Quantitative Methods for Economics

The research activity in quantitative methods for economics is based on three macro-areas: (a) econometrics, (b) statistics and (c) optimisation. (a) Within the field of Econometrics, appropriate methods are used and developed for the collection and analysis of non-experimental economic data from both longitudinal and time series. The main applications consist in the following activities: forecasting of macroeconomic and financial variables; the quantitative analysis of individual and collective economic behaviour; the impact assessment of economic and public policies; the measurement of risk; the empirical analysis of the evolution in the life cycle of saving and investment decisions at households level; the empirical analysis of the determinants of investment choices in R&D. (b) The main object of the statistical research area is related to the development of statistical methodologies and techniques for data analysis, for the design and implementation of surveys and experiments, the development of new probabilistic models as well as of the related inferential procedures. Some of the topics investigated in this area are related to demographic and social statistical analysis, robust parameter estimation, meta-analysis of different studies related to the same object of interest, models for time series and spatial economics, statistical methods for the integration of data from different sources. (c) The research activity within the optimisation field primarily concerns the study of theoretical aspects of constrained optimisation problems and variational inequalities. These models are involve both scalar and vectorial cases; in particular, are investigated the necessary and/or sufficient conditions for optimality; the definition of generalized Langragian and the consequent definition of Kuhn-Tucker multipliers and of generalized dual problems that could be not necessarily convex or non-differentiable. The topics developed in this area include also applicative aspects: optimization of the risk-return profile of investors operating in international markets; methods of stochastic optimisation for portfolio selection; mathematical methods applied to the design of automated trading systems formulated as problems of stochastic optimal control.
Francesco Andreoli
Associate Professor
Alessandro Bucciol
Full Professor
Maria Flora
Research Assistants
Bruno Giacomello
Associate Professor
Alessandro Gnoatto
Full Professor
Luigi Grossi
Visiting Professors
Diego Lubian
Full Professor
Cecilia Mancini
Full Professor
Eleonora Matteazzi
Temporary Assistant Professor
Marco Minozzo
Associate Professor
Alberto Peretti
Associate Professor
Paolo Pertile
Full Professor
Athena Picarelli
Associate Professor
Roberto Renò
Full Professor
Francesca Rossi
Associate Professor
Alberto Roveda
Assistant Professor
Catia Scricciolo
Associate Professor
Research interests
Topic People Description
Hamilton-Jacobi theories, including dynamic programming (see  MSC classification)
MSC 49L20 - Dynamic programming method Athena Picarelli
An optimal control problem is defined starting from a dynamics, a set of controls acting on this dynamics and a cost (or gain), functional of the control and the associated dynamics. The objective is to minimize (or maximize) this cost (or gain). The value function (function of the initial time and position) is defined as the optimal value, i.e. the minimum (or maximum) value of the cost (or gain), associated to the problem. I study optimal control problems for which the dynamics is given by a stochastic differential equation. By the dynamic programming approach the value function can be characterized as the solution (in the weak viscosity sense) of a partial differential equation called the Hamilton-Jacobi-Bellman equation.
Numerical methods (see  MSC classification)
MSC 49M37 - Methods of nonlinear programming type Alberto Peretti
Alberto Roveda
Methods for solving constrained  and unconstrained problems with non-linear functions. This includes the Gradient type methods, Method of conjugate gradient, Newton-type methods, Near-Newton methods, Penalization methods and Interior Point methods. It also covers differentiable  and non-differentiable case study, Multi-objective optimization and numerical experimentation of the mentioned methods on test problems and application to real problems.
Data Collection and Data Estimation Methodology ; Computer Programs (see  JEL classification)
JEL C80 - General Francesco Andreoli
Implementazione e sviluppo software per l'analisi statistica ed econometrica, per il trattamento dati e per la rappresentazione grafica.
Econometric and Statistical Methods and Methodology: General (see  JEL classification)
JEL C12 - Hypothesis Testing: General Cecilia Mancini
Francesca Rossi
Hypotesis testing to detect spatial correlation and to assess whether models are correctly specified, development of analytical corrections to improve tests' performance in finite samples.
