Andrea BucciUniversity of Macerata | UNIMC · Department of Economics and Law
Andrea Bucci
PhD in Economics
About
46
Publications
14,202
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
144
Citations
Citations since 2017
Introduction
Additional affiliations
March 2020 - April 2020
July 2018 - March 2020
September 2017 - present
Education
November 2013 - October 2016
Publications
Publications (46)
Accurately estimating and predicting chronological age from some anthropometric characteristics of an individual without an identity document can be crucial in the context of a growing number of forced migrants. In the related literature, the prediction of chronological age mostly relies upon the use of a single predictor, which is usually represen...
This paper introduces a novel portfolio optimization method, the Clustered Minimum Spanning Tree Nested Optimization, capable of overcoming the limitations of classical asset allocation, such as instability and over-concentration of portfolio weights, and providing a defensive mechanism against the enhanced systematic risk during high-volatility pe...
In many applications, data are observed as matrices with temporal dependence. Matrix-variate time series modeling is a new branch of econometrics. Although stylized facts in several fields, the existing models do not account for regime switches in the dynamics of matrices that are not abrupt. In this paper, we extend linear matrix-variate autoregre...
This study aims to investigate the association between gross domestic product (GDP), mortality rate (MR) and current healthcare expenditure (CHE) in 31 high-income countries. We used panel data from 2000 to 2017 collected from WHO and OECD databases. The association between CHE, GDP and MR was investigated through a random-effects model. To control...
![Volatility plots for n=15\documentclass[12pt]{minimal}...](publication/364280899/figure/fig1/AS:11431281093783461@1667271873770/Volatility-plots-for-n15documentclass12ptminimal-usepackageamsmath_Q320.jpg)
![Volatility plots for n=15\documentclass[12pt]{minimal}...](publication/364280899/figure/fig2/AS:11431281093773781@1667271873863/Volatility-plots-for-n15documentclass12ptminimal-usepackageamsmath_Q320.jpg)
Forecasting covariance matrices is a difficult task in many research fields since the predicted matrices should be at least positive semidefinite. This problem can be overcome by including constraints in the predictive model or through a parametrization of the matrices to be predicted. In this paper, we focus on the latter approach in a financial a...
Identifying market regimes is crucial for asset pricing and portfolio management. Within efficient markets, the macroeconomic conditions drive the demand for risky assets. Consequently, the transitions between different regimes are reflected into covariance matrices, whose time-varying coefficients react to unexpected news. Accordingly, we identify...
Background:
Perceived health is largely dependent on multiple socio-demographic and behavioral lifestyles and healthcare related factors. This could be accentuated when gender is taken into account. The aim of this study is to explore gender-related differences in multiple socio-demographic and behavioral lifestyles and healthcare related factors...
The impact of the COVID-19 pandemic varied significantly across different countries, with important consequences in the definition of control and response strategies. In this work, to investigate the heterogeneity of this crisis, we analyse the spatial patterns of deaths attributed to COVID-19 in several European countries. To this end, we propose...
Modern healthcare management and clinical practice strongly rely on data and scientific evidence. Digital technologies, tools, and services are core components of Healthcare Management and scientific Research (HMR). Data interoperability, security, privacy, and ease of sharing represent fundamental conditions for guaranteeing quality HMR. Current d...
Background
Long-term parenteral nutrition (PN) is the mainstay of the therapeutic strategy in intestinal failure (IF) due to neonatal short bowel syndrome (SBS). Our aim was to identify prognostic factors for PN weaning and to assess if measuring plasma citrulline concentrations over time could account for the intestinal adaptation in progress.
Me...
There is broad empirical evidence of regime switching in financial markets. The transition between different market regimes is mirrored in correlation matrices, whose time-varying coefficients usually jump higher in highly volatile regimes, leading to the failure of common diversification methods. In this article, we aim to identify market regimes...
