Dear Colleagues,

 

   a special session entitled ‘Challenges in modelling sparse and noisy data’ will take place during the AMASES Annual Conference, which will be held in Perugia on September 9-11, 2019 (http://amases2019.unipg.it).


 

Topic of the session

 

Far more than in the past, policy makers, investors, and data scientists are required to take decisions based on sparse and noisy data. Observations from heterogeneous sources, typically sampled at different frequencies, and contaminated by noise, need to be aggregated and analyzed jointly. This is customary in several economic applications, including macroeconomics, high-frequency finance, climate economics, and data science. Traditional mathematical and statistical methods can lead to misleading conclusions when these features are not properly accounted for. The objective of this session is to present the latest methodologies and to foster discussions among researchers from different fields.

  

Theoretical and empirical papers are welcome. Topics include but are not limited to:

-       high-frequency time series modelling 

-       mixed-frequency data modelling in economic and social sciences

-       dimensionality reduction and factor analysis

-       sparse data modelling

-       noisy data filtering and smoothing

 

It is a great pleasure to invite you to submit an extended abstract. To be considered for the stream, please submit your abstract by specifying the stream code (MSND) in the file name (MSND-[surname of author who will present the paper].pdf). 

Please refer to the official web page of the conference for further details on the submission.

 

Important dates:

May 1, 2019: deadline for abstract submission

June 10, 2019: notification of acceptance

June 17, 2019: early registration

July 1, 2019: late registration

 

For information, please contact:

 

Giacomo Bormetti (giacomo.bormetti@unibo.it)

Giuseppe Buccheri (giuseppe.buccheri@sns.it)

Fabrizio Lillo (fabrizio.lillo@unibo.it) 

 

We are looking forward to meeting you in Perugia.

 

Best regards

 

Giacomo Bormetti, Giuseppe Buccheri, and Fabrizio Lillo