June 21 is the sixth annual #ShowYourStripes Day - a time when meteorologists and other climate communicators around the world raise awareness of our warming planet by displaying colorful visuals of climate change. The warming stripe graphics are representations of the change in temperature over the past 100+ years (here we use the global average). Each stripe represents the temperature averaged over a year. The stripes typically start around the year 1900 and finish in 2022.
Integrated Energy Accounting is keeping track and reporting on an entity’s detailed energy footprint (primary inputs, transformations and waste generation) not as an addendum to financial accounting and reporting but as a deeply-linked extension that is subject to the same level of rigor. The central design is the use of multidimensional double-entry bookkeeping which tracks additional quantitative information characterizing economic objects beyond their monetary values. This choice ensures the enforcement of both classic balance sheet constraints and the applicable energy conservation laws.
Motivation Fig 1. An economic network as a graph. The economy is a complex tangle of various agents that interact via transactions (sales and purchases) and contracts (lending, investing). In recent times more and more techniques from graph theory and network science are brought to bear on economic analysis. On the other hand, ever since the seminal contributions of Leontief, Input-Output Models (IO) have been widely used to describe economic relationships between economic actors (e.
The frontpage graphic is adapted from Steffen et al. “Planetary Boundaries: Guiding human development on a changing planet”. Science (2015). The Planetary Boundaries concept was proposed in 2009 by this group of Earth system and environmental scientists. The group suggested that finding a “safe operating space for humanity” is a precondition for sustainable development. The framework is based on scientific evidence that human actions since the Industrial Revolution have become the main driver of global environmental change.
Agent-Based Models The origins and early years According to Wikipedia an agent-based model (ABM) is ABM: class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. A cellular automaton is a particular class of ABM. It is a discrete dynamical model used and studied in a variety of fields: computer science, mathematics, physics, complexity science, theoretical biology among others.
Course Content This course is an introduction to the concept of credit contagion. It covers the following topics: Contagion Risk Overview and Definition Various Contagion Types and Modelling Challenges The Simple Contagion Model by Davis and Lo Supply Chains Contagion Sovereign Contagion Who Is This Course For The course is useful to: Risk Analysts across the financial industry and beyond Risk Management students Quantitative Risk Managers developing or validating risk models How Does The Course Help Mastering the course content provides background knowledge towards the following activities:
Connecting the Dots: Economic Networks as Property Graphs We develop a quantitative framework that approaches economic networks from the point of view of contractual relationships between agents (and the interdependencies those generate). The representation of agent properties, transactions and contracts is done in the a context of a property graph. A typical use case for the proposed framework is the study of credit networks. You can find the white paper here: (OpenRiskWP08_131219)
Open Risk White Paper 8: Connecting the Dots, Economic Networks as Property Graphs We develop a quantitative framework that approaches economic networks from the point of view of contractual relationships between agents (and the interdependencies those generate). The representation of agent properties, transactions and contracts is done in the context of a property graph. A typical use case for the proposed framework is the study of credit networks. Download OpenRiskWP12_230922 PDF
The motivation for federated credit risk models Federated learning is a machine learning technique that is receiving increased attention in diverse data driven application domains that have data privacy concerns. The essence of the concept is to train algorithms across decentralized servers, each holding their own local data samples, hence without the need to exchange potentially sensitive information. The construction of a common model is achieved through the exchange of derived data (gradients, parameters, weights etc).