IMT Institutional Repository: No conditions. Results ordered -Date Deposited. 2022-05-21T03:18:16ZEPrintshttp://eprints.imtlucca.it/images/logowhite.pnghttp://eprints.imtlucca.it/2021-07-19T09:36:23Z2021-07-19T09:39:43Zhttp://eprints.imtlucca.it/id/eprint/4082This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/40822021-07-19T09:36:23ZPredicting Exporters with Machine LearningIn this contribution, we exploit machine learning techniques to predict out-of-sample firms'
ability to export based on the financial accounts of both exporters and non-exporters. Therefore,
we show how forecasts can be used as exporting scores, i.e., to measure the distance of
non-exporters from export status. For our purpose, we train and test various algorithms on the
financial reports of 57,021 manufacturing firms in France in 2010-2018. We find that a Bayesian
Additive Regression Tree with Missingness In Attributes (BART-MIA) performs better than
other techniques with a prediction accuracy of up to 0:90. Predictions are robust to changes in
definitions of exporters and in the presence of discontinuous exporters. Eventually, we argue
that exporting scores can be helpful for trade promotion, trade credit, and to assess firms'
competitiveness. For example, back-of-the-envelope estimates show that a representative firm
with just below-average exporting scores needs up to 44% more cash resources and up to 2:5
times more capital expenses to reach full export status.Francesca Micoccifrancesca.micocci@imtlucca.itArmando Rungiarmando.rungi@imtlucca.it2020-06-15T11:52:24Z2020-06-15T12:06:00Zhttp://eprints.imtlucca.it/id/eprint/4077This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/40772020-06-15T11:52:24ZMachine Learning for Zombie Hunting.
Firms’ Failures and Financial Constraints.In this contribution, we exploit machine learning techniques to predict the risk of failure of firms.
Then, we propose an empirical definition of zombies as firms that persist in a status of high
risk, beyond the highest decile, after which we observe that the chances to transit to lower risk
are minimal. We implement a Bayesian Additive Regression Tree with Missing Incorporated in
Attributes (BART-MIA), which is specifically useful in our setting as we provide evidence that
patterns of undisclosed accounts correlate with firms’ failures. After training our algorithm
on 304,906 firms active in Italy in the period 2008-2017, we show how it outperforms proxy
models like the Z-scores and the Distance-to-Default, traditional econometric methods, and
other widely used machine learning techniques. We document that zombies are on average
21% less productive, 76% smaller, and they increased in times of financial crisis. In general,
we argue that our application helps in the design of evidence-based policies in the presence of
market failures, for example optimal bankruptcy laws. We believe our framework can help to
inform the design of support programs for highly distressed firms after the recent pandemic
crisis.Falco J. Bargagli-Stoffifalco.bargaglistoffi@imtlucca.itMassimo Riccabonimassimo.riccaboni@imtlucca.itArmando Rungiarmando.rungi@imtlucca.it2018-03-09T13:10:49Z2018-03-09T13:10:49Zhttp://eprints.imtlucca.it/id/eprint/3996This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/39962018-03-09T13:10:49ZComplexity in Neural and Financial Systems: From Time-Series to Networks (editorial)Tiziano Squartinitiziano.squartini@imtlucca.itAndrea GabrielliDiego Garlaschellidiego.garlaschelli@imtlucca.itTommaso GiliAngelo BifoneFabio Caccioli2018-01-16T10:04:27Z2018-01-16T10:04:27Zhttp://eprints.imtlucca.it/id/eprint/3861This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/38612018-01-16T10:04:27ZThe Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the
Global Financial CrisisNetwork theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk diversification by individual investors. We
nvestigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and analyse the interplay between diversification, as understood in classical portfolio theory, and similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from models of random allocation of investments. This indicates the existence of strong correlations between fund portfolio strategies. We introduce a simplified model of propagation of financial shocks, that we exploit to show that a systemic risk component origins from the similarity of portfolios. The network is still vulnerable after crisis because of this effect, despite the increase in the diversification of portfolios. Our results indicate that diversification may even increase systemic risk when funds diversify in the same way. Diversification and similarity can play antagonistic roles and the trade-off between the two should be taken into account to properly assess systemic risk.Danilo DelpiniStefano BattistonGuido Caldarelliguido.caldarelli@imtlucca.itMassimo Riccabonimassimo.riccaboni@imtlucca.it2017-11-29T09:28:46Z2017-11-29T09:28:46Zhttp://eprints.imtlucca.it/id/eprint/3842This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/38422017-11-29T09:28:46ZDoes corporate control matter to financial volatility?In our contribution we study how the ownership channel affects the stock price volatility
of listed stock markets. In particular, we study how a linkage between a parent company and
its affiliates may drive differences in stock price volatility, within and across countries. We
exploit a worldwide dataset of stock-exchange listed firms, controlling for several financial
dimensions, to assess whether business groups matter to financial volatility. The answer is
positive and does not depend on the definition of volatility used. Our results contribute to
the corporate finance literature by defining the role of multinational corporate control in
financial markets, and to the financial stability literature by assessing corporate control as
an undiscovered channel of transmission for financial shocks.Laura Gianfagnalaura.gianfagna@imtlucca.itArmando Rungiarmando.rungi@imtlucca.it2017-09-04T09:15:17Z2017-09-04T09:20:20Zhttp://eprints.imtlucca.it/id/eprint/3767This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/37672017-09-04T09:15:17ZGlobal ownership and corporate control networksIn this contribution, at first, we introduce a basic network framework to study pyramidal structures and wedges between ownership and control of companies. Then, we apply it to a dataset of
53.5 million of companies operating in 208 countries. Among others, we detect a strong concentra-
tion of corporate power, as less than 1% of parent companies collect more than 100 subsidiaries, but
they are responsible for more than 50% of global sales. Therefore, we show that the role of indirect
control, i.e., through middlemen subsidiaries, is relevant in 15% of domestic and 54% of foreign
subsidiaries. Among foreign companies, cases emerge of blurring nationality, when control paths
cross more than one national border, in the presence of multiple passports (19.1%), indirectly for-
eign (24.5%), and round-tripping subsidiaries (1.33%). Finally, we relate indirect control strategies
to country indicators of the institutional environment. We find that pyramidal structures arise less
likely in the presence of good financial and contractual institutions in the parent's country, as these
foster more transparent forms of corporate governance. Instead, parent companies choose indirect
control through countries of subsidiaries that have better financial institutions, possibly because it
is easier to coordinate decisions from remote. Finally, we find that offshore financial centers are
preferred jurisdictions for middlemen subsidiaries, probably due to a lower taxation and a lack of
financial disclosure.Armando Rungiarmando.rungi@imtlucca.itGreg MorrisonFabio Pammolli2017-08-04T11:22:51Z2017-08-04T11:22:51Zhttp://eprints.imtlucca.it/id/eprint/3755This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/37552017-08-04T11:22:51ZEntangling Credit and Funding Shocks in Interbank MarketsCredit and liquidity shocks represent main channels of financial contagion for interbank lending markets. On one hand, banks face potential losses whenever their counterparties are under distress and thus unable to fulfill their obligations. On the other hand, solvency constraints may force banks to recover lost fundings by selling their illiquid assets, resulting in effective losses in the presence of fire sales—that is, when funding shortcomings are widespread over the market. Because of the complex structure of the network of interbank exposures, these losses reverberate among banks and eventually get amplified, with potentially catastrophic consequences for the whole financial system. Inspired by the recently proposed Debt Rank, in this work we define a systemic risk metric that estimates the potential amplification of losses in interbank markets accounting for both credit and liquidity contagion channels: the Debt-Solvency Rank. We implement this framework on a dataset of 183 European banks that were publicly traded between 2004 and 2013, showing indeed that liquidity spillovers substantially increase systemic risk, and thus cannot be neglected in stress-test scenarios. We also provide additional evidence that the interbank market was extremely fragile up to the global financial crisis, becoming slightly more robust only afterwards.Giulio Ciminigiulio.cimini@imtlucca.itMatteo Serri2017-03-09T10:12:31Z2017-03-09T10:12:31Zhttp://eprints.imtlucca.it/id/eprint/3659This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/36592017-03-09T10:12:31ZThe