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M. Bernardi

21 papers hereh-index 161k citations85 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author15
  • middle author4
  • last author2

Across the 21 of 21 papers where every author was matched, so the position is known.

fields
  • stat.ME8
  • stat.AP4
  • econ.EM2
  • q-fin.ST2
  • math.ST1
  • q-fin.MF1
same name
  • M. Bernardi — 122 papers, h 62
  • M. Bernardi — 38 papers, h 37
  • M. Bernardi — 5 papers, h 9
  • M. Bernardi — 3 papers, h 22
  • M. Bernardi — 3 papers, h 8
  • M. Bernardi — 2 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132023
most citedMultivariate Markov-Switching models and tail risk interdependence

6 citations · 35 across the 20 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

econ.EM2022

Flexible variational approximations for stochastic volatility-managed portfolios

Nicolas Bianco, Mauro Bernardi

This paper investigates volatility-managed portfolios through a variational Bayes approach that smooths stochastic volatility forecasts. Our algorithm exhibits competitive performa…

stat.AP2022

Missing data patterns in runners' careers: do they matter?

Mattia Stival, Mauro Bernardi, Manuela Cattelan +1

Predicting the future performance of young runners is an important research issue in experimental sports science and performance analysis. We analyse a data set with annual seasona…

stat.AP2022

Doubly-online changepoint detection for monitoring health status during sports activities

Mattia Stival, Mauro Bernardi, Petros Dellaportas

We provide an online framework for analyzing data recorded by smart watches during running activities. In particular, we focus on identifying variations in the behavior of one or m…

econ.EM2022★ 2 cited

Variational inference for large Bayesian vector autoregressions

Mauro Bernardi, Daniele Bianchi, Nicolas Bianco

We propose a novel variational Bayes approach to estimate high-dimensional vector autoregression (VAR) models with hierarchical shrinkage priors. Our approach does not rely on a co…

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