A GSOC 2021 summer project collaboration between Open Risk and the Hydra Ecosystem Summer is underway and for the Google Summer of Code 2021 season Open Risk is happy to join forces with the Hydra Ecosystem. The project aims to guide students to build a hypermedia enabled REST service around standardized credit portfolio data. More specifically the project will build a REST service as backend for a hypothetical banking entity that collects and disseminates credit portfolio data conforming to an established public standard (the EBA NPL templates, see below).
Equinox is an open source platform that supports risk management and reporting of Project Finance. The platform integrates geospatial information with applicable regulatory and industry standards from EBA, PCAF and Equator Principles to provide a holistic view of the footprint of both individual projects and portfolios of project finance investments. Motivation Sustainability (understood in environmental, economic and social terms) is emerging as an undisputed constraint that will shape future human activity and more specifically how the financial system facilitates and empowers economic life.
Semantic Web Technologies integrate naturally with the worlds of open data science and open source machine learning, empowering better control and management of the risks and opportunities that come with increased digitization and model use The ongoing and accelerating digitisation of many aspects of social and economic life means the proliferation of data driven/data intermediated decisions and the reliance on quantitative models of various sorts (going under various hashtags such as machine learning, artificial intelligence, data science etc.
Celebrating Pi Day 2021 Pi Day is celebrated every year on March 14th. The reason of course is that the day is denoted in some calendars as (3/14), which evokes of 3.14, the first three digits of “π”. A thin excuse maybe but sufficient for the true believers to join along! The occasion represents an annual opportunity for mathematics and science enthusiasts to recite the infinite charms of Pi, including its irrationality, to talk to friends and family about math and its uses, and, when everything else fails, simply eat pie.
Course Content: This CrashCourse is an introduction to semantic data using Python. It covers the following topics: We learn to work with RDF graphs using rdflib We explore the owlready package and OWL ontologies We look into json-ld serialization of RDF/OWL data We try data validation using pySHACL We use throughout a realistic data set based on the Credit Ratings Ontology Who Is This Course For: The course is useful to:
Using Sankey Diagrams: Sankey Diagrams are a type of flow diagram composed of interconnected arrows. The width of the arrows is proportional to the flow rate. Sankey diagrams are often used in physical sciences (physics, chemistry, biology) and engineering but also in economics. They can be used to represent the relative role and significance of various inputs and outputs in a given process. Sankey diagrams emphasize the major transfers within a system.
openNPL 0.2 release: The open source openNPL platform supports the management of standardized credit portfolio data for non-performing loans. In this respect it implements the detailed European Banking Authority NPL loan templates. It aims to be at the same time easy to integrate in human workflows (using a familiar web interface) and integrate into automated (computer driven) workflows. The latest (0.2) release exposes a REST API that offers machine oriented access using, what is by now, the most established mechanism for achieving flexible online data transfers.
openNPL now Available in Dockerized Form: Following up on the first release of openNPL the platform is now available to install using Docker. Running openNPL via docker is the installation option that simplifies the manual process (but a working docker installation is required!). Docker Hub You can pull the latest openNPL image from Docker Hub (This method is recommended if you do not want to mess with the source distribution).
What this blog post is about (and what it isn’t): With the ever more widespread adoption of Data Science, defined as the intensive use of data in various forms of decision making, there is a renewed interest in Visualization as an effective channel for humans to understand data at various stages of the data lifecycle. There is a large variety of data visualization tools which can produce an ever more bewildering variety of visualization types
Non-Performing Loans: The covid-19 crisis will certainly impact the concentration of Non-Performing Loans but given the special nature of this economic crisis compared (in particular) with the 2008 financial crisis it is unclear how precisely things will evolve. In a previous post and white paper (OpenRiskWP07_022616) we discussed the importance of advancing open and transparent methodologies for managing the risks associated with such credit portfolios. Effective management of NPL is also a top regulatory priority.
Open Source Securitisation: Motivation After the Great Financial Crisis securitisation has become the poster child of a financial product exhibiting complexity and opaqueness. The issues and lessons learned post-crisis were many, involving all aspects of the securitisation process, from the nature and quality of the underlying assets, the incentives of the various agents involved and the ability of investors to analyze the products they invested in. While the most egregious complications involved various types of re-securitisation and/or the interplay of structured credit derivatives undoubtedly even vanilla securitisation structure has a considerable amount of business logic.
