Happy New Year Everyone. The last half of the previous year was a bit quieter for this blog, mainly because I was busy on my grand project: the Financial Network Analytics (FNA) web service and enterprise software. The project is getting closer to an official release and FNA now has its own website at www.fna.fi. You can sign up there and try it online.

The second big change is that this blog has moved to www.fna.fi/blog/. It will maintain its original purpose of being a focal point for research and news on network analysis and agent-based models of financial systems. The complete three-year history of the blog will be available in the new address as well. Please update your bookmarks and sign up to the e-mail alerts if you have not done so yet. Alternatively, you can also follow the blog and other updates on Twitter and Facebook.

Thirdly, the Research Database has moved to www.fna.fi/library/. It now has a much better user interface and it is easier to browse and find articles. Perhaps importantly to some, you can also get bibtex references of each article. The library has some 110 articles and I am working on an update. Please let me know if yours is missing.

After a busy summer we are proud to release the first online version of the FNA (Financial Network Analytics) platform at www.fna.fi. The site is currently in ‘private alpha’ stage. This means that all main functionality is available but it may not be completely polished yet.

FNA is an application for exploring, analyzing and visualizing financial networks – in a way that much of the research featured in this blog has shown is useful and important. Below is a short “Getting started” video tutorial. In the video I create networks from link data, do centrality analysis of the network and visualize the results.

FNA is intended as a tool for financial regulators and overseers to analyze regulatory data with the tools of network analysis and simulations – and to explore the financial system through visualisations. In addition to the web version, FNA can be installed on company intranets and as a desktop software.

The tool is probably also interesting for researchers in the area. Our plan is to directly connect more data to the online platform so that the cumbersome steps of data cleaning and formatting can be bypassed. Currently a full time series of BIS statistics on banking sector claims by country is included (Table 9D). Better availability of public data should lower the entry barriers to this type of financial research. Also, when both research and policy analysis are available on the same platform, new research models can be made available for policy makers for empirical testing in a resource efficient way.

As for developers, FNA has a modular structure and allows new functionality and models to be easily added. Currently we have plugins for network analysis, basic charts, network layouts, data cleaning tools, a payment system simulator and an algorithm for identifying overnight and term loans from payment data. You can read more about these in earlier posts (1, 2). If you are a researcher or developer, you can have your models run from FNA via our API. You can use all the graphical user interface, data visualization and graph database functionality of FNA in your code. Please get in touch if you would like to know more.

Go to www.fna.fi

For the last couple of months we have been working hard on the new version of FNA. FNA is a platform for analyzing, exploring and visualizing financial networks (download FNA Info sheet).

Working with large (often messy) datasets is hard, so our focus has been to make it as easy and intuitive as possible. Thus FNA has features starting from cleaning and validating data, calculating network metrics to eventually visualizing and modeling the analyzed system.

We now have a ‘functioning prototype’ almost finished. We are now ironing out a few details and it will be available online in about a month for everyone to try it out. Meanwhile the following screenshots provide a preview.

FNA is based on web technologies and runs on your browser. The server where the commands execute can be installed on your local desktop, on the company intranet or you can use the web version running on our servers.

In addition to the command line interface (Picture 1) already available in the previous version, you can now also give commands with mouse by point-and-click (Picture 2). The command line interface itself is improved with an ‘auto-suggest’ function. As working with different files is often a slowing factor in analysis, the new FNA integrates file management into the user interface (panels on the right).

Picture 1 : Command line user interface

Picture 2: Point-and-click user interface

A major new feature set are visualizations. First of all you can several different network layouts. Currently we have a force-directed network layout (Picture 3), arc layout and a geographic overlay of networks available (Picture 4). As these are based on JavaScript templates (the ones below use Protovis) it will be easy for us to add new ones on the fly. If you have more than one network in memory, a similar chart is automatically created for all networks allowing you to browse the results quickly visually. The layouts are interactive allowing you to select, zoom and get more details on the network elements. You can also export them keeping interactivity.

Picture 3: Force-directed network layout

Picture 4: Geographic network layout

There are also many more familiar chart types (line, pie, bar, scatter plot, etc) available which can show statistics from any arc, vertex or network properties.

If you would like to learn more about FNA or participate in developing and testing it, please get in touch with us.

Here are a few papers that were recently added to the database.

A network analysis of global banking:1978-2009 (April 2011) by Camelia Minoiu and Javier A. Reyes carries out an empirical analysis on the structure and statistical properties of the global banking network. They use cross-border bank lending data for 184 countries over 1978–2009. They find that the network has several structural breaks in network indicators that relate to several waves of capital flows. Connectivity of the network tends to fall during and after systemic banking crises and sovereign debt crises. The 2008–09 global financial crisis stands out as an unusually large perturbation to the cross-border banking network.

Network view of cross-border banking in 2007 (Minoiu and Reyes 2011)

Measuring the systemic importance of interconnected banks (March 2011) by Mathias Drehmann and Nikola Tarashev develops a measure of systemic importance based on how banks propagate shocks across the banking system and are vulnerable to propagated shocks. They find substantial differences between alternative measures, which implies that prudential authorities should be careful in choosing the underlying approach.

Macro-prudential Regulation from the Perspective of the Financial Network: Empirical Analysis Based on the Data from Payment and Settlement System in China (April 2011) by Yandong Jia analyzes the properties of the Chinese banking network and proposes methods for macro-prudential supervision based on network analysis.

Complex stock trading network among investors (March 2010) by Zhi-Qiang Jiang and Wei-Xing Zhou analyze the statistical properties of stock trading networks based on order flow data of a highly liquid stock (Shenzhen Development Bank) listed on Shenzhen Stock Exchange during the whole year of 2003.

Financial Connections and Systemic Risk (July 2010) by Franklin Allen, Ana Babus and Elena Carletti develops a model where institutions form connections through swaps of projects in order to diversify their individual risk. They find that network structure matters when short-term financing is used. If expectations on payback are low, systemic consequences are created by banks decisions not to roll over the short term debt.