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Article ; Online: Wasserstein barycenter regression for estimating the joint dynamics of renewable and fossil fuel energy indices.

De Giuli, Maria Elena / Spelta, Alessandro

2023 Volume 20, Issue 1, Page(s) 1

Abstract: In order to characterize non-linear system dynamics and to generate term structures of joint distributions, we propose a flexible and multidimensional approach, which exploits Wasserstein barycentric coordinates for histograms. We apply this methodology ... ...

Abstract	In order to characterize non-linear system dynamics and to generate term structures of joint distributions, we propose a flexible and multidimensional approach, which exploits Wasserstein barycentric coordinates for histograms. We apply this methodology to study the relationships between the performance in the European market of the renewable energy sector and that of the fossil fuel energy one. Our methodology allows us to estimate the term structure of conditional joint distributions. This optimal barycentric interpolation can be interpreted as a posterior version of the joint distribution with respect to the prior contained in the past histograms history. Once the underlying dynamics mechanism among the set of variables are obtained as optimal Wasserstein barycentric coordinates, the learned dynamic rules can be used to generate term structures of joint distributions.
Language	English
Publishing date	2023-02-04
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2107564-5
ISSN	1619-6988 ; 1619-697X
ISSN (online)	1619-6988
ISSN	1619-697X
DOI	10.1007/s10287-023-00436-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Multi-country clustering-based forecasting of healthy life expectancy.

Levantesi, Susanna / Nigri, Andrea / Piscopo, Gabriella / Spelta, Alessandro

Quality & quantity

2023 , Page(s) 1–27

Abstract: Healthy life expectancy (HLE) is an indicator that measures the number of years individuals at a given age are expected to live free of disease or disability. HLE forecasting is essential for planning the provision of health care to elderly populations ... ...

Abstract	Healthy life expectancy (HLE) is an indicator that measures the number of years individuals at a given age are expected to live free of disease or disability. HLE forecasting is essential for planning the provision of health care to elderly populations and appropriately pricing Long Term Care insurance products. In this paper, we propose a methodology that simultaneously forecasts HLE for groups of countries and allows for investigating similarities in their HLE patterns. We firstly apply a functional data clustering to the multivariate time series of HLE at birth of different countries for the years 1990-2019 provided by the Global Burden of Disease Study. Three clusters are identified for both genders. Then, we carry out the HLE simultaneous forecasting of the populations within each cluster by a multivariate random walk with drift. Numerical results and the statistical significance of the parameters of the identified multivariate processes are shown. Demographic evidences on the different evolution of HLE between countries are commented.
Language	English
Publishing date	2023-01-14
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2003280-8
ISSN	1573-7845 ; 0033-5177
ISSN (online)	1573-7845
ISSN	0033-5177
DOI	10.1007/s11135-022-01611-6
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Article ; Online: Mobility-based real-time economic monitoring amid the COVID-19 pandemic.

Spelta, Alessandro / Pagnottoni, Paolo

Scientific reports

2021 Volume 11, Issue 1, Page(s) 13069

Abstract: Mobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the real economy. ...

Abstract	Mobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the real economy. In this paper we propose a real-time monitoring framework for tracking the economic consequences of various forms of mobility reductions involving European countries. We adopt a granular representation of mobility patterns during both the first and second waves of SARS-COV-2 in Italy, Germany, France and Spain to provide an analytical characterization of the rate of losses of industrial production by means of a nowcasting methodology. Our approach exploits the information encoded in massive datasets of human mobility provided by Facebook and Google, which are published at higher frequencies than the target economic variables, in order to obtain an early estimate before the official data becomes available. Our results show, in first place, the ability of mobility-related policies to induce a contraction of mobility patterns across jurisdictions. Besides this contraction, we observe a substitution effect which increases mobility within jurisdictions. Secondly, we show how industrial production strictly follows the dynamics of population commuting patterns and of human mobility trends, which thus provide information on the day-by-day variations in countries' economic activities. Our work, besides shedding light on how policy interventions targeted to induce a mobility contraction impact the real economy, constitutes a practical toolbox for helping governments to design appropriate and balanced policy actions aimed at containing the SARS-COV-2 spread, while mitigating the detrimental effect on the economy. Our study reveals how complex mobility patterns can have unequal consequences to economic losses across countries and call for a more tailored implementation of restrictions to balance the containment of contagion with the need to sustain economic activities.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/pathology ; COVID-19/virology ; Economic Status ; Europe/epidemiology ; Humans ; Pandemics ; Quarantine ; SARS-CoV-2/isolation & purification ; Social Media ; Travel
Language	English
Publishing date	2021-06-22
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-92134-x
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Article ; Online: Mobility-based real-time economic monitoring amid the COVID-19 pandemic

Alessandro Spelta / Paolo Pagnottoni

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 15

Abstract: Abstract Mobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the ... ...

