Economic Networks

EEIO in Sustainable Finance: Challenges and Opportunities

Presentation given at the 15th I-O Workshop, March 1st 2024, Osnabrueck, Germany

We discuss the overlap of EEIO tools with Sustainable Finance applications. In particular their potential role in Portfolio Management and, more specifically,

• the Attribution of environmental impact in financial portfolios and,
• the Allocation of future financial resources and sustainability constraints

We sketch two proof-of-concept computer applications that highlight opportunities and challenges:

Who Needs a New Financial Services Taxonomy?

Our age is increasingly dominated by the dual challenges and opportunities of the sustainability transition on the one hand, and digital transformation on the other. We witness emerging new financial domains with novel names such as Fintech , or TechFin, or various combinations and hues of Green and Sustainable in Sustainable Finance and we see forces that are reshaping the direction of travel for the financial industry.

Open Risk White Paper 15: Tensor Representations of ActivityPub Networks

In this third Open Risk White Paper on Connecting the Dots we explore representations of online communication networks that are organized according to the ActivityPub protocol. We discuss the main relevant features of the protocol and the broader application ecosystem around it that shapes emerging online network topologies. We develop a stylized description of ActivityPub compliant networks as a mathematical multilayer network. Tensor representations of such complex graphs generalize the more familiar matrix algebra tools and can be useful in various ways: On the one hand they help empirical work in analyzing the characteristics of such networks, on the other they enable simulating and exploring network behavior.

What are ActivityPub Networks?

ActivityPub is a technical specification towards decentralized (more precisely, federated) social networking (termed the Fediverse) based upon the exchange of ActivityStreams messages that follow the Activity Vocabulary. The ActivityPub proposal has been standardized and published by the W3C and has motivated the design of several federated social networking systems.

There are presently several concrete ActivityPub compliant implementations and the protocol sees meaningful adoption, primarily in the domain of federated social networks. Current ActivityPub networks consist of several million individual users, using several thousands of distinct servers, and a few dozens of distinct server types. An overview of ongoing network statistics is available here.

June 21 2023 marks 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.

Open Risk White Paper 14: Integrated energy accounting using relational databases

In this Open Risk White Paper we demonstrate a concrete implementation of an integrated energy accounting framework using relational database technologies. The framework enables accounting of non-financial disclosures (such as the physical and embodied energy footprints of economic transactions) while enforcing the familiar double-entry balance constraints used to produce conventional (monetary) accounts and financial statements. In addition, it allows enforcing constraints associated with the flow and transformations of energy that can happen inside the organizational perimeter.

Open Risk White Paper 13: Federated Credit Systems, Part II: Techniques for Federated Data Analysis

In this Open Risk White Paper, the second of series focusing on Federated Credit Systems, we explore techniques for federated credit data analysis. Building on the first paper where we outlined the overall architecture, essential actors and information flows underlying various business models of credit provision, in this step we focus on the enabling arrangements and techniques for building Federated Credit Data Systems and enabling Federated Analysis.

Course Objective

Digging into the meaning of credit data collections, the logic that binds them together towards understanding what they can be used for and what limitations and issues they may be affected by, this new course in the Credit Portfolio Management category explores a new angle to look at an old practice.

The course is now live at the Academy.

Pre-requisites

Familiarity with credit provision in general (lending products, banking processes and credit risk) is required for getting the most out of the course. Affinity with mathematical notation and language is also important.

Modeling economic networks and their dynamics

Economic networks are the primary abstractions though which we can conceptualize the state (condition) and evolution of economic interactions. This simply reflects the fact that human economies are quite fundamentally systems of interacting actors (or nodes in a network) with transient or more permanent relations between them.

In practice the network character of an economy is frequently suppressed or under-emphasized and does not play a particularly important role. This may be for reasons of expediency (inadequacy of data characterising the network in detail) or because the objectives of the analysis can be obtained without detailed micro-data that capture network properties (e.g., it may be sufficient to work with sectoral aggregates or “representative” agents).

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.

Open Risk White Paper 12: Deep-Linking Financial and Energy Accounting

We develop a conceptual framework for integrated accounting that produces (where possible) non-financial disclosures subject to the same double-entry balance constraints as those used to produce conventional financial statements and automatically ensures any additional conservation laws are satisfied. We identify the key ingredients required for such a rigorous integrated accounting framework, in terms of concepts, postulates and design choices. Our focus and concrete use case is built around energy accounting, keeping track on an entity’s detailed energy footprint (primary inputs, transformations and waste generation) as an extension of its standard financial accounting and reporting. The central tool is the use of multidimensional double-entry bookkeeping which tracks quantitative information characterizing economic objects beyond their monetary values. This choice ensures the enforcement of both classic balance constraints and any applicable energy conservation laws. Further tools and techniques concern the aggregation and reporting of dual (monetary and physical) dimensions of an entity’s accounting state. The framework is documented using mathematical notation.

Course Objective

The objective of the course is to discuss the relation of economic input-output models with graph theory and networks.

The course is now live at the Academy.

Pre-requisites

Basic knowledge of input-output models and graph theory would help to get the most out of the course but is not strictly required.