JEL C13 - Estimation: General Cecilia Mancini
Marco Minozzo
Development and estimation of statistical models in finance, and for economic and social data; computationally intensive Monte Carlo estimation algorithms such as Monte Carlo EM and sequential Monte Carlo.
JEL C14 - Semiparametric and Nonparametric Methods: General Cecilia Mancini
Stime dei coefficienti di semimartingale con salti definite a tempi continui ma osservate a tempi discreti.
JEL C15 - Statistical Simulation Methods: General Marco Minozzo
Francesca Rossi
Computer intensive estimation methods based on Monte Carlo simulations, bootstrap and indirect inference. Also includes machine learning, and development of statistical software for the analysis of economic phenomena.
JEL C18 - Methodological Issues: General Francesco Andreoli
Eleonora Matteazzi
Francesca Rossi
Derivation of properties of estimators and test statistics in large samples and their analytical corrections for small/medium samples.
Econometric Modeling (see  JEL classification)
JEL C51 - Model Construction and Estimation Cecilia Mancini
Modellizzazione dei (possibili) salti nei prezzi di titoli finanziari, osservati in modo discreto.
JEL C52 - Model Evaluation, Validation, and Selection Cecilia Mancini
Stima, diagnostica e selezione di modelli per i salti nelle traiettorie dei prezzi di titoli finanziari, date osservazioni discrete.
JEL C53 - Forecasting and Prediction Methods;Simulation Methods Luigi Grossi
Statistical methods for short-term prediction of time series. Evaluation of forecasting performance using computer simulated data.
JEL C58 - Financial Econometrics Luigi Grossi
Diego Lubian
Cecilia Mancini
Roberto Renò
Covers studies related to econometric modeling of financial markets. Analysis of econometric models with continuous time and its applications in finance. Robust estimates for volatility models of financial returns.
Mathematical Methods; Programming Models; Mathematical and Simulation Modeling (see  JEL classification)
JEL C61 - Optimization Techniques; Programming Models; Dynamic Analysis Bruno Giacomello
Alessandro Gnoatto
Cecilia Mancini
Alberto Peretti
Paolo Pertile
Alberto Roveda
Covers theory and methods for optimization problems. Linear programming and mathematical programming. Vector optimization and duality models. Economic applications to the problems of optimal investment choices under conditions of uncertainty and portfolio optimization. Estimation of the parameters of financial models including a risk-neutral assumption and calibration of the models. Stochastic optimization for finding estimators of the volatility of a semimartingale with jumps.
Multiple or Simultaneous Equation Models; Multiple Variables (see  JEL classification)
JEL C32 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Models;Diffusion Processes;State Space Models Luigi Grossi
Robust estimation of model coefficients applied to financial and energy data odered by time. Analysis and prediction of prices collected on financial and electricity markets.
Single Equation Models; Single Variables (see  JEL classification)
JEL C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions Francesca Rossi
Inference for spatial data, teoretical analysis of the models known as spatial autoregressions and their application in empirical settings.
JEL C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Models; Diffusion Processes Diego Lubian
Estimation, inference and forecasting in time series models. Applications to financial markets.
JEL C23 - Models with Panel Data; Longitudinal Data; Spatial Time Series Alessandro Bucciol
Panel data analysis: estimation and evaluation of static and dynamic models for microeconomic data. Applications in the fields of industrial and health economics, behavioral economics, environmental economics and consumption and saving decisions.
JEL C25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions Alessandro Bucciol
Empirical and theoretical analysis of models for limited dependent variable (binary variable, count data, truncated and censored samples). With applications in the fields of environmental economics, industrial and health economics, consumption and saving decisions.
Mathematical programming, optimization and variational techniques (see  MSC classification)
MSC 65K05 - Mathematical programming methods Alberto Peretti
General and numerical methods for the solution of the problem of finding the maximum/minimum of a scalar function with some equality/inequality constraints. In addition to the classical techniques that assume first and second differentiability of the functions, the case of non differentiable functions is also considered.
Partial differential equations, initial value and time-dependent initial- boundary value problems (see  MSC classification)
MSC 65M06 - Finite di erence methods Athena Picarelli
Only in very few cases Hamilton-Jacobi-Bellman equations admit an explicit solution. It becomes then fundamental the numerical approximation of the solution. Numerical methods for partial differential equations are basically divided in: finite elements methods and finite difference methods. The latter are based on a Taylor approximation of derivatives. They are quite simple and intuitive methods for which a complete convergence analysis in the class of solutions of the equation in the viscosity sense is available.