Accounting Network: How Financial Institutions React to Systemic CrisisThe role of Network Theory in the study of the financial crisis has been widely spotted in the latest years. It has been shown how the network topology and the dynamics running on top of it can trigger the outbreak of large systemic crisis. Following this methodological perspective we introduce here the Accounting Network, i.e. the network we can extract through vector similarities techniques from companies’ financial statements. We build the Accounting Network on a large database of worldwide banks in the period 2001–2013, covering the onset of the global financial crisis of mid-2007. After a careful data cleaning, we apply a quality check in the construction of the network, introducing a parameter (the Quality Ratio) capable of trading off the size of the sample (coverage) and the representativeness of the financial statements (accuracy). We compute several basic network statistics and check, with the Louvain community detection algorithm, for emerging communities of banks. Remarkably enough sensible regional aggregations show up with the Japanese and the US clusters dominating the community structure, although the presence of a geographically mixed community points to a gradual convergence of banks into similar supranational practices. Finally, a Principal Component Analysis procedure reveals the main economic components that influence communities’ heterogeneity. Even using the most basic vector similarity hypotheses on the composition of the financial statements, the signature of the financial crisis clearly arises across the years around 2008. We finally discuss how the Accounting Networks can be improved to reflect the best practices in the financial statement analysis.Michelangelo Puligamichelangelo.puliga@imtlucca.itAndrea Floriandrea.flori@imtlucca.itGiuseppe PappalardoAlessandro Chessaalessandro.chessa@imtlucca.itFabio Pammolli2016-12-13T15:24:29Z2016-12-13T15:24:29Zhttp://eprints.imtlucca.it/id/eprint/3608This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/36082016-12-13T15:24:29ZPeer-Group Detection of Banks and Resilience to DistressThe paper looks at the importance of the true business model in shaping the risk profile of
financial institutions. We adopt a novel indirect clustering approach to enrich the classic bank
business model classification on a global data set including about 11,000 banks, both listed and
non-listed representing more than 180 countries over the period 2005-2014. A comprehensive
list of global distress events, which combines bankruptcies, liquidations, defaults, distressed
mergers, and public bailouts, is regressed against financial statement ratios (i.e. proxies for
CAMELS) and controlling for macro and sectoral effects using a rare-event logit model. Our
findings suggest that individual characteristics along with macro and sectoral factors contribute
differently, sometimes with opposite sign, to the likelihood of distress and to the volatility
of business models with the exception of liquidity whose contribution appears exogenous to
business model choice. By capturing the switching behaviour across groups, we find that
business model volatility exacerbates vulnerability and distress, especially if moving from
wholesale-oriented to deposit oriented groups.Andrea Floriandrea.flori@imtlucca.itSimone GiansanteFabio Pammollif.pammolli@imtlucca.it2016-11-21T12:16:45Z2016-11-21T12:16:45Zhttp://eprints.imtlucca.it/id/eprint/3598This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/35982016-11-21T12:16:45ZAssessing financial distress dependencies in OTC markets: a new approach using trade repositories dataIn this paper, we study the relationships among financial market sub-segments as a way to identify potential financial distress through increased co-movements among them. To study how sub-markets are mutually co-dependent, we combine granular data on over-the-counter derivatives by trade repositories and the joint probability of distress (JPoD) approach introduced by the International Monetary Fund. We define an indicator that combines several distress drivers and observe that results on co-dependencies are similar to those that would be expected: similarities between financial and contractual terms seem to be responsible for stronger co-movements among sub-markets. However, high values for JPoD even in correspondence of quite dissimilar sub-markets suggest the presence of other drivers that should be investigated in future research. To the best of our knowledge, this is the first empirical study on systemic risk assessment based on micro-founded trade repositories’ data on interest rate swaps.Michele Bonollomichele.bonollo@imtlucca.itIrene Crimaldiirene.crimaldi@imtlucca.itAndrea Floriandrea.flori@imtlucca.itLaura Gianfagnalaura.gianfagna@imtlucca.itFabio Pammollif.pammolli@imtlucca.it2016-01-11T09:11:26Z2016-02-26T15:56:01Zhttp://eprints.imtlucca.it/id/eprint/2978This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/29782016-01-11T09:11:26ZBasis Risk in Static versus Dynamic Longevity Risk HedgingThis paper provides a simple model for basis risk in a longevity framework, by separating common and idiosyncratic risk factors. Basis risk is captured by a single parameter, that measures the co-movement between the portfolio and the reference population. In this framework, the paper sets out the static, swap-based hedge for an annuity, and compares it with the dynamic, delta-based hedge, achieved using longevity bonds. We assume that the longevity intensity is distributed according to a CIR-type process and provide closed-form derivatives prices and hedges, also in the presence of an analogous CIR process for interest rate risk.Clemente De RosaElisa LucianoLuca Regisluca.regis@imtlucca.it2015-11-05T15:00:03Z2018-03-08T16:58:34Zhttp://eprints.imtlucca.it/id/eprint/2834This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/28342015-11-05T15:00:03ZSystemic Risk Analysis on Reconstructed Economic and Financial NetworksWe address a fundamental problem that is systematically encountered when modeling real-world complex systems of societal relevance: the limitedness of the information available. In the case of economic and financial networks, privacy issues severely limit the information that can be accessed and, as a consequence, the possibility of correctly estimating the resilience of these systems to events such as financial shocks, crises and cascade failures. Here we present an innovative method to reconstruct the structure of such partially-accessible systems, based on the knowledge of intrinsic node-specific properties and of the number of connections of only a limited subset of nodes. This information is used to calibrate an inference procedure based on fundamental concepts derived from statistical physics, which allows to generate ensembles of directed weighted networks intended to represent the real system—so that the real network properties can be estimated as their average values within the ensemble. We test the method both on synthetic and empirical networks, focusing on the properties that are commonly used to measure systemic risk. Indeed, the method shows a remarkable robustness with respect to the limitedness of the information available, thus representing a valuable tool for gaining insights on privacy-protected economic and financial systems.Giulio Ciminigiulio.cimini@imtlucca.itTiziano Squartinitiziano.squartini@imtlucca.itDiego Garlaschellidiego.garlaschelli@imtlucca.itAndrea Gabrielli2015-11-02T13:37:08Z2015-11-02T13:37:08Zhttp://eprints.imtlucca.it/id/eprint/2793This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/27932015-11-02T13:37:08ZThe Effects of Twitter Sentiment on Stock Price ReturnsSocial media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known “event study” from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the “event study” methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1–2), but the dependence is statistically significant for several days after the events.Gabriele RancoDarko AleksovskiGuido Caldarelliguido.caldarelli@imtlucca.itMiha GrčarIgor Mozetič2015-10-23T12:05:04Z2016-11-17T10:35:24Zhttp://eprints.imtlucca.it/id/eprint/2781This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/27812015-10-23T12:05:04ZAssessing financial distress dependencies in OTC markets:
a new approach by Trade Repositories dataAfter the recent financial crisis, it is undoubtedly recognized the importance of assessing
not only the risk of distress for a single \financial entity", but also the distress dependencies
between the different \entities", where by \entities" we mean in a broad sense any relevant
cluster of products, risk factors, counterparties. In this paper, we focus on the Interest Rate
Swap (IRS) segment as a significant fraction of the OTC market. We define a distress indicator
by combining some distress drivers, such as averaged volumes, liquidity, volatility and
bid-ask proxies. Hence, we analyse the distress dependencies among sub-markets identified
by the segmentation of the IRS market according to contractual and financial features. We
try to combine in an innovative way some new ingredients, namely the more granular data
on OTC derivatives available from the trade repositories along with the classical JPoD approach
introduced in the recent years by the IMF for studying the distress interdependence
structure among financial institutions. The proposed technique seems to be quite promising.
