238 research outputs found

    Distributed Ledger Technology (DLT) Applications in Payment, Clearing, and Settlement Systems:A Study of Blockchain-Based Payment Barriers and Potential Solutions, and DLT Application in Central Bank Payment System Functions

    Get PDF
    Payment, clearing, and settlement systems are essential components of the financial markets and exert considerable influence on the overall economy. While there have been considerable technological advancements in payment systems, the conventional systems still depend on centralized architecture, with inherent limitations and risks. The emergence of Distributed ledger technology (DLT) is being regarded as a potential solution to transform payment and settlement processes and address certain challenges posed by the centralized architecture of traditional payment systems (Bank for International Settlements, 2017). While proof-of-concept projects have demonstrated the technical feasibility of DLT, significant barriers still hinder its adoption and implementation. The overarching objective of this thesis is to contribute to the developing area of DLT application in payment, clearing and settlement systems, which is still in its initial stages of applications development and lacks a substantial body of scholarly literature and empirical research. This is achieved by identifying the socio-technical barriers to adoption and diffusion of blockchain-based payment systems and the solutions proposed to address them. Furthermore, the thesis examines and classifies various applications of DLT in central bank payment system functions, offering valuable insights into the motivations, DLT platforms used, and consensus algorithms for applicable use cases. To achieve these objectives, the methodology employed involved a systematic literature review (SLR) of academic literature on blockchain-based payment systems. Furthermore, we utilized a thematic analysis approach to examine data collected from various sources regarding the use of DLT applications in central bank payment system functions, such as central bank white papers, industry reports, and policy documents. The study's findings on blockchain-based payment systems barriers and proposed solutions; challenge the prevailing emphasis on technological and regulatory barriers in the literature and industry discourse regarding the adoption and implementation of blockchain-based payment systems. It highlights the importance of considering the broader socio-technical context and identifying barriers across all five dimensions of the social technical framework, including technological, infrastructural, user practices/market, regulatory, and cultural dimensions. Furthermore, the research identified seven DLT applications in central bank payment system functions. These are grouped into three overarching themes: central banks' operational responsibilities in payment and settlement systems, issuance of central bank digital money, and regulatory oversight/supervisory functions, along with other ancillary functions. Each of these applications has unique motivations or value proposition, which is the underlying reason for utilizing in that particular use case

    The Political Dynamics of Electricity Sector Performance in Ghana and CĂ´te d'Ivoire

    Get PDF
    What factors drive variation in policy choices related to the electricity sector and, ultimately, in sectoral performance over time? This dissertation argues that differences in the form and intensity of competitive political pressures affect the choice and implementation of electricity sector policies and thus sectoral performance. First, I explore bivariate relationships between commonly cited external factors – natural resource endowments, economic shocks, investment climate, droughts, and civil wars – and sectoral performance across Sub-Saharan Africa. The findings confirm associations between these factors and sectoral performance. Yet they indicate considerable unexplained variation in sectoral performance, which requires qualitative analysis. Second, I analyze the politics of electricity sector management in Ghana and Côte d’Ivoire. In the 1980s and 1990s, these two countries faced similar economic and climatic crises that brought the electricity sector to its knees. Yet when the World Bank and the IMF pushed neoliberal policies as solutions for sectoral challenges, they responded differently. Liberalization and privatization policies moved forward more quickly in Côte d’Ivoire than in Ghana. Moreover, electricity sector performance differed in the two countries during 1990-2019. Electrification rates accelerated in Ghana, but they slowed in Côte d’Ivoire. Côte d’Ivoire improved the reliability of electricity supply more than Ghana. Electricity prices also reflected costs of service in Côte d’Ivoire but not in Ghana. The comparative political analysis traces how different forms and intensity of competitive political pressures, especially coups d’état, electoral threats, civil wars, and risks of civil wars, affect the implementation of electricity sector policies and then sectoral performance in Ghana and Côte d’Ivoire. I argue that intense political competition encourages Ghanaian politicians to extend electricity access to rural areas to mobilize political support and to set artificially low tariffs to appease urban residents and swing voters. Politically motivated low tariffs, coupled with unpaid subsidies and governments’ failure to pay their own electricity bills, result in inadequate investments in power utilities and, in turn, recurrent power shortages and outages. On the other hand, I argue that existential threats, mainly contestations over Ivorian identity and citizenship and civil war, slowed electrification programs with governments prioritizing regime and national stability. My study shows that (the risks of) civil wars crowd out ordinary concerns like electricity provision. However, when political life returns to normal, high competition drives governments to mollify voters by extending access to electricity and setting below-cost tariffs. Low competition allows governments to make policy changes they view as solutions for sectoral challenges but might defer short-term voter gratification. I demonstrate that low electoral threats encouraged the privatization of the state-owned electricity company in Côte d’Ivoire. In contrast, intense political competition discouraged ruling elites from privatizing the national electricity distributor in Ghana

