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    Academy News

    Solstice - a new framework for simulating economic networks

    by Ad Min -
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    Dear all,

    we've started  releasing bits and pieces of a new open source tool we are building (the Solstice simulation framework) on our github repo and more is comming over the next weeks. You can check out the first installment of the Solstice manual which describes the analytic framework behind Solstice. 

    The analytic framework has the following core components:

    • A representation of economic entities as property graphs (nodes and edges with associated attributes) as discussed in our earlier white papers (number 8 and 10 in particular)
    • A representation of network-wide factors and dynamics drivers as macro variables
    • Sources of uncertainty (both macro (system-wide) and idiosyncratic (entity-specific)
    • A discrete temporal grid where future states of the economic network and (any) macro variables are modeled
    • Network evolution along the temporal grid due to both deterministic and stochastic elements that follows by a variety of risk distributions / models using potentially a combination of model components (satellite models)
    • Bottom up composition of network state changes using elementary "system updates"
    • Ability to condition on specific realizations of (in particular) macro factors, which emulates scenario analysis / stress testing
    • Introducing special entities that interact with the network in systemic ways (e.g. financial intermediaries, sovereigns or regulatory entities) with specialized internal states
    • Collection of sampling statistics of network evolution and distillation of useful risk metrics and reports

    If you are interested to use and/or contribute to our open source projects please follow and star them on github and (if appropriate) raise issues with ideas or functionality that you would like to see.

    the logo of the Solstice framework

    Step into python data science the hacktoberfest way. Two small libraries that can help you get started

    by Ad Min -
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    Machine learning and data science turned python from a niche scripting language into one of the most popular developer ecosystems. From numpy and pandas to scikit-learn and pytorch and tensorflow to name but a few, there are some amazing python open source frameworks out there. These projects have completely transformed what people can do with data. What used to be expensive, proprietary and arcane software is now one pip install away!
    Hacktoberfest is a great excuse to get involved with python data science and learn what all the excitement is about.

    What is hactoberfest??

    Hacktoberfest is an annual global hackathon event celebrating open source software hosted by DigitalOcean in partnership with Github. The event was created to raise awareness for the open source community and encourage participation in open source projects. Participants are challenged to contribute a specific amount of pull requests during the month of October to public open source repositories on GitHub in order to earn a limited-edition T-shirt and swag from the host and sponsors.

    The catch is that these are sophisticated and mature frameworks, frequently using also optimized C/C++ code underneath the hood. But there is also the "long tail" of niche python libraries and tools that focus on some specific data science task and these might be an easier stepping stone for aspiring data scientists.
    Two such libraries you can contribute to this hactoberfest are https://github.com/open-risk/transitionMatrix and concentrationMetrics. Here is a brief description of what they are about and how you can contribute:


    transitionMatrix is a library for the statistical analysis and visualization of state transition phenomena. It can be used to analyze (produce a transition matrix) for any dataset that captures timestamped transitions in a discrete state space. You can use the library to:
    • Estimate transition matrices from historical event data using a variety of estimators
    • Manipulate transition matrices (generators, comparisons etc.)
    • Visualize event data and transition matrices
    • Provide standardized data sets for testing
    • Model transitions using threshold processes
    • Map credit ratings using mapping tables between popularly used rating systems
    Use cases include credit rating transitions in finance, system state event logs etc.


    concentrationMetrics is a python library for the computation of various concentration, diversification and inequality indices. You can use concentrationMetrics to
    • access an exhaustive collection of such indexes and metrics
    • perform file input/output in both json and csv formats
    • compute indexes with confidence intervals via bootstraping
    • visualize using matplotlib

    How you can contribute

    First things first, make sure you read the hactoberfest participation guidelines!
    • fork the repos from the above links
    • look at the code / documentation and / try the examples
    • find bugs or other issues and raise issues
    • think and work on possible extensions, better documentation or any other ideas that fit within the scope of each library
    • eventually contribute via a pull request
    • get a tree planted in your name, or the Hacktoberfest 2022 t-shirt :-)
    Good luck, enjoy hactoberfest and hope to see you around the python metaverse!

    New season, new members and new Open Risk White Paper

    by Ad Min -
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    Dear Academy users,

    we are officially past the Fall Equinox for 2022 and the new season is in full swing. We have also reached a milestone of more than 1500 registered users on the site. A warm welcome to all new Open Risk Academy enthousiasts!

