Luca Trapin

Luca Trapin photo
Candidate PhD in Economics (XXVIII cycle) at IMT Institute for Advanced Studies Lucca, under the joint supervision of Prof. Massimo Riccaboni and Prof. Marco Bee

I graduated from the University of Trento (Italy) where I obtained my Bachelor's degree in Economics and Business Administration in 2010, and a Master's degree in Finance in 2012.  I also spent a period abroad at Maastricht University (Netherlands), in fall 2011.


I have been visiting PhD researcher at HEC Montréal, under the supervision of  Prof. Debbie Dupuis.

Job Market Paper: Extremal Behaviour of Financial Returns and Models

While there exists an extensive literature on the autocorrelation of asset returns and volatility, serial dependence in extreme returns, i.e. extremal dependence, has been mostly ignored. This paper gives three contribution in this direction. First, exploiting dierent statistical procedures, we provide evidence of strong and persistent extremal dependence in both the upper and lower tails of the daily return distribution and in the extremes of the return variance. Second, we investigate the extremal properties of a class of processes for the daily returns and variance that exploits high-frequency (intra-daily) data. Third, we propose to estimate continuous-time models with a Simulated Method of Moments estimator which includes extreme moment conditions in order to match the empirical extremal dependence with that implied by the estimated model.

 

Research Interest

Financial Econometrics, Financial Economics, Statistics and Econometrics, Network Economics.

Publications

  1. Bee M., Dupuis D. and Trapin L. (2016). Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective. Journal of Empirical Finance (Forthcoming).
  2. Bee M., Dupuis D. and Trapin L. (2016). U.S. stock returns: Are there seasons of excesses?. Quantitative Finance (Forthcoming).
  3. Bee M. and Trapin L. (2016). A simple approach to the estimation of Tukey's gh distribution. Journal of Statistical Computation and Simulation (Forthcoming).
  4. Chessa A., Crimaldi I., Riccaboni M. and Trapin L. (2014). Cluster analysis of weighted bipartite networks: A new copula-based approach. PlosOne, 9(10): e109507.
  5. Bee M., Riccaboni M. and Trapin L. (2016). An extreme value analysis of the last century crises across industries in the U.S. Economy. (Submitted).

Work in progress

  1. Trapin L. (2015). Extremal Behaviour of Financial Returns and Models
  2. Dupuis D. and Trapin L. (2015). Tail spillovers in the Euro area.
  3. Trapin L. (2015). Dynamic Tail Risk and asset Prices.
  4. Trapin L. (2015). Systemic Peaks over Treshold. A dynamic extreme value model of systemic risk.
  5. Bee M., Dupuis D. and Trapin L. (2015) Realized Extreme Quantile. A time-varying threshold model for financial exceedances.
  6. Bee M., Dupuis D. and Trapin L. (2015) Generalized dynamic extreme value models for financial time series.