    Yield Curves and Macro Variables Interactions and Predictions

    Get PDF
    This research is based on the yield curves and five macro variables, namely equity indices, FX rates, central banks’ policy rates, inflation rates and the GDP growth rates, for nine different markets, from different geographical regions. Our aim was to identify common trends in yield curves and macro variables behaviors, from two perspectives: the interaction and predictive power of the variables. Firstly, we studied the interaction between yield curves and macro variables based on: Granger Causality, Impulse Response Function and Variance Decomposition. Afterwards, we predicted yield curves based on ANN Regression Multitask learning, and lastly, we predicted our five macro variables based on three different ANN Classifiers, in order to generalize and present results that are not specific to a country, or region, or model. The most persistence trend, amongst the variables, was the association between the GDP, inflation, policy rate and the Level. Based on Multitask learning, we achieved a 1-mnth average yield curves prediction accuracy of 80.2% for all yield maturities and studied markets. Additionally, we found out that increasing the hidden nodes led to overfitting the data, hence, we recommend the use of a simple neural network architecture. Furthermore, we designed a model that computes the optimum number of hidden nodes based on: the number of input/output nodes and forecasted months ahead. The Independent Variable Contribution analysis increased the weight of Slope on average for all markets. Weighted KNN caused a deterioration in the prediction accuracy of macro variables, and K of KNN increased with the horizon forecasted. In terms of predictive power of the variables, the yield curve on its own had predictive powers over long term equity markets, and the policy rate seemed to be affected by macro variables in the short term. Furthermore, the inflation and GDP were dominated by their own past values

    Post-Growth Geographies: Spatial Relations of Diverse and Alternative Economies

    Get PDF
    Post-Growth Geographies examines the spatial relations of diverse and alternative economies between growth-oriented institutions and multiple socio-ecological crises. The book brings together conceptual and empirical contributions from geography and its neighbouring disciplines and offers different perspectives on the possibilities, demands and critiques of post-growth transformation. Through case studies and interviews, the contributions combine voices from activism, civil society, planning and politics with current theoretical debates on socio-ecological transformation

    Influencers in Dynamic Financial Networks

    Get PDF
    To monitor risk in temporal financial networks, an understanding of how individual behaviours affect the temporal evolution of networks is needed. This is typically achieved using centrality and importance metrics, which rank nodes in terms of their position in the network. This approach works well for static networks, that do not change over time, but does not consider the dynamics of the network. In addition to this, current methods are often unable to capture the complex, often sparse and disconnected structures of financial transaction networks. This thesis addresses these gaps by considering importance from a dynamical perspective, first by using spectral perturbations to derive measures of importance for nodes and edges, then adapting these methods to incorporate a structural awareness. I complement these methods with a generative model for transaction networks that captures how individual behaviours give rise to the key properties of these networks, offering new methods to add to the regulatory toolkit. My contributions are made across three studies which complement each other in their findings. Study 1: \begin{itemize} \item I define a structural importance metric for the edges of a network, based on perturbing the adjacency matrix and observing the resultant change in its largest eigenvalues. \item I combine this with a model of network evolution where this metric controls the scale and probabilities of subsequent edge changes. This allows me to consider how edge importance relates to subsequent edge behaviour. \item I use this model alongside an exercise to predict subsequent change from edge importance. Using this I demonstrate how the model parameters are related to the capability of predicting whether an edge will change from its importance. \end{itemize} Study 2: \begin{itemize} \item I extend my measure of edge importance to measure the importance of nodes, and to capture complex community structures through the use of additional components of the eigenspectrum. \item While computed from a static network, my measure of node importance outperforms other centrality measures as a predictor of nodes subsequently transacting. This implies that static representations of temporal networks can contain information about their dynamics. \end{itemize} Study 3: \begin{itemize} \item I contrast the snapshot based methods used in the first two studies by modelling the dynamic of transactions between counterparties using both univariate and multivariate Hawkes processes, which capture the non-linear `bursty’ behaviour of transaction sequences. \item I find that the frequency of transactions between counterparties increases the likelihood of them to transact in the future, and that univariate and multivariate Hawkes processes show promise as generative models for transaction sequences. \item Hawkes processes also perform well when used to model buys and sells through a central clearing counterparty when considered as a bivariate process, but not as well when these are modelled as individual univariate processes. This indicates that mutual excitation between buys and sells is present in these markets. \end{itemize} The observations presented in this thesis provide new insights into the behaviour of equities markets, which until now have mainly been studied via price information. The metrics I propose offer a new potential to identify important traders and transactions in complex trading networks. The models I propose provide a null model over which a user could detect outlying transactions and could also be used to generate synthetic data for sharing purposes