    A new Open Risk White Paper that might be of interest to some of you focuses on sustainability accounting and in particular how to elevate the reporting of non-financial data to the same level of rigor offered by double-entry bookkeeping practices. 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. The blog post has a summary overview, while the pdf is available here.


    Pictogram of a balance, with an energy amount on the left and a monetary amount on the right

    Sustainable Procurement with Equinox, Open Data and Open Source

    by Ad Min -
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    Adressing sustainability is a major challenge (and opportunity) facing portfolio managers in diverse domains. If sound financial portfolio (and risk) management was not already enough of a challenge, integrating totally new and diverse data streams about environmental impacts, new objective functions that go beyond monetary measures, new and evolving environmental policies and targets is a major journey that has barely begun.

    Some Academy users might be already familiar with  equinox, our open source sustainable portfolio management platform. In a new series of blog posts we explored how it can be used to support sustainable procurement management. In procurement, the financial portfolio is a collection of contracts where the counterparties are various suppliers of goods, works or services.

    The use case is built around the TED, an Open Data database In the European Union that is the pre-eminent platform collecting data about public procurement. In the first post we explore the overall shape of the dataset which is quite large (over three millions of contracts between 2017-2021)!

    The value distribution of contracts in the TED database

    In the second post we dig deeper into important facets of the data, with the aim of constructing a meaningful economic representation of the public procurement process. Most importantly this involves identifying who is the procurement manager and who are their counterparties. The geographic distribution of contracting entities cover the entire European region (every NUTS3 region)

    Distribution of contracting authorities in Europe

    In the third part of this series we illustrate how one may assign greenhouse gas emissions (GHG) to public procurement using environmentally extended input-output models. Public procurement represents final demand of the public sector (which ultimately provides services to households). Towards that end we adopt datasets produced by Eurostat as the basis for the GHG attribution. Specifically, Eurostat produces the statistics with a production and consumption perspective and re-publishes the territorial statistics of the European Environmental Agency (EEA). For this exercise we utilized emissions intensity estimates.  As outcome we can generate a variety of reports and visualizations, such as a sector-by-country grid of attributed emissions:

    A tabular representation of procurement emissions by sector and country

    Finally, we conclude the discussion with an overview of the conceptual data models involved and future applications that may involve additional geospatial data linked to emissions sources.


    Visual representation of hypothetical emissions sources on a map

    EU Datathon 2022 preselection for the Equinox platform

    by Ad Min -
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    We are very happy to announce that our EU Datathon 2022 proposal based on the Equinox platform has been pre-selected to enter the formal stage of the competition

    The EU Datathon is an annual Open Data competition organised by the Publications Office of the European Union since 2017. The competitions are organised to create new value for citizens through innovation and promoting the use of open data, in particular the datasets available on the official portal for European data

    As Open Risk we submitted a proposal under Challenge 2 (Transparency in Public Procurement) that aims to integrate the rich dataset of the TED (Tenders Electronic Daily) dedicated to European public procurement into Equinox, thereby offering an innovative and powerful platform that supports green public procurement using the full machinery of Sustainable Portfolio Management.

    We are very happy to announce that the proposal has been pre-selected to enter the formal stage of the competition!

    A slide including the teams and proposals that were preselected by the EU Publications office to take part in the EU Datathon

    Are you interested in topics around sustainable finance and portfolio management? Your feedback, ideas and contributions, whether technical or non-technical are welcome for example:

    Interest to learn more about these topics?

    Sustainable Finance Topic Taxonomies

    by Ad Min -
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    The Open Risk Manual contains now quite a number of topics related to sustainable finance. The related category page has been augmented to organize them in a logical manner: There are two main schemes (arranged as matrices):

    • Grouping of concepts by economic entity (agent) and their financial activities (e.g. individuals, corporates and their typical respective economic activity that are affected by sustainability)
    • Grouping of concepts by the 17 Sustainable Development Goals and the available tools such as information technology, policies etc
    Snapshot of an Open Risk Manual table organizing various sustainable finance concepts
    As with all entries of the Manual, this is a live page that continues being updated. Suggestions always welcome!

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