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Assistant Professor
Department of Accounting

Courses a.y. 2021/2022


Courses previous a.y.

Biographical note

Sep. 2018 - Present Assistant Professor at Accounting Department - Bocconi University.

Feb. 2017 - Aug. 2018. Postdoctoral Fellow with Grant at Accounting Department - Bocconi University.

Nov. 2013 - Jan. 2017. PhD Student in Applied and Computational Statistics at Modeling and Scientific Computing Lab (MOX) - Mathematics Department - Politecnico di Milano.

Sep. 2011 - Oct. 2013. Research Fellow with Grant at Management, Economics and Industrial Engineering - Politecnico di Milano.

Nov. 2010. MSc in Astrophysics and Space Physics - University of Milano-Bicocca.

Academic CV

Conferences & Research Seminars

  • 2021/05: Financial Reporting e Mercati dei Capitali Conference at Università di Bologna - Plenary session talk: Risk Disclosure and (in-)Effective Tax Planning.
  • 2021/05: Research Seminar Series at Portsmouth Business School (UK) - Invited online research talk.
  • 2020/05: Research Seminar Series at Free University of Bozen-Bolzano (Italy) - Invited research talk.
  • 2020/03: 1st Artificial Intelligence in Management Conference at USC Marshall (Los Angeles, USA) - A Better Picture: How Computer Vision Can Help Market Segmentation.
  • 2019/08: American Accounting Association Annual Meeting (San Francisco, USA) - Invited panelist in Machine Learning: corporate reporting insights.
  • 2019/07: Intelligent Information Retrieval in Accounting and Finance (Beijing, China) - When Less Is Not Necessarily More: Loosing Meaning with Dedicated Dictionaries.
  • 2018/05: Annual Congress of European Accounting Association (Milan, Italy) - Equity Analyst Responsiveness to the Tone in MD&A Filings.
  • 2017/11: Talent Workshop - EAA Job Market for Accounting Academics (Madrid, Spain) - Using Machine Learning and Survival Analysis to Estimate Analysts Speed to Incorporate Tone from MD&A Filings.
  • 2016/06: 48th Scientific Meeting of the Italian Statistical Society (Salerno, Italy) - A multi-state approach to patients affected by chronic heart failure: the value added by administrative data.
  • 2016/03: 8th IMA Conference on Quantitative Modeling in the Management of Health and Social Care (London, UK) - A multi-state approach to patients affected by chronic heart failure: the value added by administrative data.
  • 2015/04: StaTalks (Milan, Italy) Intensive Statistical Computing with R.

Research Grants

  • 2020: Bocconi Senior Researchers' Grants - from November 2020 to November 2021 - Co-Principal Investigator
  • 2019: Bocconi Junior Researchers' Grants - from May 2019 to May 2020 - Principal Investigator

Public Software

  • OpTop Optimal Topics Detection [hosted on Github]: R package which implements a set of statistical tools to detect and evaluate the optimal number of topics out of a Latent Dirichelet Allocation (LDA) model in the context of Natural Language Processing. This is a huge advantage since it provides a goodness of fit tool in the context of semi-supervised method such the LDA. This also protects from researcher own judgment when selecting topics.
  • msmtools Multi-State Models Tools [hosted on Github and available at official R repository CRAN]: R package which implements a fast and efficient algorithm to restructure classical longitudinal database into an augmented format. This increments the amount of information out of data and facilitates the modeling through the companion package msm.
  • statutils Statistical Utilities [hosted on Github]: R package which gathers several statistical utilities devoted both to data wrangling/management and modeling. In particular, it implements an automatic model selection procedure for linear models which enables to choose only high order effects. It also comes with a tool to reduce a dataset once it has been imputed through the mice package.

Scientific Affiliations

  • BIDSA Affiliate: Bocconi Institute for Data Science and Analytics (website here).
  • SIS: Società Italiana di Statistica.
  • AAA: American Accounting Association.
  • EAA: European Accounting Association.

Research areas

My research areas cover the fields of Accounting and Finance as well as Marketing and Management. I am involved in several research projects in which I am in charge of the development of all the computational and statistical methodology. My main research topics are:


  • Natural Language Processing: identification of relevant semantic structures through topic modeling. Deception detection in uncontrolled environment such as Conference Calls 
  • Artificial Intelligence and Computer Vision algorithms devoted to object detection and recognition in 2D images. The main field of application is real-time fashion industry.
  • Multi-state models, survival analysis, and stochastic processes.
  • Development of efficient algorithms to process large in-memory data and to reduce computational time.
  • Economic and business impact of blockchain technology. Distributed consensus protocols and smart contract implementation.