    Contingent convertible bonds in financial networks

    Get PDF
    We study the role of contingent convertible bonds (CoCos) in a complex network of interconnected banks. By studying the system’s phase transitions, we reveal that the structure of the interbank network is of fundamental importance for the effectiveness of CoCos as a financial stability enhancing mechanism. Our results show that, under some network structures, the presence of CoCos can increase (and not reduce) financial fragility, because of the occurring of unneeded triggers and consequential suboptimal conversions that damage CoCos investors. We also demonstrate that, in the presence of a moderate financial shock, lightly interconnected financial networks are more robust than highly interconnected networks. This makes them a potentially optimal choice for both CoCos issuers and buyers

    Financial Stability Report. Spring 2023

    Get PDF

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

    Get PDF
    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

    Basel III: Implications of Capital and Liquidity Regulations on Financial Stability during Economic Depression.

    Get PDF
    The dynamic global financial system has made it necessary to implement adequate regulatory measures that can effectively guarantee financial stability at the national and international levels. This thesis consists of three self-contained analytical chapters that focus on the effectiveness of evolving financial regulations in addressing systemic risk within the financial system. Despite numerous regulatory reforms introduced following the 2008 GFC, they are still concerns over the role of these regulations in mitigating complex issues related to systemic risk. The first study focuses on international and national regulatory frameworks in the context of conventional, hybrid, and Islamic banking. It analyses the guidance provided by the Basel Committee on Banking Supervision (BCBS) and the Islamic Financial Services Board (IFSB) and examines the differences in the treatment of credit, liquidity, and systemic risk across four countries. The IFSB converts BCBS guidance to ensure compliance with Sharia principles for Islamic banks. Further insights show variations in liquidity and capital requirements imposed on banks in different countries, highlighting the need for countryspecific regulations to address the unique risks. The second study uses data from emerging market economies to investigate the relationship between capital and liquidity regulations under Basel III and their impact on default risk and systemic risk. The study addresses whether the new liquidity and capital requirements, such as the net stable funding ratio and higher capital adequacy ratio, contribute to alleviating the default risk and systemic risk in emerging market economies. The third study focuses on the relationship between credit and liquidity risks and their impact on bank default risk. It also addresses the effect of bank liquidity creation on systemic risk across different types of banks. The findings suggest that while credit and liquidity risks are positively related, no significant relationship exists. The impact of credit and liquidity risks on bank default risk is significant for conventional and hybrid banks, while bank size and capital adequacy ratio play a greater role in the stability of Islamic banks. The joint interaction between credit and liquidity risk negatively influences banking stability. The key findings demonstrate that Basel III's liquidity requirements, such as the Net Stable Funding Ratio (NSFR), play an important role in forecasting banks' default probability and mitigating systemic risk. The insights gathered emphasise the importance of incorporating new mitigating measures, including NSFR, leveraging requirements, countercyclical buffers, and globally systemically important institution surcharges to promote financial stability. Additionally, it demonstrates the relevance of liquidity creation in determining bank stability and its implications for systemic risk. This study offers substantial contributions to the growing body of literature by highlighting the differences in regulatory frameworks, the importance of this approach in developing bank risk profiles, and how they are adequately addressed. The study also contributes to understanding how financial stability can be enhanced while reducing systemic liquidity risk. The study shows that banks, regulators, and policymakers must collaborate adequately across all levels to align risk management and improve regulations and guidelines. This includes sharing information and fostering coordination at the international level

    Auf dem Weg zur Cyberpolis

    Get PDF
    Der soziale, kulturelle und politische Prozess der Digitalisierung hat neue Gemeinschafts- und Bildungsformen denkbar werden lassen, die u.a. durch drei Szenen entscheidend geprägt wurden: die kybernetisch-künstlerischen Hintergründe der PC-Kultur als Basis des Silicon Valley, die Popularisierung des Internets in den 1990er Jahren und aktuelle Entwicklungen, die unter dem Begriff des digitalen Nomadentums gefasst werden. Martin Donner und Heidrun Allert fragen vor dem Hintergrund der damit verbundenen Verschiebungen der Gemeinschaftsverständnisse nach praxistauglichen Gestaltungsmöglichkeiten der digitalen Gesellschaft
    • …
    corecore