Abstract	Abstract Mobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the real economy. In this paper we propose a real-time monitoring framework for tracking the economic consequences of various forms of mobility reductions involving European countries. We adopt a granular representation of mobility patterns during both the first and second waves of SARS-COV-2 in Italy, Germany, France and Spain to provide an analytical characterization of the rate of losses of industrial production by means of a nowcasting methodology. Our approach exploits the information encoded in massive datasets of human mobility provided by Facebook and Google, which are published at higher frequencies than the target economic variables, in order to obtain an early estimate before the official data becomes available. Our results show, in first place, the ability of mobility-related policies to induce a contraction of mobility patterns across jurisdictions. Besides this contraction, we observe a substitution effect which increases mobility within jurisdictions. Secondly, we show how industrial production strictly follows the dynamics of population commuting patterns and of human mobility trends, which thus provide information on the day-by-day variations in countries’ economic activities. Our work, besides shedding light on how policy interventions targeted to induce a mobility contraction impact the real economy, constitutes a practical toolbox for helping governments to design appropriate and balanced policy actions aimed at containing the SARS-COV-2 spread, while mitigating the detrimental effect on the economy. Our study reveals how complex mobility patterns can have unequal consequences to economic losses across countries and call for a more tailored implementation of restrictions to balance the containment of contagion with the need to sustain economic activities.
Keywords	Medicine ; R ; Science ; Q
Subject code	337
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: The impact of the SARS-CoV-2 pandemic on financial markets: a seismologic approach.

Spelta, Alessandro / Pecora, Nicolò / Flori, Andrea / Giudici, Paolo

Annals of operations research

2021 , Page(s) 1–26

Abstract: This work investigates financial volatility cascades generated by SARS-CoV-2 related news using concepts developed in the field of seismology. We analyze the impact of socio-economic and political announcements, as well as of financial stimulus ... ...

Abstract	This work investigates financial volatility cascades generated by SARS-CoV-2 related news using concepts developed in the field of seismology. We analyze the impact of socio-economic and political announcements, as well as of financial stimulus disclosures, on the reference stock markets of the United States, United Kingdom, Spain, France, Germany and Italy. We quantify market efficiency in processing SARS-CoV-2 related news by means of the observed Omori power-law exponents and we relate these empirical regularities to investors' behavior through the lens of a stylized Agent-Based financial market model. The analysis reveals that financial markets may underreact to the announcements by taking a finite time to re-adjust prices, thus moving against the efficient market hypothesis. We observe that this empirical regularity can be related to the speculative behavior of market participants, whose willingness to switch toward better performing investment strategies, as well as their degree of reactivity to price trend or mispricing, can induce long-lasting volatility cascades.
Language	English
Publishing date	2021-05-14
Publishing country	United States
Document type	Journal Article
ISSN	0254-5330
ISSN	0254-5330
DOI	10.1007/s10479-021-04115-y
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Book ; Online: Stock prices prediction via tensor decomposition and links forecast

Spelta, Alessandro

(Working paper / Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore ; n. 41 (May 2016))

2016

Abstract: Many complex systems display fluctuations between alternative states in correspondence to tipping points. These critical shifts are usually associated with generic empirical phenomena such as strengthening correlations between entities composing the ... ...

Author's details	Alessandro Spelta
Series title	Working paper / Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore ; n. 41 (May 2016)
Abstract	Many complex systems display fluctuations between alternative states in correspondence to tipping points. These critical shifts are usually associated with generic empirical phenomena such as strengthening correlations between entities composing the system. In finance, for instance, market crashes are the consequence of herding behaviors that make the units of the system strongly correlated, lowering their distances. Consequently, determining future distances between stocks can be a valuable starting point for predicting market down-turns. This is the scope of the work. It introduces a multi-way procedure for forecasting stock prices by decomposing a distance tensor. This multidimensional method avoids aggregation processes that could lead to the loss of crucial features of the system. The technique is applied to a basket of stocks composing the S&P500 composite index and to the index itself so as to demonstrate its ability to predict the large market shifts that arise in times of turbulence, such as the ongoing financial crisis.
Keywords	Stock prices ; Correlations ; Tensor Decomposition ; Forecast
Language	English
Size	1 Online-Ressource (circa 33 Seiten), Illustrationen
Publisher	Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore
Publishing place	Milano, Italy
Document type	Book ; Online
Database	ECONomics Information System

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Book ; Online: A unified view of systemic risk

Spelta, Alessandro

detecting SIFIs and forecasting the financial cycle via EWSs

(Working paper / Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore ; n. 36 (January 2016))

2016

Abstract: Following the definition of systemic risk by the Financial Stability Board, the International Monetary Fund and the Bank for International Settlements, this paper proposes a method able to simultaneously address the two dimensions in which this risk ... ...