Indeed, the results are quite close to the practical intuition. At the best of our knowledge,
this work is the first empirical study based on trade repositories' data for assessing systemic
risk.Michele Bonollomichele.bonollo@imtlucca.itIrene Crimaldiirene.crimaldi@imtlucca.itAndrea Floriandrea.flori@imtlucca.itLaura Gianfagnalaura.gianfagna@imtlucca.itFabio Pammollif.pammolli@imtlucca.it2015-07-30T15:03:51Z2015-07-31T10:30:07Zhttp://eprints.imtlucca.it/id/eprint/2735This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/27352015-07-30T15:03:51ZOwnership, Taxes and DefaultThis paper determines ownership and leverage of two units facing a tax-
bankruptcy trade-o�. Connected units have higher leverage and lower tax burden,
because of internal support through both bailouts and corporate dividends. Owner-
ship adjusts to additional tax provisions. A hierarchical group with a wholly-owned
subsidiary results from Thin Capitalization rules. The presence of corporate divi-
dend taxes generates horizontal groups, or a Special Purpose Vehicle, or a private
equity fund. Combinations of tax provisions contain tax savings, debt and default
in connected units. No bailout provisions, such as the Volcker rule, succeed in
reducing leverage and default.Giovanna NicodanoLuca Regisluca.regis@imtlucca.it2015-07-08T09:45:55Z2015-07-08T09:45:55Zhttp://eprints.imtlucca.it/id/eprint/2726This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/27262015-07-08T09:45:55ZSingle and cross-generation natural hedging of longevity and financial riskThe paper provides natural hedging strategies among death benefits and annuities written on a single and on different generations. It obtains closed-form Delta and Gamma hedges, in the presence of both longevity and interest rate risk. We present an application to UK data on survivorship and bond dynamics. We first compare longevity and financial risk exposures: Deltas and Gammas for longevity risk are greater in absolute value than the corresponding sensitivities for interest rate risk. We then calculate the optimal hedges, both within and across generations. Our results apply to both asset and asset-liability management.Elisa LucianoLuca Regisluca.regis@imtlucca.itElena Vigna2015-06-25T12:47:44Z2015-06-25T12:47:44Zhttp://eprints.imtlucca.it/id/eprint/2717This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/27172015-06-25T12:47:44ZAutomotive and finance case studies in the conversation calculusWe describe the encoding of the Car Break scenario of the SENSORIA Automotive case study and of the Credit Request scenario of the SENSORIA Finance case study using the Conversation Calculus (CSCC). These scenarios consist of an orchestration of services and service clients which are typefully encoded here in a modular way. Namely the latter scenario consists of a workflow involving different actors: a client willing to submit a credit request, a bank employee, and its supervisor. We show how the workflow is well described in the type assigned to the processes implementing it. We first informally describe the CSCC calculus, and then show how the two scenarios can be encoded using the CSCC calculus and the corresponding typing.Luis CairesJoão Costa SecoHugo Torres Vieirahugo.torresvieira@imtlucca.it2015-05-19T10:14:45Z2015-05-19T10:14:45Zhttp://eprints.imtlucca.it/id/eprint/2684This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/26842015-05-19T10:14:45ZLeveraging the network: a stress-test framework based on DebtRankWe develop a novel stress-test framework to monitor systemic risk in financial systems. The modular structure of the framework allows to accommodate for a variety of shock scenarios, methods to estimate interbank exposures and mechanisms of distress propagation. The main features are as follows. First, the framework allows to estimate and disentangle not only first-round effects (i.e. shock on external assets) and second-round effects (i.e. distress induced in the interbank network), but also third-round effects induced by possible fire sales. Second, it allows to monitor at the same time the impact of shocks on individual or groups of financial institutions as well as their vulnerability to shocks on counterparties or certain asset classes. Third, it includes estimates for loss distributions, thus combining network effects with familiar risk measures such as VaR and CVaR. Fourth, in order to perform robustness analyses and cope with incomplete data, the framework features a module for the generation of sets of networks of interbank exposures that are coherent with the total lending and borrowing of each bank. As an illustration, we carry out a stress-test exercise on a dataset of listed European banks over the years 2008-2013. We find that second-round and third-round effects dominate first-round effects, therefore suggesting that most current stress-test frameworks might lead to a severe underestimation of systemic risk. Stefano BattistonMarco D'ErricoStefano GurciulloGuido Caldarelliguido.caldarelli@imtlucca.it2015-03-13T09:03:08Z2015-03-13T09:03:08Zhttp://eprints.imtlucca.it/id/eprint/2634This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/26342015-03-13T09:03:08ZL’importanza sistemica delle banche: da una prospettiva
globale a una locale?
(Systemic Importance of Financial Institutions: from a Global to a Local Perspective? A Network Theory Approach)Nonostante la vasta letteratura che si è occupata di rischio sistemico, non si è ancora giunti a definire misure e approcci metodologici standard volti a gestire questa tipologia di rischio. Questo lavoro illustra alcune questioni aperte e delinea possibili linee di ricerca future. In particolare, una eventuale declinazione su scala locale della nozione di rischio sistemico, di specifico interesse nel contesto italiano.