Release of version 0.4.1 of the transitionMatrix package focuses on stressing transition matrices: Further building the open source OpenCPM toolkit this realease of transitionMatrix features: Feature: Added functionality for conditioning multi-period transition matrices Training: Example calculation and visualization of conditional matrices Datasets: State space description and CGS mappings for top-6 credit rating agencies Conditional Transition Probabilities The calculation of conditional transition probabilities given an empirical transition matrix is a highly non-trivial task involving many modelling assumptions.
Release of version 0.4 of the transitionMatrix package: Further building the open source OpenCPM toolkit this realease of transitionMatrix features: Feature: Added Aalen-Johansen Duration Estimator Documentation: Major overhaul of documentation, now targeting ReadTheDocs distribution Training: Streamlining of all examples Installation: Pypi and wheel installation options Datasets: Synthetic Datasets in long format Enjoy!
Release of version 0.4 of the Concentration Library adds Geographic / Industrial concentration indexes: Further building out the OpenCPM set of tools, we release version 0.4 of the Concentration Library, a python library for the computation of various concentration, diversification and inequality indices. The below list provides documentation URL’s for each one of the implemented classic indexes (the Hoover index is a new addition in this release Atkinson Index Hoover Index Concentration Ratio Berger-Parker Index Herfindahl-Hirschman Index Hannah-Kay Index Gini Index Theil Index Shannon Index Generalized Entropy Index Kolm Index An important new direction that appears first in this release is the introduction of indexes that measure geographical and industrial concentration.
Representing economic activity using pictograms: Visualization can produce significant new insights when applied to quantitative data. It is currently undergoing a renaissance that mirrors other developments in computing and data science. Sophisticated open source libraries such as d3.js or matplotlib, to name but a couple, are enabling an ever wider range of users to distill valuable information from the avalanche of data being produced. Yet when it comes to visualizing data that relate to abstract concepts it can be quite difficult to find an appropriate grammar to express the quantitative context.
Extending the Open Risk API to include the EBA Portfolio Data Templates: The Open Risk API provides a mechanism to integrate arbitrary collections of risk data and risk modelling resources in the context of assessing and managing financial risk. It is based on two key technologies of the modern Web, RESTful architectures and Semantic Data. OpenCPM, the credit portfolio management platfrom we launched recently fully integrates the latest versions of the Open Risk API.
Release of version 0.3 of the Concentration Library: Further building out the OpenCPM set of tools, we release version 0.3 of the Concentration Library. This python library for the computation of various concentration, diversification and inequality indices. The below list provides documentation URL’s for each one of the implemented indexes Atkinson Index Concentration Ratio Berger-Parker Index Herfindahl-Hirschman Index Hannah-Kay Index Gini Index Theil Index Shannon Index Generalized Entropy Index Kolm Index The image illustrates a simple use of the library where the HHI and Gini indexes are computed and compared for a range of randomly generated portfolio exposures.
Motivation for Building an open source database based on EBA’s Standardized NPL Templates In a recent insightful piece “Overcoming non-performing loan market failures with transaction platforms”, Fell et al. dug deeply into the market failures that help perpetuate the NPL problem. They highlight, in particular, information asymmetries and the attendant costs of valuing NPL portfolios as key obstacles. In the same wavelength, the European Banking Authority published standardized NPL data templates as a step towards reducing the obstacles that prevent the reduction of NPL’s.
Open Risk released version 0.1 of the Transition Matrix Library Motivation: State transition phenomena where a system exhibits stochastic (random) migration between well defined discrete states (see picture below for an illustration) are very common in a variety of fields. Depending on the precise specification and modelling assumptions they may go under the name of multi-state models, Markov chain models or state-space models. In financial applications a prominent example of phenomena that can be modelled using state transitions are credit rating migrations of pools of borrowers.
Loan Level Templates Using Python: In this Open Risk Academy course we figure step by step how to use python to work with Loan Level Templates, using the ECB SME template as an example. Overview of the loan level template Manipulating spreadsheets with Python The Python Dictionary Organization of Portfolio Data Generating Test Portfolios Get an Open Risk Academy account and get started with the course here