Andrea TROVATO

Position
PhD Student
Dottorato
ECONOMIA
36° Ciclo - Immatricolati nel 2020
Area tematica
Bayesian Methods in Econometrics, Forecasting and Structural Time Series Analysis
Supervisore
Roberto Casarin / Monica Billio
E-mail
andrea.trovato@unive.it
956606@stud.unive.it
Website
www.unive.it/people/andrea.trovato (personal record)
Office
Department of Economics
Website: https://www.unive.it/dep.economics

Andrea Trovato, PhD candidate in Economics - Ca' Foscari University of Venice.

- Education:

  • PhD candidate in Economics, Ca' Foscari Univerisity.
  • SIdE Summer School of Econometrics: An introduction to Machine Learning and Text Mining for Economists using Stata, Python and R (2021).
  • SIdE Summer School of Econometrics: Financial Time Series and High Frequency Econometrics (2021).
  • CIdE Summer School of Econometrics: Advanced Bayesian Econometrics (2014).
  • MBBA, Bocconi University (2012-2014).
  • M.Sc. in Money and Finance, University of Brescia (2004 - 2005).
  • Graduate Degree in Economics, Thesis in Econometrics for Financial Markets - Supervisor Prof. G. Amisano, University of Brescia (2003).

- Work Experience: Quantitative Fund Manager at Eurizon Capital Asset Management (since 2008):

  • Time-varying Markov Switching Models for the Tactical Asset Allocation.
  • State Space and Stochastic Volatility Models for Equity Markets.
  • Early Warning Markov Switching Models for FX trading strategies.
  • Volatility Fair Value Models.
  • Yield Curve Fair Value Models.

- Research Areas:

  • Time-varying Markov Switching Models.
  • State Space Models.
  • Stochastic Volatility Models.
  • Bayesian Econometrics.
  • MCMC Methods.
  • Non Parametric Bayesian Econometrics.
  • Bayesian Model Averaging.
  • Forecasting and Calibration

- Research Projects:

  • Factors models with time-varying coefficients for the Tactical Asset Allocation. A Bayesian approach based on Kalman Filter and Gibbs Sampling will be derived in order to make inference on the model.
  • Time-varying Markov Switching Models with stochastic transition probabilities for trading strategies. Multivariate specifications with interactive effects will be considered in order to estimate possible spillover effects across financial markets.

- Conference Partecipation:

  • ESOBE2021 Bayesian Econometrics.

- Teaching Activities:

  • The impact of the US yield curve on the Tactical Asset Allocation Models, Ca' Foscari University (2021).
  • Markov Switching Models for Asset Allocation, MIP Politecnico of Milan (2021).
  • Bayesian Ecometrics for Financial Markets, MIP Politecnico of Milan (2020).
  • Momentum Strategies with stochastic volatility filtering, University of Bologna (2014).
  • Markov Switching Models: Bayesian Framework for the Equity Market, Ca' Foscari University (2012).
  • Overview about the Econometrics of Financial Markets, Ca' Foscari University (2012).