(English version:
After the systemic effects of bank defaults during the recent financial crisis, and despite a huge amount of literature on systemic risk, no standard methodologies have been set up until now. We aim to build a concise but comprehensive picture of the state of the art, illustrating the open issues and outlining pathways for future research. In particular, we propose the analysis of some examples of local systems that attract the attention of the financial sector.)Michele Bonollomichele.bonollo@imtlucca.itIrene Crimaldiirene.crimaldi@imtlucca.itAndrea Floriandrea.flori@imtlucca.it2015-01-29T08:42:51Z2017-04-03T12:04:07Zhttp://eprints.imtlucca.it/id/eprint/2548This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/25482015-01-29T08:42:51ZSystemic risk and banking regulation: some facts on the new regulatory frameworkThe recent financial crisis highlighted the relevant role of the systemic effects of banks’ defaults on the stability of the whole financial system. In this work we draw an organic picture of the current regulations, moving from the definitions of systemic risk to the issues concerning data availability. We show how a more detailed flow of data on traded deals might shed light on some systemic risk features
taken into account only partially in the past. In particular, we analyse how the new regulatory framework allows regulators to describe OTC derivatives markets according to more detailed partitions, thus depicting a more realistic picture of the system. Finally, we suggest to study submarkets illiquidity conditions to consider possible spill over effects which might lead to a worsening
for the entire system.Michele Bonollomichele.bonollo@imtlucca.itIrene Crimaldiirene.crimaldi@imtlucca.itAndrea Floriandrea.flori@imtlucca.itFabio Pammollif.pammolli@imtlucca.itMassimo Riccabonimassimo.riccaboni@imtlucca.it2014-12-16T10:32:30Z2016-04-06T08:06:17Zhttp://eprints.imtlucca.it/id/eprint/2395This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/23952014-12-16T10:32:30ZAssessing the solvency of insurance portfolios via a continuous-time cohort modelThis paper evaluates the solvency of a portfolio of assets and liabilities of an insurer subject to both longevity and financial risks. Liabilities are evaluated at fair-value and, as a consequence, interest-rate risk can affect both the assets and the liabilities. Longevity risk is described via a continuous-time cohort model. We evaluate the effects of natural hedging strategies on the risk profile of an insurance portfolio in run-off. Numerical simulations, calibrated to UK historical data, show that systematic longevity risk is of particular importance and needs to be hedged. Natural hedging can improve the solvency of the insurer, if interest-rate risk is appropriately managed. We stress that asset allocation choices should not be independent of the composition of the liability portfolio of the insurer.Petar JevtićLuca Regisluca.regis@imtlucca.it2014-11-18T08:34:05Z2014-11-18T08:34:05Zhttp://eprints.imtlucca.it/id/eprint/2372This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/23722014-11-18T08:34:05ZRisk-return appraisal of longevity swapsThe authors show that the transfer of longevity risk through derivatives, such as longevity swaps, usually decreases the overall risk of a pension fund, while also decreasing expected returns, thus resulting in efficient outcomes. In some cases, however, this may increase the overall risk. Risk is measured by Value-at-Risk (VaR), taking into account the impact of both longevity and interest-rate shocks on assets and liabilities. After calibrating a hypothetical fund to the U.K. longevity and bond market, the authors show that when inefficiencies arise, they may be avoided with a partial transfer of longevity risk.Luca Regisluca.regis@imtlucca.itElisa Luciano2014-07-22T14:24:57Z2014-07-22T14:24:57Zhttp://eprints.imtlucca.it/id/eprint/2261This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/22612014-07-22T14:24:57ZAssessing the solvency of insurance portfolios via a continuous time cohort modelThis paper evaluates the solvency of a portfolio of assets and liabilities of an insurer subject to both longevity and financial risks. Liabilities are evaluated at fair-value and, as a consequence, interest-rate risk can affect both the assets and the liabilities. Longevity risk is
described via a continuous-time cohort model. We evaluate the effects of natural hedging strategies on the risk profile of an insurance portfolio in run-off. Numerical simulations, calibrated to UK historical data, show that systematic longevity risk is of particular importance
and needs to be hedged. Natural hedging can improve the solvency of the insurer, if interest-rate risk is appropriately managed. We stress that asset allocation choices should not be independent of the composition of the liability portfolio of the insurer.Petar JevtićLuca Regisluca.regis@imtlucca.it2014-06-26T12:39:17Z2014-06-26T12:39:17Zhttp://eprints.imtlucca.it/id/eprint/2211This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/22112014-06-26T12:39:17ZAn economic and financial exploratoryThis paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs.Silvano CincottiDidler SornettePhilip TreleavenStefano BattistonGuido Caldarelliguido.caldarelli@imtlucca.itCars H. HommesAlan Kirman2014-06-16T12:06:17Z2014-06-16T12:06:17Zhttp://eprints.imtlucca.it/id/eprint/2202This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/22022014-06-16T12:06:17ZSystemic risk in financial networksFinancial inter-linkages play an important role in the emergence of financial instabilities and the formulation of systemic risk can greatly benefit from a network approach. In this paper, we focus on the role of linkages along the two dimensions of contagion and liquidity, and we discuss some insights that have recently emerged from network models. With respect to the issue of the determination of the optimal architecture of the financial system, models suggest that regulators have to look at the interplay of network topology, capital requirements, and market liquidity. With respect to the issue of the determination of systemically important financial institutions the findings indicate that both from the point of view of contagion and from the point of view of liquidity provision, there is more to systemic importance than just size. In particular for contagion, the position of institutions in the network matters and their impact can be computed through stress tests even when there are no defaults in the system.topology, capital requirements, and market liquidity. With respect to the issue of the determination of systemically important financial institutions the findings indicate that both from the point of view of contagion and from the point of view of liquidity provision, there is more to systemic importance than just size. In particular for contagion, the position of institutions in the network matters and their impact can be computed through stress tests even when there are no defaults in the system.Stefano BattistonGuido Caldarelliguido.caldarelli@imtlucca.it2014-06-16T11:16:52Z2014-07-07T10:28:55Zhttp://eprints.imtlucca.it/id/eprint/2200This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/22002014-06-16T11:16:52ZBootstrapping topological properties and systemic risk of complex networks using the fitness modelIn this paper we present a novel method to reconstruct global topological properties of a complex network starting from limited information. We assume to know for all the nodes a non-topological quantity that we interpret as fitness. In contrast, we assume to know the degree, i.e. the number of connections, only for a subset of the nodes in the network. We then use a fitness model, calibrated on the subset of nodes for which degrees are known, in order to generate ensembles of networks. Here, we focus on topological properties that are relevant for processes of contagion and distress propagation in networks, i.e. network density and k-core structure, and we study how well these properties can be estimated as a function of the size of the subset of nodes utilized for the calibration. Finally, we also study how well the resilience to distress propagation in the network can be estimated using our method. We perform a first test on ensembles of synthetic networks generated with the Exponential Random Graph model, which allows to apply common tools from statistical mechanics. We then perform a second test on empirical networks taken from economic and financial contexts. In both cases, we find that a subset as small as 10 % of nodes can be enough to estimate the properties of the network along with its resilience with an error of 5 %.Nicolò MusmeciStefano BattistonGuido Caldarelliguido.caldarelli@imtlucca.itMichelangelo Puligamichelangelo.puliga@imtlucca.itAndrea Gabrielli2014-06-11T12:52:21Z2016-03-18T10:41:24Zhttp://eprints.imtlucca.it/id/eprint/2199This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/21992014-06-11T12:52:21ZThe impact of financial restructuring after 2001 Turkey crisis on the risk determinants of Turkish commercial bank stocksThis paper examines the risk features of Turkish commercial banks and the determinants of their systematic and unsystematic risks by analyzing the effects of financial reforms after 2001 crisis. The sample period is divided into two sub-periods: before financial restructuring period (1994-2000) and post-financial restructuring period (2001-2010). The OLS framework is utilized to investigate the impact of financial restructuring on the risk determinants. For the majority of the stocks in the sample, the results point out that turnover and size are the most explanatory variables for systematic risk and unsystematic risk, respectively in two sub-periods. As for the comparison of the before and post-financial restructuring periods, the results indicate that there is not a significant change in risk factors, suggesting that investors risk preferences are same for the analyzed period.Cengiz ErolÜnal Sevenunal.seven@imtlucca.itBerna AydoğanSeda Tunc2013-12-17T15:29:35Z2014-01-28T15:24:51Zhttp://eprints.imtlucca.it/id/eprint/2075This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/20752013-12-17T15:29:35ZEfficient versus inefficient hedging strategies in the presence of financial and longevity (value at) riskThis paper provides a closed-form Value-at-Risk (VaR) for the net exposure of an annuity provider, taking into account both mortality and interest-rate risk, on both assets and liabilities. It builds a classical risk-return frontier and shows that hedging strategies–such as the transfer of longevity risk–may increase the overall risk while decreasing expected returns, thus resulting in inefficient outcomes. Once calibrated to the 2010 UK longevity and bond market, the model gives conditions under which hedging policies become inefficient.