MSC 65M15 - Error bounds Athena Picarelli
Defined a numerical approximation scheme for a partial differential equation and proved its convergence, it is also interesting to provide error estimates. For classical solutions of elliptic and parabolic equation this can be obtained by quite standard techniques. However, in the particular case of viscosity solutions specific analytic regularization techniques have to be applied.
Probabilistic methods, simulation and stochastic differential equations (see  MSC classification)
MSC 65C05 - Monte Carlo methods Bruno Giacomello
Alessandro Gnoatto
Marco Minozzo
Monte Carlo methods for estimating and predicting dynamic models, such as Markov chain Monte Carlo, particle filters and sequential Monte Carlo. Applications of these methods to economic and financial field. In particular, applications for the numerical solution of stochastic differential equations forward-backward. Also covers Longstaff-Schwartz regression methods for the solution of Snell envelopes and applications in the counterparty risk field.
Mathematical programming (see  MSC classification)
MSC 90C05 - Linear programming Alberto Peretti
Methods and numerical algorithms for the solution of a linear programming problem, that is a mathematical programming problem where the functions are assumed to be linear. The simplex method and its generalizations.
MSC 90C30 - Nonlinear programming Alberto Peretti
Methods and numerical algorithms for the solution of a mathematical programming problem where the functions are specifically assumed to be non linear.
MSC 90C46 - Optimality conditions, duality Alberto Peretti
Optimality conditions for constrained and unconstrained extremum problems: sufficient and necessary conditions in the case of differentiable and non-differentiable functions. Image Space Analysis: sufficient and necessary optimality conditions for not convex and / or non-differentiable problems. Regularity conditions and constraint qualifications for scalar and vector optimization problems.
Parabolic equations and systems (see  MSC classification)
MSC 35K61 - Nonlinear initial-boundary value problems for nonlinear parabolic equations Athena Picarelli
The study of parabolic equations is related to evolutive diffusion problems. Hamilton-Jacobi-Bellman equations are fully nonlinear possibly degenerate equations belonging to this class and arise in the study of stochastic optimal control problems. Fixed suitable initial and boundary conditions, I’m interested in the study of existence and uniqueness of solutions, their regularity and numerical approximation.
Stochastic analysis (see  MSC classification)
MSC 60H10 - Stochastic ordinary differential equations Alessandro Gnoatto
Analysis of continuous time stochastic processes. Applications of stochastic differential equations of forward and backword type with jumps to problems of financial pricing and optimal control.
MSC 60H30 - Applications of stochastic analysis Maria Flora
Bruno Giacomello
Alessandro Gnoatto
Applications of continuous-time stochastic processes in economics and finance. Analysis of pricing problems and contingent claims. Studies of problems of risk management and applications of measures of risk.
MSC 60H35 - Computational methods for stochastic equations Alessandro Gnoatto
Probabilistic computational methods: recursive marginal quantization and Fourier-quantization. Exposure estimation in models featuring counterparty risk.
Applications (see  MSC classification)
MSC 62P05 - Applications to actuarial sciences and financial mathematics Bruno Giacomello
Marco Minozzo
Risk modelling in insurance and finance, in particular credit risk with the development of credit scoring models and algorithms; calibration of the probabilities of defaults; market segmentation.
Inference from stochastic processes (see  MSC classification)
MSC 62M10 - Time series, auto-correlation, regression, etc. Marco Minozzo
Modelling and analysis (data science) of univariate and multivariate time series, equally or unequally spaced, including the use of models with latent factors and for skewed data; machine learning methods for the analysis of large collections of time series.
MSC 62M20 - Prediction; filtering Marco Minozzo
Forecasting and filtering techniques of the signal such as, for instance, the Kalman filter; prediction, smoothing and filtering techniques based on Monte Carlo simulation, such as particle filtering and sequential Monte Carlo.