Published Papers

  • M. Gietzmann and F. Grossetti (2021): Blockchain and other Distributed Ledger Technologies: where is the Accounting? - Journal of Accounting and Public Policy (IF. 2.815). DOI: http://dx.doi.org/10.1016/j.jaccpubpol.2021.106881.
  • E. Pasini, L. Comini, F.S. Dioguardi, F. Grossetti, A. Olivares, R. Aquilani, S. Scalvini (2020): Hypoalbuminemia as a Marker of Protein Metabolism Disarrangement in Patients with Stable Chronic Heart Failure - Minerva Medica (IF. 1.202)
  • S. Scalvini, F. Grossetti, A.M. Paganoni, M.T. La Rovere, R. Pedretti, M. Frigerio (2019): Impact of in-hospital Cardiac Rehabilitation on Mortality and Readmissions in Heart Failure: A Population Study in Lombardy, Italy, from 2005 to 2012 - European Journal of Preventive Cardiology (IF. 5.640). DOI: 10.1177/2047487319833512.
  • F. Grossetti, F. Ieva, A.M. Paganoni (2017): A multistate approach to hospital readmissions of patients affected by chronic heart failure: the value added by administrative data - Health Care Management Science (IF. 2.059). DOI: 10.1007/s10729-017-9400-z.
  • B. Gialanella, F. Grossetti, M. Mazza, L. Danna, L. Comini; (2017): Functional recovery after rotator cuff repair for full thickness tear: the role of biceps surgery - Journal of Sport Rehabilitation (IF. 1.811). DOI: 10.1123/jsr.2015-0055.
  • M. Vitacca, M. Paneroni, F. Grossetti, N. Ambrosino (2016): Is there any additional effect of tele-assistance on long term care programs in hypercapnic COPD patients? - Journal of Chronic Obstructive Pulmonary Disease (IF. 2576). DOI: 10.3109/15412555.2016.1147542.
  • G. Gavazzi, M. Fumagalli, M. Fossati, V. Galardo, F. Grossetti, A. Boselli, R. Giovanelli, M.P. Haynes (2013): Hα3: an Hα imaging survey of HI selected galaxies from ALFALFA. II. Star formation properties of galaxies in the Virgo cluster and surroundings - Astronomy & Astrophysics (IF. 6.209).
  • G. Gavazzi, M. Fumagalli, V. Galardo, F. Grossetti, A. Boselli, R. Giovanelli, M.P. Haynes, and S. Fabello (2012): Hα3: an Hα imaging survey of HI selected galaxies from ALFALFA. I. Catalogue in the Local Supercluster - Astronomy & Astrophysics (IF. 6.209).

Submitted Papers

  • C. Lewis and F. Grossetti: A Statistical Approach for Optimal Topic Model Identification. (2nd round at Journal of Machine Learning Research) (latest version available on ResearchGate here).
  • M. Gietzmann, F. Grossetti, C. Lewis: Investor Inattention, Financial Narrative, and Tone-Based Heuristics (Submitted).
  • O. Bogachek, M. Gietzmann, F. Grossetti: Risk Guidance and Anti-Corruption Language: Evidence from Corporate Codes of Conduct (Submitted).

Working Papers

  • O. Bogachek, A. DeVito, F. Grossetti: Risk Disclosure and (in-)Effective Tax Planning.
  • M. Gietzmann, F. Grossetti, C. Lewis: Investor Inattention, Financial Narrative, and Tone-Based Heuristics.
  • M. Gietzmann, F. Grossetti, A. Huang: Predicting the Success of Jawboning in Fight Letters: Evidence from a Deep Learning Approach.
  • A. Caglio, F. Grossetti, G. Melloni: Do Firms Speak ESG and Do Investors Listen? Information content and market effects of mandatory non-financial disclosures.
  • F. Grossetti and C. Lewis: OpTop: an R Package to Detect the Optimal Number of Topics.
  • Bogachek, O. and F. Grossetti: On the Non-Linear Value Relevance of Tone Measures.
  • F. Grossetti, G. Rubera, P. Cillo: A Better Picture: How Computer Vision Can Help Market Segmentation.