Elisa LucianoLuca Regisluca.regis@imtlucca.it2013-09-02T11:23:34Z2014-09-04T09:11:19Zhttp://eprints.imtlucca.it/id/eprint/1657This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/16572013-09-02T11:23:34ZWhich Reforms Work and under What Institutional Environment? Evidence from a New Data Set on Structural ReformsAre structural reforms growth enhancing? Is the effectiveness of reforms constrained by a country's distance from the technology frontier or by its institutional environment? This paper takes a new and comprehensive look at these questions by employing a novel data set that includes several kinds of real (trade, agriculture, and networks) and financial (domestic finance, banking, securities, and capital account) reforms for an extensive list of developed and developing countries, going back to the early 1970s. First-pass evidence based on growth breaks analysis and on panel growth regressions suggests that on average, both real and financial sector reforms are positively associated with higher growth. However, on several occasions, botched reforms resulted in growth disasters. More important, the positive reform-growth relationship is shown to be highly heterogeneous and to be influenced by a country's constraints on the authority of the executive power and by its distance from the technology frontier. Finally, there is some evidence that crises, defined as severe growth downturns, are associated with subsequent reform upticks.Alessandro PratiMassimiliano Gaetano Onoratomassimiliano.onorato@imtlucca.itChris Papageorgiou2013-07-10T10:59:17Z2013-07-10T10:59:17Zhttp://eprints.imtlucca.it/id/eprint/1641This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/16412013-07-10T10:59:17ZStudy of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USAIn this study two approaches are applied for the prediction of the economic recession or expansion periods in USA. The first approach includes Logit and Probit models and
the second is an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell membership functions. The in-sample period 1950-2006 is examined
and the forecasting performance of the two approaches is evaluated during the out-of sample period 2007-2010. The estimation results show that the ANFIS model outperforms
the Logit and Probit model. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.Eleftherios Giovaniseleftherios.giovanis@imtlucca.it2013-07-10T09:46:59Z2013-07-10T09:46:59Zhttp://eprints.imtlucca.it/id/eprint/1639This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/16392013-07-10T09:46:59ZApplication of Adaptive Νeuro-Fuzzy Inference System in Interest Rates Effects on Stock ReturnsIn the current study we examine the effects of interest rate changes on common stock returns of Greek banking sector. We examine the Generalized Autoregressive Heteroskedasticity (GARCH) process and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The conclusions of our findings are that the changes of interest rates, based on GARCH model, are insignificant on common stock returns during the period we examine. On the other hand, with ANFIS we can get the rules and in each case we can have positive or negative effects depending on the conditions and the firing rules of inputs, which information is not possible to be retrieved with the traditional econometric modelling. Furthermore we examine the forecasting performance of both models and we conclude that ANFIS outperforms GARCH model in both in-sample and out-of-sample periods.Eleftherios Giovaniseleftherios.giovanis@imtlucca.it2013-07-08T14:07:40Z2013-07-08T14:07:40Zhttp://eprints.imtlucca.it/id/eprint/1632This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/16322013-07-08T14:07:40ZApplications of Neural Network Radial Basis Function in Economics and Financial Time SeriesIn this paper we present the Radial Basis Neural Network Function. We examine some simple numerical examples of time-series in economics and finance. The forecasting performance is significant superior, especially in financial time-series, to traditional econometric modeling indicating that artificial intelligence procedure are more appropriate. Some MATLAB routines are presented for further application research. Eleftherios Giovaniseleftherios.giovanis@imtlucca.it2012-08-10T08:02:12Z2012-08-10T08:02:12Zhttp://eprints.imtlucca.it/id/eprint/1332This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/13322012-08-10T08:02:12ZTomas Bjork, A geometric view of the term structure of interest rates, Cattedra Galileiana 2000 (Lecture notes written by Irene Crimaldi)This set of lecture notes is the outcome of a lecture series, given in April 2000 by Prof. Tomas Bjork while holding the "Cattedra Galileiana" at Scuola Normale Superiore in Pisa. The purpose of the lectures was to give an overview of some recent work concerning structural properties of the evolution of the forward rate curve in an arbitrage free bond market.Irene Crimaldiirene.crimaldi@imtlucca.it2012-05-30T09:01:07Z2014-11-19T11:13:11Zhttp://eprints.imtlucca.it/id/eprint/1280This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/12802012-05-30T09:01:07ZDynamic option hedging via stochastic model predictive control based on scenario simulation Derivative contracts require the replication of the product by means of a dynamic portfolio composed of simpler, more liquid securities. For a broad class of options encountered in financial engineering we propose a solution to the problem of finding a hedging portfolio using a discrete-time stochastic model predictive control and receding horizon optimization. By employing existing option pricing engines for estimating future option prices (possibly in an approximate way, to increase computation speed), in the absence of transaction costs the resulting stochastic optimization problem is easily solved at each trading date as a least-squares problem with as many variables as the number of traded assets and as many constraints as the number of predicted scenarios. As shown through numerical examples, the approach is particularly useful and numerically viable for exotic options where closed-form results are not available, as well as relatively long expiration dates where tree-based stochastic approaches are excessively complex. Alberto Bemporadalberto.bemporad@imtlucca.itLeonardo BellucciTommaso Gabbriellini2012-02-27T11:35:45Z2014-06-26T11:17:43Zhttp://eprints.imtlucca.it/id/eprint/1193This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11932012-02-27T11:35:45ZA numerical study on the evolution of portfolio rulesIn this paper we test computationally the performance of CAPM in an evolutionary setting. In particular we study the stability of distribution of wealth in a financial market where some traders invest as prescribed by CAPM and others behave according to different portfolio rules. Our study is motivated by recent analytical results that show that, whenever a logarithmic utility maximiser enters the market, CAPM traders vanish in the long run. Our analysis provides further insights and extends these results. We simulate a sequence of trades in a financial market and: first, we address the issue of how long is the long run in different parametric settings; second, we study the effect of heterogeneous savings behaviour on asymptotic wealth shares. We find that CAPM is particularly “unfit” for highly risky environments.Guido Caldarelliguido.caldarelli@imtlucca.itMarina PiccioniEmanuela Sciubba2012-02-20T13:43:10Z2013-11-20T14:30:41Zhttp://eprints.imtlucca.it/id/eprint/1134This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11342012-02-20T13:43:10ZTopology of correlation-based minimal spanning trees in real and model marketsWe compare the topological properties of the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the widespread one-factor model.Giovanni BonannoGuido Caldarelliguido.caldarelli@imtlucca.itFabrizio LilloRosario Nunzio Mantegna2012-02-15T15:33:23Z2012-02-15T15:33:23Zhttp://eprints.imtlucca.it/id/eprint/1124This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11242012-02-15T15:33:23ZNetworks of equities in financial marketsWe review the recent approach of correlation based networks of financial equities. We investigate portfolio of stocks at different time horizons, financial indices and volatility time series and we show that meaningful economic information can be extracted from noise dressed correlation matrices. We show that the method can