Dental root calcification has proven to be a reliable biological evidence to estimate chronological age of children. The development of structures usually examined in the age estimation forensic practice (e.g. skeleton, teeth) is supposed to be influenced by diseases and nutritional, environmental, ethnic, and ultimately even socioeconomic factors....
Background
The alignment of human lower limb has been an area of ongoing study for decades. The purpose of this study was to analyze the axial and rotational alignment from hip to ankle in a Caucasian aged non-arthritic cohort.MethodsA non-arthritic cohort of aged patients was retrospectively analyzed by computer tomography. Anatomical–mechanical a...
Background
The Institute for Health Sciences in Aragon developed a process-mining based algorithm deployed using a container solution to describe the Stroke Care Pathway reproducible in different Health Systems. Our aim is to apply the proposed solution to administrative data of an Italian region to explore interoperability in the case of the strok...
In the last few decades, a broad strand of literature in finance has implemented artificial neural networks as a forecasting method. The major advantage of this approach is the possibility to approximate any linear and nonlinear behaviors without knowing the structure of the data generating process. This makes it suitable for forecasting time serie...
Accurately forecasting multivariate volatility plays a crucial role for the financial industry. The Cholesky‐Artificial Neural Networks specification here presented provides a twofold advantage for this topic. On the one hand, the use of the Cholesky decomposition ensures positive definite forecasts. On the other hand, the implementation of artific...
This paper addresses the question of the relevance of macroeconomic determinants in forecasting the evolution of stock markets volatilities and co-volatilities. Our approach combines the Cholesky decomposition of the covariance matrix with the use of the Vector Logistic Smooth Transition Autoregressive Model. The model includes predetermined variab...
Forensic age estimation is receiving growing attention from researchers in the last few years. Accurate estimates of age are needed both for identifying real age in individuals without any identity document and assessing it for human remains. The methods applied in such context are mostly based on radiological analysis of some anatomical districts...
In the last few decades, a broad strand of literature in finance has implemented artificial neural networks as forecasting method. The major advantage of this approach is the possibility to approximate any linear and nonlinear behaviors without knowing the structure of the data generating process. This makes it suitable for forecasting time series...
Accurately forecasting multivariate volatility plays a crucial role for the financial industry. The Cholesky-Artificial Neural Networks specification here presented provides a twofold advantage for this topic. On the one hand, the use of the Cholesky decomposition ensures positive definite forecasts. On the other hand, the implementation of artific...
The main objective of this article is to describe the legal principles governing the selection by European public authorities, such as National Health Services (NHS), of third parties, when entering into agreements for the transfer of health data. According to Directive 2003/98/EC, and in light of the provisions of the Treaties of the European Unio...
Background
After 2008 global economic crisis, Italian governments progressively reduced public healthcare financing. Describing the time trend of health outcomes and health expenditure may be helpful for policy makers during the resources’ allocation decision making process. The aim of this paper is to analyze the trend of mortality and health spen...
Modeling financial volatility is an important part of empirical finance. This paper provides a literature review of the most relevant volatility models, with a particular focus on forecasting models. We firstly discuss the empirical foundations of different kinds of volatility. The paper, then, analyses the non-parametric measure of volatility, nam...
Background:
The sustainability of healthcare systems is a topic of major interest. During periods of economic instability, policy makers typically reallocate resources and execute linear cuts in different areas of public spending, including healthcare.
Objectives:
The aim of this paper was to examine whether and how per capita public healthcare...
Questions
Question (1)
I am trying to forecast a persistent time series through neural networks. Accordingly, I would like to compare the perfomance of several kinds of neural networks: feedforward, Elman, Jordan, LSTM and NARX. I am not sure that I have understood the difference between a Jordan neural network and a NARX. Since they both take exogenous variables as inputs and previous outputs as additional inputs, is the number of delayed outputs used as inputs (i.e. 1 for the JNN and n for the NARX) the only difference?
Projects
Projects (3)
The project aims at providing new tools to forecast the realized volatility in the univariate and multivariate context. Specifically, the project relies on nonlinear models such as smooth transition models or artificial neural Networks.
