Research paper

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Distribution forecasts for macroeconomic variables are often evaluated against realizations observed with time-varying measurement error. I examine the sensitivity of the log score, the quadratic score and the continuous ranked probability score to the presence of noise in the observations and investigate to what extent these scoring rules can be robustified in the sense of making their forecast rankings less prone to measurement error.
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We examine whether low-volatility factor investing can benefit from using time series models that employ intraday data.
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Theoretical and evidence-based examination of multiplicative volatility models that decompose the conditional variance into a short- and a long-term component.
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Econometric software

R package: mfGARCH

  • An R package for estimating multiplicative mixed-frequency GARCH models (GARCH-MIDAS) as proposed in Engle et al. (2013)
  • Can be installed from CRAN
  • Development version can be found in its Github repository
  • Creator and maintainer

R package: alfred

  • Provides direct access to the FRED and ALFRED databases. Its functions return tidy data frames for different releases of the specified time series.
  • Can be installed from CRAN
  • Development version can be found in its Github repository
  • Creator and maintainer

Conferences & Summer Schools

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