ERCIM News 78
July 2009
Special theme Mathematics for Finance and Economy
Guest editor Ralf Korn (University of Kaiserslautern and Fraunhofer ITWM)
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by Ralf Korn
With so much science and so many applications focused on quantitative output, mathematics plays a key role in the design and evaluation of quantitative models. While in some cases simple or standard mathematics is enough to formulate models and support theories, sometimes methods are required that are very recent or even yet to be developed.
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by Paul Wilmott
I'm not sure readers of this magazine are going to be pleased with the following statement,
but here goes: "There is too much mathematics in finance". Ooh, er!
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by Marlene Müller
The financial mathematics department at the Fraunhofer Institute for Industrial Mathematics (ITWM) covers all important topics of modern financial mathematics which has been an extremely innovative research area during the last years.
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by László Gerencsér, Balázs Torma and Zsanett Orlovits
In modelling stock prices, two competing approaches exist: technical modelling and fundamental modelling. Technical models capture statistical phenomena observed directly in stock prices, while fundamental models consist of mathematical descriptions of the behaviour of economic agents that affect the stock price. Fundamental models incorporate minute details of the price generating process, and are thus more authentic than technical models. The development and analysis of multi-agent fundamental models has been the subject of research in the Stochastic Systems Research Group of SZTAKI since 2006.
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by Massimo Bernaschi, Maria Francesca Carfora, Albina Orlando, Silvia Razzano and Davide Vergni
Sovereign debt management is the process of establishing and executing a strategy for managing government debt. Among the main goals of a sound public debt management are i) to fulfil the funding requirements; ii) to minimize the cost of the debt and the related risk; and iii) to set up and control an efficient market for government securities. Our research is aimed at providing the mathematical tools for a cost/risk analysis of the portfolio of securities issued every month by the Italian Treasury. The final goal is to provide public debt managers with a flexible, efficient and user-friendly decision support tool.
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by Miklós Rásonyi
Despite of providing a good fit to financial data, asset price models with a fractal structure have often been rejected as they contradict a basic principle of economic theory: that arbitrage should be absent. In light of new results, their role must be reconsidered.
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by Xinzheng Huang and Cornelis W. Oosterlee
The last year has seen financial institutions worldwide announce writedowns of hundreds of billions of dollars as a result of participating in the US mortgage market, in particular in subprime and other lower-rated mortgage-backed securities. Improving the practice of credit risk management by banks has thus become a top priority. Researchers Huang (Delft University of Technology) and Oosterlee (CWI) in the Netherlands focus on quantifying portfolio credit risk by advanced numerical techniques with an eye to active credit portfolio management. This work is sponsored by the Dutch Rabobank.
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by Cornelis W. Oosterlee and Lech A. Grzelak
When the financial sector is in crisis, stocks go down and investors escape from the market to reduce their losses. Global banks then decrease interest rates in order to increase cash flow: this may lead to an increase in stock values, since it becomes less attractive for investors to keep their money in bank accounts. It is clear, therefore, that movements in the interest rate market can influence the behaviour of stock prices. This is taken into account in the so-called hybrid models currently being developed by researchers Grzelak (Delft University of Technology) and Oosterlee (CWI) from the Netherlands.
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by Jacek Jakubowski and Andrzej Palczewski
Modelling fixed income securities and managing risk in their portfolios is a challenging mathematical task requiring models with an infinite number of risk factors. We have designed new methods of dealing with the risk of defaultable bonds and risk diversification in large bond portfolios.
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by Olivier Davidau, Mireille Bossy, Nadia Maïzi and Odile Pourtallier
The carbon market was launched in the European Union in 2005 as part of the EU's initiative to reduce its greenhouse gas (GHG) emissions. This means that industrial players must now include their GHG emissions in their production costs. We aim to model the behaviour of an industrial agent who faces market uncertainties, and we compare the expected value of an optimal production strategy when buying (or not buying) supplementary emission allowances. This allows us to compute the agent's carbon indifference price which defines its market behaviour (buyer or not). We aim to use the resulting indifference price to study the sensitivity of the carbon market to the shape of the penalty and the emission allowances allocation.
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by Rob van der Mei, Kevin Pak, Maarten Soomer and Ger Koole
Revenue Management (RM) techniques provide a powerful means of increasing revenue, creating new business opportunities for companies in a wide variety of business areas. Recently, the authors have successfully applied RM techniques for one the worlds largest parking companies, creating millions in additional yearly revenue.
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by Stefano Basta, Fosca Giannotti, Giuseppe Manco, Dino Pedreschi and Laura Spinsanti
An effective audit strategy is a key success factor for 'a posteriori' fraud detection applications in fiscal and insurance domains. 'Sniper' is an auditing methodology with a rule-based system, which is capable of dealing with conflicting issues such as maximizing audit benefits, minimizing false-positive audit predictions and deterring probable future fraud.
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by Marco Remondino and Marco Pironti
We apply computational modelling and simulation to enterprise economics and the underlying network dynamics. Here, we briefly describe a comprehensive framework.
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by João Oliveira Soares
Diverse case studies carried out at CEGIST (Centre for Management Studies) at the Technical University of Lisbon have a common root: the support and analysis of investment decisions made by public authorities, banks and private firms. The approach comprises multiple dimensions and reflects on the use of statistical and quantitative methods along with qualitative criteria and judgment-based procedures. Recent work also adds flexibility and risk issues to this multidimensional context.
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by Agnès Sulem and Antonino Zanette
PREMIA is a computational platform designed to set up a technology watch for numerical problems related to the evaluation of financial derivative products and the management of pertinent risks. It is developed by the MATHFI research team at INRIA.
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by John Barr
The computational power required to participate successfully in todays financial markets is growing exponentially, but the performance of commodity processors is not keeping pace. How can firms harness innovative technology to achieve success? Two financial and two technology issues are combining to force a radical rethink of how financial algorithms are computed.
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by Marco Hülsmann, Christoph M. Friedrich and Dirk Reith
The Fraunhofer-Institute for Algorithms and Scientific Computing (SCAI) has developed a software tool for sales forecasts using a methodology that consists of a combination of time series analysis and data mining techniques.
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by Gerard Torrent
Financial institutions need tools to simulate their credit portfolios in the same way that they simulate their equity portfolios. CreditCruncher allows each payment in a massive loan portfolio to be simulated, taking into account the probability of default for each creditor and the correlations between them.
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by Pierluigi Contucci and Francesca Romiti
Will the noble (and sometimes snobbish) queen of sciences mathematics have a role in the future study of economics? Will the role it plays (if any) be as crucial as in the physical sciences? We argue that mathematics will very likely have a pivotal beneficial mutual exchange with economics, particularly through the study of statistical mechanical models of complex systems.