Author's details	Alessandro Spelta
Series title	Working paper / Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore ; n. 36 (January 2016)
Abstract	Following the definition of systemic risk by the Financial Stability Board, the International Monetary Fund and the Bank for International Settlements, this paper proposes a method able to simultaneously address the two dimensions in which this risk materializes: namely the cross-sectional and the time dimension. The method is based on the W-TOPHITS algorithm, that exploits the connectivity information of an evolving network, and decomposes its tensor representation as the outer product of three vectors: borrowing, lending and time scores. These vectors can be interpreted as indices of the systemic importance of borrowing and lending associated with each financial institution and of the systemic importance associated with each period, coherently with the realization of the whole network in that period. The time score, being able to simultaneously consider the temporal distribution of the whole traded volume over time as well as the spatial distribution of the transactions between players in each period, turns out to be a useful Early Warning Signal of the financial crisis. The W-TOPHITS is tested on the e-MID interbank market dataset and on the BIS consolidated banking statistics with the aim of discovering Systemically Important Financial Institutions and to show how the time score is able to signal a change in the bipartite network of borrowers and lenders that heralds the fall of the traded volume that occurred during the 2007/2009 financial crisis.
Keywords	Systemic Risk ; Tensor ; Early Warning Signals ; Evolving Networks
Language	English
Size	1 Online-Ressource (circa 34 Seiten), Illustrationen
Publisher	Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore
Publishing place	Milano, Italy
Document type	Book ; Online
Database	ECONomics Information System

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Article: Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets.

Pagnottoni, Paolo / Spelta, Alessandro / Pecora, Nicolò / Flori, Andrea / Pammolli, Fabio

Physica A

2021 Volume 582, Page(s) 126240

Abstract: The SARS-CoV-2 epidemics outbreak has shocked global financial markets, inducing policymakers to put in place unprecedented interventions to inject liquidity and to counterbalance the negative impact on worldwide financial systems. Through the lens of ... ...

Abstract	The SARS-CoV-2 epidemics outbreak has shocked global financial markets, inducing policymakers to put in place unprecedented interventions to inject liquidity and to counterbalance the negative impact on worldwide financial systems. Through the lens of statistical physics, we examine the financial volatility of the reference stock and bond markets of the United States, United Kingdom, Spain, France, Germany and Italy to quantify the effects of country-specific socio-economic and political announcements related to the epidemics. Main results show that financial markets exhibit heterogeneous behaviours towards news on the epidemics, with the Italian and German bond markets responding with major delays to shocks. Additionally, credit markets tend to be slower than equity markets in adjusting prices after shocks, hence being slower at incorporating the effects of such news.
Language	English
Publishing date	2021-07-07
Publishing country	Netherlands
Document type	News
ZDB-ID	1466577-3
ISSN	1873-2119 ; 0378-4371
ISSN (online)	1873-2119
ISSN	0378-4371
DOI	10.1016/j.physa.2021.126240
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Article ; Online: Network Based Scoring Models to Improve Credit Risk Management in Peer to Peer Lending Platforms.

Giudici, Paolo / Hadji-Misheva, Branka / Spelta, Alessandro

Frontiers in artificial intelligence

2019 Volume 2, Page(s) 3

Abstract: Financial intermediation has changed extensively over the course of the last two decades. One of the most significant change has been the emergence of FinTech. In the context of credit services, fintech peer to peer lenders have introduced many ... ...

Abstract	Financial intermediation has changed extensively over the course of the last two decades. One of the most significant change has been the emergence of FinTech. In the context of credit services, fintech peer to peer lenders have introduced many opportunities, among which improved speed, better customer experience, and reduced costs. However, peer-to-peer lending platforms lead to higher risks, among which higher credit risk: not owned by the lenders, and systemic risks: due to the high interconnectedness among borrowers generated by the platform. This calls for new and more accurate credit risk models to protect consumers and preserve financial stability. In this paper we propose to enhance credit risk accuracy of peer-to-peer platforms by leveraging topological information embedded into similarity networks, derived from borrowers' financial information. Topological coefficients describing borrowers' importance and community structures are employed as additional explanatory variables, leading to an improved predictive performance of credit scoring models.
Language	English
Publishing date	2019-05-24
Publishing country	Switzerland
Document type	Journal Article
ISSN	2624-8212
ISSN (online)	2624-8212
DOI	10.3389/frai.2019.00003
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Article ; Online: A behavioral approach to instability pathways in financial markets.

Spelta, Alessandro / Flori, Andrea / Pecora, Nicolò / Buldyrev, Sergey / Pammolli, Fabio

Nature communications

2020 Volume 11, Issue 1, Page(s) 1707

Abstract: We introduce an indicator that aims to detect the emergence of market instabilities by quantifying the intensity of self-organizing processes arising from stock returns' co-movements. In financial markets, phenomena like imitation, herding and positive ... ...

Abstract	We introduce an indicator that aims to detect the emergence of market instabilities by quantifying the intensity of self-organizing processes arising from stock returns' co-movements. In financial markets, phenomena like imitation, herding and positive feedbacks characterize the emergence of endogenous instabilities, which can modify the qualitative and quantitative behavior of the underlying system. The impossibility to formalize ex-ante the dynamic laws that rule the evolution of financial systems motivates the use of a parsimonious synthetic indicator to detect the disruption of an existing equilibrium configuration. Here we show that the emergence of an interconnected sub-graph of stock returns co-movements from a broader market index is a signal of an out-of-equilibrium transition of the underlying system. To test the validity of our approach, we propose a model-free application that builds on the identification of up and down market phases.
Language	English
Publishing date	2020-04-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-020-15356-z
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