Summary of the Course

What we cover in this course:

• Step 1. In this step we discuss in more detail the motivation for the course and provide a very brief introduction to the graph theory to establish the notation.
• Step 2. In this step we explore the duality between graphs and matrix representations.
• Step 3. This step introduces the concept of Qualitative Input-Output Analysis
• Step 4. In the fourth step off the course we discuss Sources, Sinks and Conservation Laws
• Step 5.In the final step of the course discuss and interpret in graph terms the typical question one wants to answer with an IO model: what happens if there is new set of final demands?

What are Input-Output Models?

Environmentally Extended Multi-Regional Input-Output (EE-MRIO) tables describe economic relationships of economic actors (e.g. industrial sectors) operating within and between regions and their environmental repercussions.

An EE MRIO augments the more basic and historically first proposed Input-Output Models (IO) with additional datasets and/or modeling assumptions in order to provide insights into the environmental foorprint of economic activity. Presently, the emphasis on negative externalities of economic activity (e.g., climate change, biodiversity loss) turns EE MRIO models into a useful conceptual and analytic tool. Yet a good grounding on the underlying IO models is a prerequisite and this is the focus of this new course that is now available at the Open Risk Academy.

Open Risk White Paper 10: Connecting the Dots: Concentration, diversity, inequality and sparsity in economic networks

In this second Open Risk White Paper on Connecting the Dots we examine measures of concentration, diversity, inequality and sparsity in the context of economic systems represented as network (graph) structures. We adopt a stylized description of economies as property graphs and illustrate how relevant concepts can be represented in this language. We explore in some detail data types representing economic network data and their statistical nature which is critical in their use in concentration analysis. We proceed to recast various known indexes drawn from distinct disciplines in a unified computational context.

Concentration, diversity, inequality and sparsity in the context of economic networks

In this second Open Risk White Paper on Connecting the Dots we examine measures of concentration, diversity, inequality and sparsity in the context of economic systems represented as network (graph) structures. We adopt a stylized description of economies as property graphs and illustrate how relevant concepts can represent in this language. We explore in some detail data types representing economic network data and their statistical nature which is critical in their use in concentration analysis. We proceed to recast various known indexes drawn from distinct disciplines in a unified computational context.

Course Objective

Graphs (and the related concept of Networks) have emerged from a relative mathematical and physics niches to become mainstream models for describing and interpreting various phenomena. The objective of the course is to review various important graph types as they are increasingly explored in data science and sketch their linkages and relationships (a graph of graphs!).

It is not meant to be a rigorous mathematical or computer science classification of graphs but rather an operational guide towards a better overall understanding of those powerful tools.

The role of simulation in risk management and decision support

A Simulation is a simplified imitation of a process or system that represents with some fidelity its operation over time. In the context of risk management and decision support simulation can be a very powerful tool as it allows us to assess potential outcomes in a systematic way and explore what-if questions in ways that might otherwise be not feasible. Simulation is used when the underlying model is too complex to yield explicit analytic models (An analytic model is one can be “solved” exactly or with standard numerical methods, for example resulting in a formula).

Federated Credit Systems, Part I: Unbundling the Credit Provision Business Model

As an architectural design and information technology approach, federation has received increased attention in domains such as the medical sector (under the name federated analysis), in official statistics (under the name trusted data) and in mass computing devices (smartphones), under the name federated learning.

In this (the first of series of three) white paper, we introduce and explore the concept of federated credit systems. We first review the rapidly developing fields of Federated Analysis and Federated Learning as already actively studied in the domains of medicine and consumer computing devices. This forms the backdrop for understanding the potential and challenges of applying similar concepts in finance and more particular credit provision.

Open Risk White Paper 9: Federated Credit Systems, Part I: Unbundling The Credit Provision Business Model

In this (the first of series of three) white paper, we introduce and explore the concept of federated credit systems. We review the rapidly developing fields of Federated Analysis and Federated Learning as already actively studied in the domains of medicine and consumer computing devices. This forms the backdrop for understanding the potential and challenges of applying similar concepts in finance and more particular credit provision. The context of modern banking is substantially different from the above-mentioned use cases. Understanding and shaping federated information systems to cater to its unique features and constraints (key added value, competitive landscape, regulatory frameworks) will help accelerate the adoption of new designs. Towards that purpose we construct a framework that conceptually unbundles the complex operation that is modern credit provision. We introduce a number of fundamental business entities (subunits) and their associated functions and discuss the underlying business models. We discuss, in particular, how and why they exchange data and metrics and the key risk management challenges of each. Finally, we sketch current architectures for credit information sharing with an overture to the new possibilities opening up with federation architectures.

Course Content

This course is a CrashProgram (short course) introducing the GeoJSON specification for the encoding of geospatial features. The course is at an introductory technical level. It requires some familiarity with data specifications such as JSON and a very basic knowledge of Python

Who Is This Course For

The course is useful to:

• Any developer or data scientist that wants to work with geospatial features encoded in the geojson format

How Does The Course Help

Mastering the course content provides background knowledge towards the following activities: