Finance is as fragile as a house of cards, as complicated as a Rubik cube, and as intermingled as a bunch of mikado sticks. Science can help to sort out patterns in the complexity of the economic world. FOC has developed new tools to model, monitor, and visualize crucial patterns of financial crises.
and on Vimeo.
and on Vimeo.
Queries issued today on search engines can tell you something about how the stock market will go tomorrow, says Antti Ukkonen, computer scientist at Barcelona Media (Spain), partner of the FOC project.
Guido Caldarelli and the collaborator of FOC project Michele Catanzaro have published:
G. Caldarelli, M. Catanzaro “Networks. A Very Short Introduction” Oxford University Press. (US website)
SUMMARY: From ecosystems to Facebook and from the Internet to the global financial market, networks play a central role in nature and society. Phenomena such as climate change, pandemics, and financial crises are based on networked structures; and networks give insights into how social environments affect health and behaviour. In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and variety of networks, using familiar examples from society, technology, nature, and history. They show how networks self-organize and the role they play in processes like large-scale blackouts and computer virus outbreaks. They also describe the wide and important applications of network theory in a range of areas, including genetics, ecology, technology, and management.
Find in the following links a short video and a blogpost on the subject.
How to get it (£7.99, $11.95)
- Bookshops in UK and USA.
- Bookshops in Spain. Possibly, in La Central and Laie in the next few days: if you are interested, write at catanzaro [DOT] michele [AT] gmail [DOT] com and I will alert you when the book is available there.
- Amazon UK (Amazon US).
- Other online booksellers (for example Barnes&Noble).
- Ebook. Soon available for Kindle, Nook, Sony, Ebooks.com, Google Play, and Kobo : if you are interested, write at catanzaro [DOT] michele [AT] gmail [DOT] com and I will alert you when the book is available.
To know more about networks:
Large fluctuations in volatility and uncertainty is a crucial aspect to be understood to prevent future crises, says Austin Gerig, physicist at University of Oxford (UK), partner of the FOC project (Forecasting Financial Crises).
and on Vimeo.
and on Vimeo.
In the last few year a network of goods has grown worldwide, says Leonardo Bargigli, economist at Università Politecnica delle Marche (Italy), partner of the FOC project (Forecasting Financial Crises). FOC is a European scientific project aimed at understanding and forecasting systemic risk and global financial instabilities. focproject.net/
Financial regulators and policy makers should focus on financial institutions that are ‘too central to fail’ as well as those that are ‘too big to fail’, research published in Scientific Reports this week suggests. The quantitative analysis of emergency loans made by the US Federal Reserve Bank during the financial crisis highlights the importance of an institution’s position within a financial network.
Systemic risk — the risk of default of a large portion of a financial system — depends on the network of financial exposures among institutions, but there is no widely accepted method for working out which institutions in a network are the most important to the stability of the system. Inspired by feedback-centrality measures in networks, such as PageRank, Stefano Battiston and colleagues introduce a new measure of systemic impact, which they call DebtRank. They use DebtRank to analyze a recently released data set with information on the institutions that received aid from the US Federal Reserve Bank through its US$1.2 trillion emergency loans programmes from 2008 to 2010.
The authors find that during the peak of the crisis, a group of 22 financial institutions, which received most of the loans, became more central to the network, which means that the default of each one would have a larger economic impact on the whole network. Even small, dispersed shocks to individual banks could thus have triggered the default of a large portion of the system. The authors note that because the network of impact used in the study is a proxy of the real, unknown network, the findings should be regarded with caution, but the study shows the kinds of insights that can be gained using DebtRank.
Stefano Battiston (ETH Zurich, Switzerland) email@example.com
The DebtRank network of the top borrowers during the peak of the crisis. Nodes represent financial institutions among the most exposed to the FED. The outgoing links account fo the network effects where the potential impact of an institution to another one is computed with the DebtRank. In the diagram, if the position of a node is more central, the relative impact on the financial system, in case of default or financial distress, is larger. The colors of the nodes show the distress level, their sizes the debt with the FED.
Credit: Stefano Battiston
and on Vimeo.
Both good things and bad things spread fast through the channels of an interconnected economy, says Saquib Jafarey, economist City University London (UK), partner of the FOC project (Forecasting Financial Crises).