be used to falsify widespread market models by directly comparing the topological properties of networks of real and artificial markets.Giovanni BonannoGuido Caldarelliguido.caldarelli@imtlucca.itFabrizio LilloSalvatore MiccichèNicolas VandewalleRosario Nunzio Mantegna2012-02-14T13:52:35Z2018-03-08T17:08:11Zhttp://eprints.imtlucca.it/id/eprint/1118This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11182012-02-14T13:52:35ZEmergence of complexity in financial networks We present here a brief summary of the various possible applications of network theory in the field of finance. Since we want to characterize different systems by means of simple and universal features, graph theory could represent a rather powerful methodology. In the following we report our activity in three different subfields, namely the board and director networks, the networks formed by prices correlations and the stock ownership networks. In most of the cases these three kind of networks display scale-free properties making them interesting in their own. Nevertheless, we want to stress here that the main utility of this methodology is to provide new measures of the real data sets in order to validate the different models.Guido Caldarelliguido.caldarelli@imtlucca.itStefano BattistonDiego Garlaschellidiego.garlaschelli@imtlucca.itMichele Catanzaro2012-02-14T13:25:27Z2012-02-14T13:25:27Zhttp://eprints.imtlucca.it/id/eprint/1117This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11172012-02-14T13:25:27ZThe corporate boards networksIn this work we apply network theory to detect in a quantitative fashion some of the characters of the system composed by companies and their boards of directors. Modelling this as a bipartite graph, we can derive two networks (one for the companies and one for the directors) and apply to them the standard graph analysis instruments. The emerging picture shows an environment where the exchange of information and mutual influences, conveyed by interlocks between boards, is predominant. Such a result should be taken into account when modelling this system.Guido Caldarelliguido.caldarelli@imtlucca.itMichele Catanzaro2012-02-13T14:54:52Z2018-03-08T17:07:48Zhttp://eprints.imtlucca.it/id/eprint/1115This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11152012-02-13T14:54:52ZThe scale-free topology of market investmentsWe propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree (kin) and the sum of incoming link weights (v) of an investor correspond to the number of assets held (portfolio diversification) and to the invested wealth (portfolio volume), respectively. An empirical analysis of three different real markets reveals that the distributions of both kin and v display power-law tails with exponents γ and α. Moreover, we find that kinscales as a power-law function of v with an exponent β. Remarkably, despite the values of α, β and γ differ across the three markets, they are always governed by the scaling relation β=(1-α)/(1-γ). We show that these empirical findings can be reproduced by a recent model relating the emergence of scale-free networks to an underlying Paretian distribution of ‘hidden’ vertex properties.Diego Garlaschellidiego.garlaschelli@imtlucca.itStefano BattistonMaurizio CastriVito D. P. ServedioGuido Caldarelliguido.caldarelli@imtlucca.it2012-02-03T14:52:07Z2018-03-08T17:07:59Zhttp://eprints.imtlucca.it/id/eprint/1110This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11102012-02-03T14:52:07ZThe topology of shareholding networksWe study the statistical properties of the network of shareholding relationships in the Italian stock market (MIB) and in two US stock markets (NYSE and NASDAQ). The networks are found to be scale free a feature which doesn't seem to be in accord with classical theories of portfolio optimization. Several statistical properties differ across markets and allow for a classification. We introduce two quantities, HI and SI, analogous to in-degree and out-degree for weighted graphs. The distribution of HI and SI allow us to characterize from a statistical perspective the individual ownership concentration of stocks and the individual power of holders. They also suggest two different global pictures of the structure of the networks: the MIB seems characterized by medium size holders controlling separate subsets of stocks, while the US markets seem characterized by very large holders sharing control over subsets of stocks.Stefano BattistonDiego Garlaschellidiego.garlaschelli@imtlucca.itGuido Caldarelliguido.caldarelli@imtlucca.it2012-02-01T16:12:55Z2014-12-18T15:56:24Zhttp://eprints.imtlucca.it/id/eprint/1107This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11072012-02-01T16:12:55ZFitness model for the Italian interbank money marketWe use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto’s law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.Giulia De MasiGiulia IoriGuido Caldarelliguido.caldarelli@imtlucca.it2012-02-01T15:59:45Z2013-11-21T09:19:40Zhttp://eprints.imtlucca.it/id/eprint/1105This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11052012-02-01T15:59:45ZTrading strategies in the Italian interbank marketUsing a data set which includes all transactions among banks in the Italian money market, we study their trading strategies and the dependence among them. We use the Fourier method to compute the variance–covariance matrix of trading strategies. Our results indicate that well defined patterns arise. Two main communities of banks, which can be coarsely identified as small and large banks, emerge.Giulia IoriRenato RenòGiulia De MasiGuido Caldarelliguido.caldarelli@imtlucca.it2012-02-01T13:51:08Z2012-02-01T13:51:48Zhttp://eprints.imtlucca.it/id/eprint/1100This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/11002012-02-01T13:51:08ZThe Italian interbank network: statistical properties and a simple modelWe use the theory of complex networks in order to quantitatively characterize the structure of reciprocal expositions of Italian banks in the interbank money market market. We observe two main different strategies of banks: small banks tend to be the lender of the system, while large banks are borrowers. We propose a model to reproduce the main statistical features of this market. Moreover the network analysis allows us to investigate properties of robustness of this system.Giulia De MasiGiulia IoriGuido Caldarelliguido.caldarelli@imtlucca.it2012-02-01T12:00:55Z2016-04-06T08:58:18Zhttp://eprints.imtlucca.it/id/eprint/1098This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10982012-02-01T12:00:55ZA network analysis of the Italian overnight money marketThe objective of this paper is to analyse the network topology of the Italian segment of the European overnight money market through methods of statistical mechanics applied to complex networks. We investigate differences in the activities of banks of different sizes and the evolution of their connectivity structure over the maintenance period. The main purpose of the analysis is to establish the potential implications of the current institutional arrangements on the stability of the banking system and to assess the efficiency of the interbank market in terms of absence of speculative and preferential trading relationships.Giulia IoriGiulia De MasiOvidiu Vasile PrecupGiampaolo GabbiGuido Caldarelliguido.caldarelli@imtlucca.it2012-01-20T10:45:29Z2012-01-25T13:10:14Zhttp://eprints.imtlucca.it/id/eprint/1076This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10762012-01-20T10:45:29Z(edited by) Large scale structure and dynamics of complex networks: from information technology to finance and natural scienceThis book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.Guido Caldarelliguido.caldarelli@imtlucca.itAlessandro Vespignani2012-01-16T09:44:29Z2013-11-21T11:39:24Zhttp://eprints.imtlucca.it/id/eprint/266This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2662012-01-16T09:44:29ZBankruptcy risk model and empirical testsWe analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor—the debt-to-asset ratio R—in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market crashes, implying that firms go bankrupt with larger values of R. Based on the Zipf analysis, we employ Bayes’s theorem and relate the conditional probability that a bankrupt firm has a ratio R with the conditional probability of bankruptcy for a firm with a given R value. For 2,737 bankrupt firms, we