Multivariate analysis (see  MSC classification)
MSC 62H11 - Directional data; spatial statistics Marco Minozzo
Modelling and analysis (data science) of areal and georeferenced data, both univariate and multivariate, with the use of Gaussian and non-Gaussian models (for discrete or skewed data, etc.); development of spatial models with latent factors; modelling of directional data.
Nonparametric inference (see  MSC classification)
MSC 62G20 - Asymptotic properties Catia Scricciolo
Analysis of likelihood-based procedures: - consistency and rates of convergence of nonparametric maximum likelihood estimators in Hellinger distance; - theory of frequentist asymptotic properties for nonparametric Bayes procedures, including general contraction rate results for posterior distributions, adaptive estimation and coverage properties of nonparametric credible sets.
Parametric inference (see  MSC classification)
MSC 62F15 - Bayesian inference Catia Scricciolo
Bayesian theory of function estimation in nonparametric statistical models, including the study of credible sets to provide a data-driven quantification of the uncertainty for point estimators. Analysis also covers inverse problems, such as deconvolution, wherein the object of interest has to be recovered from indirect noisy observations.
MSC 62F35 - Robustness and adaptive procedures Luigi Grossi
Robust estimation of model parameters which are not affected by the presence of outlying observations. Outlier detection through forward search methods.
Projects
Title Managers Sponsors Starting date Duration (months)
Dipartimento di Eccellenza Alessandro Sommacal, Marco Piovesan MIUR 1/1/23 60
Cross-border electricity trading Maria Flora Post-doc 1/1/19 36
FAIR-PLAY: studio e sviluppo di nuovi servizi e modelli di marketing 4.0 in ambiente fieristico - Studio e progettazione di strategie per l'analisi di Big Data e realizzazione di modelli di business per la profilazione di eventi fieristici Marco Minozzo, Martina Gentilin Assegno FSE - assegnato e gestito dal Dipartimento 10/15/18 12
The role of behavioral strategies in effectively promoting STEM education Maria Vittoria Levati Ricerca di Base di Ateneo 2015 10/1/17 24
Efficient and Equitable Regulation for Health Care Innovation: Theory and Evidence Paolo Pertile, Barbara Bonvento borsa di ricerca - assegnato e gestito dal Dipartimento 9/1/17 18
High Frequency Liquidity Roberto Renò Ricerca di Base di Ateneo 2015 1/1/17 24
Accounting for structural changes in stationary and nonstationary time series Maddalena Cavicchioli Post-doc 9/1/16 9
Poisson Games and Political Economy Claudia Meroni Post-doc 9/1/16 36
NUOVA ISEE - MY WELFARE Federico Perali, Elena Dalla Chiara Assegno finalizzato - assegnato e gestito dal Dipartimento 1/1/16 21
Nonlinear effects of Monetary Policy Shocks in Conventional and Unconventional Times Valentina Colombo Post-doc 12/2/15 16
Scelte di portafoglio, fiducia e preferenze al rischio Alessandro Bucciol, Ivan Soraperra Assegno finalizzato - assegnato e gestito dal Dipartimento 11/1/15 12
Facing credit risk: a mathematical approach to risk measures and their management Immacolata Oliva Post-doc 9/1/15 36
Giochi elettorali di Poisson Francesco De Sinopoli, Claudia Meroni Assegno finalizzato - assegnato e gestito dal Dipartimento 9/1/15 12
Markets for votes: conflict, distribution and welfare Monica Anna Giovanniello Post-doc 9/1/15 36
Assegno: Analisi Causale della Criminalità Giovanile in Italia: uno studio caso-controllo Federico Perali 6/1/14 12
Assegno: Analisi econometrica del passaggio dall'università al mondo del lavoro Diego Lubian 5/1/14 12
Assegno: Tecniche di inferenza Monte Carlo basate sulla verosimiglianza per modelli gerarchici per dati geostatistici multivariati non gaussiani Marco Minozzo, Luca Bagnato 4/1/12 12
Analisi e modellizzazione di fenomeni spaziali di particolare interesse per il territorio vicentino Marco Minozzo 7/1/10 24
Monte Carlo maximum likelihood for high dimensional dependency models with latent components or measurement errors Marco Minozzo Ministero dell'Istruzione dell'Università e della Ricerca 3/22/10 24
Multivariate model-based geostatistics Marco Minozzo 2/1/10 24
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