways to track risks in order to improve accuracy. We have used a conceptual Cloud platform to explain our contributions in Financial Software as a Service (FSaaS) and the IBM Fined Grained Security Framework. Our objective is to demonstrate portability, speed, accuracy and reliability of applications in the clouds, while demonstrating portability for FSaaS and the Cloud Computing Business Framework (CCBF), which is proposed to deal with cloud portability

A Case Study for Business Integration as a Service

This paper presents Business Integration as a Service (BIaaS) to allow two services to work together in the Cloud to achieve a streamline process. We illustrate this integration using two services; Return on Investment (ROI) Measurement as a Service (RMaaS) and Risk Analysis as a Service (RAaaS) in the case study at the University of Southampton. The case study demonstrates the cost-savings and the risk analysis achieved, so two services can work as a single service. Advanced techniques are used to demonstrate statistical services and 3D Visualisation services under the remit of RMaaS and Monte Carlo Simulation as a Service behind the design of RAaaS. Computational results are presented with their implications discussed. Different types of risks associated with Cloud adoption can be calculated easily, rapidly and accurately with the use of BIaaS. This case study confirms the benefits of BIaaS adoption, including cost reduction and improvements in efficiency and risk analysis. Implementation of BIaaS in other organisations is also discussed. Important data arising from the integration of RMaaS and RAaaS are useful for management and stakeholders of University of Southampton

The Internet Ecosystem: The Potential for Discrimination

Symposium: Rough Consensus and Running Code: Integrating Engineering Principles into Internet Policy Debates, held at the University of Pennsylvania\u27s Center for Technology Innovation and Competition on May 6-7, 2010. This Article explores how the emerging Internet architecture of cloud computing, content distribution networks, private peering and data-center services can simultaneously foster a perception of unfair network access while at the same time enabling significant competition for services, content, and innovation. A key enabler of these changes is the emergence of technologies that lower the barrier for entry in developing and deploying new services. Another is the design of successful Internet applications, which already accommodate the variation in service afforded by the current Internet. Regulators should be aware of the potential for anti-competitive practices in this broader Internet Ecosystem, but should carefully consider the effects of regulation on that ecosystem

Research on Mode and Risk Prevention of Agricultural Supply Chain Finance based on E-commerce

The rapid development of e-commerce has a profound impact on agricultural supply chain finance (ASCF), which is of great significance to enhance the resilience of agricultural economic development, realize the poverty alleviation effect of agricultural enterprises, integrate agricultural supply chain resources and solve the financing difficulties of agricultural enterprises. We analyze the participants and functions of the ASCF mode based on e-commerce, and the contract framework of various participants when they operate in the ASCF platform in this paper. Based on the agricultural industry chain, we analyze the operation process of accounts receivable financing mode, inventory financing mode and prepayment financing mode based on E-commerce. Finally, in view of the natural risks, credit risks, logistics risks, technical risks and legal risks that may exist in ASCF based on e-commerce, the corresponding countermeasures are put forward from the aspects of dispersing natural risks, building digital credit risk assessment system, building agricultural logistics network system, improving technical risk monitoring system, and improving relevant laws and regulations policy recommendations

Business-driven resource allocation and management for data centres in cloud computing markets

Cloud Computing markets arise as an efficient way to allocate resources for the execution of tasks and services within a set of geographically dispersed providers from different organisations. Client applications and service providers meet in a market and negotiate for the sales of services by means of the signature of a Service Level Agreement that contains the Quality of Service terms that the Cloud provider has to guarantee by managing properly its resources. Current implementations of Cloud markets suffer from a lack of information flow between the negotiating agents, which sell the resources, and the resource managers that allocate the resources to fulfil the agreed Quality of Service. This thesis establishes an intermediate layer between the market agents and the resource managers. In consequence, agents can perform accurate negotiations by considering the status of the resources in their negotiation models, and providers can manage their resources considering both the performance and the business objectives. This thesis defines a set of policies for the negotiation and enforcement of Service Level Agreements. Such policies deal with different Business-Level Objectives: maximisation of the revenue, classification of clients, trust and reputation maximisation, and risk minimisation. This thesis demonstrates the effectiveness of such policies by means of fine-grained simulations. A pricing model may be influenced by many parameters. The weight of such parameters within the final model is not always known, or it can change as the market environment evolves. This thesis models and evaluates how the providers can self-adapt to changing environments by means of genetic algorithms. Providers that rapidly adapt to changes in the environment achieve higher revenues than providers that do not. Policies are usually conceived for the short term: they model the behaviour of the system by considering the current status and the expected immediate after their application. This thesis defines and evaluates a trust and reputation system that enforces providers to consider the impact of their decisions in the long term. The trust and reputation system expels providers and clients with dishonest behaviour, and providers that consider the impact of their reputation in their actions improve on the achievement of their Business-Level Objectives. Finally, this thesis studies the risk as the effects of the uncertainty over the expected outcomes of cloud providers. The particularities of cloud appliances as a set of interconnected resources are studied, as well as how the risk is propagated through the linked nodes. Incorporating risk models helps providers differentiate Service Level Agreements according to their risk, take preventive actions in the focus of the risk, and pricing accordingly. Applying risk management raises the fulfilment rate of the Service-Level Agreements and increases the profit of the providerPostprint (published version

Innovative Asia: Advancing the Knowledge-Based Economy - Highlights of the Forthcoming ADB Study Report

[Excerpt] The development of knowledge-based economies (KBEs) is both an imperative and an opportunity for developing Asia. It is an imperative to sustain high rates of growth in the future and an opportunity whereby emerging economies can draw from beneficial trending developments that may allow them to move faster to advance in global value chains and in position in world markets. Over the last quarter of a century, driven mostly by cheap labor, developing countries in Asia have seen unprecedented growth rates and contributions to the global economy. Sustaining Asia’s growth trajectory, however, requires developing economies to seek different approaches to economic growth and progress, especially if they aspire to move from the middle-income to the high-income level. KBE is an important platform that can enable them to sustain growth and even accelerate it. It is time for Asia to consolidate and accelerate its pace of growth. Asia is positioned in a unique moment in history with many advantages that can serve as a boost: to name a couple, an expanding middle of the pyramid—Asia is likely to hold 50% of the global middle class and 40% of the global consumer market by 2020; and the growing importance of intra-regional trade within Asia, increasing from 54% in 2001 to 58% in 2011. Many developing economies are well placed to assimilate frontier technologies into their manufacturing environment

Market Concentration Implications of Foundation Models

We analyze the structure of the market for foundation models, i.e., large AI models such as those that power ChatGPT and that are adaptable to downstream uses, and we examine the implications for competition policy and regulation. We observe that the most capable models will have a tendency towards natural monopoly and may have potentially vast markets. This calls for a two-pronged regulatory response: (i) Antitrust authorities need to ensure the contestability of the market by tackling strategic behavior, in particular by ensuring that monopolies do not propagate vertically to downstream uses, and (ii) given the diminished potential for market discipline, there is a role for regulators to ensure that the most capable models meet sufficient quality standards (including safety, privacy, non-discrimination, reliability and interoperability standards) to maximally contribute to social welfare. Regulators should also ensure a level regulatory playing field between AI and non-AI applications in all sectors of the economy. For models that are behind the frontier, we expect competition to be quite intense, implying a more limited role for competition policy, although a role for regulation remains.Comment: Working Pape