demonstrate size dependence in assets change during the bankruptcy proceedings. Prepetition firm assets and petition firm assets follow Zipf distributions but with different exponents, meaning that firms with smaller assets adjust their assets more than firms with larger assets during the bankruptcy process. We compare bankrupt firms with nonbankrupt firms by analyzing the assets and liabilities of two large subsets of the US economy: 2,545 Nasdaq members and 1,680 New York Stock Exchange (NYSE) members. We find that both assets and liabilities follow a Pareto distribution. The finding is not a trivial consequence of the Zipf scaling relationship of firm size quantified by employees—although the market capitalization of Nasdaq stocks follows a Pareto distribution, the same distribution does not describe NYSE stocks. We propose a coupled Simon model that simultaneously evolves both assets and debt with the possibility of bankruptcy, and we also consider the possibility of firm mergers. Boris PodobnikDavor HorvaticAlexander M. Petersenalexander.petersen@imtlucca.itBranko UroševićH. Eugene Stanley2011-09-19T10:53:29Z2011-10-04T09:52:51Zhttp://eprints.imtlucca.it/id/eprint/892This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/8922011-09-19T10:53:29ZWarfare, Taxation, and Political Change: Evidence from the Italian RisorgimentoWe examine the relationships between warfare, taxation, and political change in the context of the political unification of the Italian peninsula. Using a comprehensive new database, we argue that external and internal threat environments had significant implications for the demand for military strength, which in turn had important ramifications for fiscal policy and the likelihood of constitutional reform and related improvements in the provision of non-military public services. Our analytic narrative complements recent theoretical and econometric works about state capacity. By emphasizing public finances, we also uncover novel insights about the forces underlying state formation in Italy.Mark Dinceccom.dincecco@imtlucca.itGiovanni Federicogiovanni.federico@eui.euAndrea Vindigniandrea.vindigni@imtlucca.it2011-08-09T09:09:41Z2011-08-12T15:18:50Zhttp://eprints.imtlucca.it/id/eprint/778This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/7782011-08-09T09:09:41ZIl concetto di mercato efficiente nella teoria economicaDavide Ticchidavide.ticchi@imtlucca.itGiuseppe Travaglini2011-08-09T07:54:49Z2011-08-12T15:18:50Zhttp://eprints.imtlucca.it/id/eprint/774This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/7742011-08-09T07:54:49ZRisk-aversion and the investment-uncertainty relationship: a commentThis paper shows that the solution of Nakamura's Journal of Economic Behavior and Organization 38 (1999) 357 model is incorrect. We propose an alternative framework that allows us to obtain closed form results on the investment-uncertainty relationship.Enrico SaltariDavide Ticchidavide.ticchi@imtlucca.it2011-08-09T07:45:00Z2011-08-12T15:18:50Zhttp://eprints.imtlucca.it/id/eprint/773This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/7732011-08-09T07:45:00ZRisk aversion, intertemporal substitution, and the aggregate investment-uncertainty relationshipWe analyze the role of risk aversion and intertemporal substitution in a simple dynamic general equilibrium model of investment and savings. Our main finding is that risk aversion cannot by itself explain a negative relationship between aggregate investment and aggregate uncertainty, as the effect of increased uncertainty on investment also depends on the intertemporal elasticity of substitution. In particular, the relationship between aggregate investment and aggregate uncertainty is positive even if agents are very risk averse, as long as the elasticity of intertemporal substitution is low. A negative investment-uncertainty relationship requires that the relative risk aversion and the elasticity of intertemporal substitution are both relatively high or both relatively low. We also show that the implications of our model are consistent with the available empirical evidence.Enrico SaltariDavide Ticchidavide.ticchi@imtlucca.it2011-07-29T11:00:09Z2012-07-09T09:42:48Zhttp://eprints.imtlucca.it/id/eprint/745This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/7452011-07-29T11:00:09ZA stochastic model predictive control approach to dynamic option hedging with transaction costsThis paper proposes a stochastic model predictive control (SMPC) approach to hedging derivative contracts (such as plain vanilla and exotic options) in the presence of transaction costs. The methodology is based on the minimization of a stochastic measures of the hedging error predicted for the next trading date. Three different measures are proposed to determine the optimal composition of the replicating portfolio. The first measure is a combination of variance and expected value of the hedging error, leading to a quadratic program (QP) to solve at each trading date; the second measure is the conditional value at risk (CVaR), a common index used in finance quantifying the average loss over a subset of worst-case realizations, leading to a linear programming (LP) formulation; the third approach is of min-max type and attempts at minimizing the largest possible hedging error, also leading to a (smaller scale) linear program. The hedging performance obtained by the three different measures is tested and compared in simulation on a European call and a barrier option.Alberto Bemporadalberto.bemporad@imtlucca.itLaura PugliaTommaso Gabbriellini2011-07-04T09:39:00Z2013-10-10T08:36:14Zhttp://eprints.imtlucca.it/id/eprint/695This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/6952011-07-04T09:39:00ZBankruptcy risk model and empirical testsWe analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor—the debt-to-asset ratio R—in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market crashes, implying that firms go bankrupt with larger values of R. Based on the Zipf analysis, we employ Bayes’s theorem and relate the conditional probability that a bankrupt firm has a ratio R with the conditional probability of bankruptcy for a firm with a given R value. For 2,737 bankrupt firms, we demonstrate size dependence in assets change during the bankruptcy proceedings. Prepetition firm assets and petition firm assets follow Zipf distributions but with different exponents, meaning that firms with smaller assets adjust their assets more than firms with larger assets during the bankruptcy process. We compare bankrupt firms with nonbankrupt firms by analyzing the assets and liabilities of two large subsets of the US economy: 2,545 Nasdaq members and 1,680 New York Stock Exchange (NYSE) members. We find that both assets and liabilities follow a Pareto distribution. The finding is not a trivial consequence of the Zipf scaling relationship of firm size quantified by employees—although the market capitalization of Nasdaq stocks follows a Pareto distribution, the same distribution does not describe NYSE stocks. We propose a coupled Simon model that simultaneously evolves both assets and debt with the possibility of bankruptcy, and we also consider the possibility of firm mergers. Boris PodobnikDavor HorvaticAlexander M. Petersenalexander.petersen@imtlucca.itBranko UroševićH. Eugene Stanley2011-07-04T09:21:46Z2016-04-06T08:02:07Zhttp://eprints.imtlucca.it/id/eprint/263This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2632011-07-04T09:21:46ZQuantitative relations between risk, return and firm sizeWe analyze —for a large set of stocks comprising four financial indices— the annual logarithmic growth rate R and the firm size, quantified by the market capitalization MC. For the Nasdaq Composite and the New York Stock Exchange Composite we find that the probability density functions of growth rates are Laplace ones in the broad central region, where the standard deviation σ(R), as a measure of risk, decreases with the MC as a power law σ(R)~(MC)- β. For both the Nasdaq Composite and the S&P 500, we find that the average growth rate langRrang decreases faster than σ(R) with MC, implying that the return-to-risk ratio langRrang/σ(R) also decreases with MC. For the S&P 500, langRrang and langRrang/σ(R) also follow power laws. For a 20-year time horizon, for the Nasdaq Composite we find that σ(R) vs. MC exhibits a functional form called a volatility smile, while for the NYSE Composite, we find power law stability between σ(r) and MC.Boris PodobnikDavor HorvaticAlexander M. Petersenalexander.petersen@imtlucca.itH. Eugene Stanley2011-07-04T09:21:40Z2016-04-06T08:01:12Zhttp://eprints.imtlucca.it/id/eprint/264This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2642011-07-04T09:21:40ZCommon scaling behavior in finance and macroeconomicsIn order to test whether scaling exists in finance at the world level, we test whether the average growth rates and volatility of market capitalization (MC) depend on the level of MC. We analyze the MC for 54 worldwide stock indices and 48 worldwide bond indices. We find that (i) the average growth rate r of the MC and (ii) the standard deviation (r) of growth rates r decrease both with MC as power laws, with exponents w = 0.28 ± 0.09 and w = 0.12 ± 0.04. We define a stochastic process in order to model the scaling results we find for worldwide stock and bond indices. We establish a power-law relationship between the MC of a country’s financial market and the gross domestic product (GDP) of the same country. Boris PodobnikDavor HorvaticAlexander M. Petersenalexander.petersen@imtlucca.itM. NjavroH. Eugene Stanley2011-07-04T09:21:34Z2013-11-21T11:40:02Zhttp://eprints.imtlucca.it/id/eprint/265This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2652011-07-04T09:21:34ZCross-correlations between volume change and price changeIn finance, one usually deals not with prices but with growth rates R, defined as the difference in logarithm between two consecutive prices. Here we consider not the trading volume, but rather the volume growth rate R̃, the difference in logarithm between two consecutive values of trading volume. To this end, we use several methods to analyze the properties of volume changes |R̃|, and their relationship to price changes |R|. We analyze 14,981 daily recordings of the Standard and Poor's (S & P) 500 Index over the 59-year period 1950–2009, and find power-law cross-correlations between |R| and |R̃| by using detrended cross-correlation analysis (DCCA). We introduce a joint stochastic process that models these cross-correlations. Motivated by the relationship between |R| and |R̃|, we estimate the tail exponent α̃ of the probability density function P(|R̃|) ∼ |R̃|−1−α̃ for both the S & P 500 Index as well as the collection of 1819 constituents of the New York Stock Exchange Composite Index on 17 July 2009. As a new method to estimate α̃, we calculate the time intervals τq between events where R̃ > q. We demonstrate that τ̃q, the average of τq, obeys τ̃q ∼ qα̃. We find α̃ ≈ 3. Furthermore, by aggregating all τq values of 28 global financial indices, we also observe an approximate inverse cubic law. Boris PodobnikDavor HorvaticAlexander M. Petersenalexander.petersen@imtlucca.itH. Eugene Stanley2011-07-04T09:21:07Z2014-12-18T15:24:33Zhttp://eprints.imtlucca.it/id/eprint/270This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2702011-07-04T09:21:07ZQuantitative law describing market dynamics before and after interest-rate changeWe study the behavior of U.S. markets both before and after U.S. Federal Open Market Commission meetings and show that the announcement of a U.S. Federal Reserve rate change causes a financial shock, where the dynamics after the announcement is described by an analog of the Omori earthquake law. We quantify the rate n(t) of aftershocks following an interest-rate change at time T and find power-law decay which scales as n(t−T)∼(t−T)−Ω, with Ω positive. Surprisingly, we find that the same law describes the rate n′(|t−T|) of “preshocks” before the interest-rate change at time T. This study quantitatively relates the size of the market response to the news which caused the shock and uncovers the presence of quantifiable preshocks. We demonstrate that the news associated with interest-rate change is responsible for causing both the anticipation before the announcement and the surprise after the announcement. We estimate the magnitude of financial news using the relative difference between the U.S. Treasury Bill and the Federal Funds effective rate. Our results are consistent with the “sign effect,” in which “bad news” has a larger impact than “good news.” Furthermore, we observe significant volatility aftershocks, confirming a “market under-reaction” that lasts at least one trading day.Alexander M. Petersenalexander.petersen@imtlucca.itFengzhong WangShlomo HavlinH. Eugene Stanley2011-07-04T09:19:17Z2014-12-18T15:21:18Zhttp://eprints.imtlucca.it/id/eprint/422This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/4222011-07-04T09:19:17ZMarket dynamics immediately before and after financial shocks: Quantifying the Omori, productivity, and Bath lawsWe study the cascading dynamics immediately before and immediately after 219 market shocks. We define the time of a market shock Tc to be the time for which the market volatility V(Tc) has a peak that exceeds a predetermined threshold. The cascade of high volatility “aftershocks” triggered by the “main shock” is quantitatively similar to earthquakes and solar flares, which have been described by three empirical laws—the Omori law, the productivity law, and the Bath law. We analyze the most traded 531 stocks in U.S. markets during the 2 yr period of 2001–2002 at the 1 min time resolution. We find quantitative relations between the main shock magnitude M≡log10 V(Tc) and the parameters quantifying the decay of volatility aftershocks as well as the volatility preshocks. We also find that stocks with larger trading activity react more strongly and more quickly to market shocks than stocks with smaller trading activity. Our findings characterize the typical volatility response conditional on M, both at the market and the individual stock scale. We argue that there is potential utility in these three statistical quantitative relations with applications in option pricing and volatility trading.Alexander M. Petersenalexander.petersen@imtlucca.itFengzhong WangShlomo HavlinH. Eugene Stanley2011-06-30T14:26:16Z2013-11-21T13:03:15Zhttp://eprints.imtlucca.it/id/eprint/646This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/6462011-06-30T14:26:16ZA generalized preferential attachment model for business firms growth rates: II. Mathematical treatmentWe present a preferential attachment growth model to obtain the distribution P(K) of number of units K in the classes which may represent business firms or other socio-economic entities. We found that P(K) is described in its central part by a power law with an exponent ϕ = 2+b/(1-b) which depends on the probability of entry of new classes, b. In a particular problem of city population this distribution is equivalent to the well known Zipf law. In the absence of the new classes entry, the distribution P(K) is exponential. Using analytical form of P(K) and assuming proportional growth for units, we derive P(g), the distribution of business firm growth rates. The model predicts that P(g) has a Laplacian cusp in the central part and asymptotic power-law tails with an exponent ζ = 3. We test the analytical expressions derived using heuristic arguments by simulations. The model might also explain the size-variance relationship of the firm growth rates. Fabio Pammollif.pammolli@imtlucca.itSergey V. BuldyrevMassimo Riccabonimassimo.riccaboni@imtlucca.itKazuko YamasakiDongfeng FuKaushik MatiaH. Eugene Stanley2011-06-30T14:26:09Z2013-11-21T13:05:56Zhttp://eprints.imtlucca.it/id/eprint/647This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/6472011-06-30T14:26:09ZA generalized preferential attachment model for business firms growth rates: I. Empirical evidenceWe introduce a model of proportional growth to explain the distribution P(g) of business firm growth rates. The model predicts that P(g) is Laplace in the central part and depicts an asymptotic power-law behavior in the tails with an exponent ζ = 3. Because of data limitations, previous studies in this field have been focusing exclusively on the Laplace shape of the body of the distribution. We test the model at different levels of aggregation in the economy, from products, to firms, to countries, and we find that the predictions are in good agreement with empirical evidence on both growth distributions and size-variance relationships. Fabio Pammollif.pammolli@imtlucca.itDongfeng FuSergey V. BuldyrevMassimo Riccabonimassimo.riccaboni@imtlucca.itKaushik MatiaKazuko YamasakiH. Eugene Stanley