Stefano Grassi

878 total citations
51 papers, 481 citations indexed

About

Stefano Grassi is a scholar working on Economics and Econometrics, Finance and Statistics and Probability. According to data from OpenAlex, Stefano Grassi has authored 51 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Economics and Econometrics, 20 papers in Finance and 13 papers in Statistics and Probability. Recurrent topics in Stefano Grassi's work include Financial Risk and Volatility Modeling (19 papers), Complex Systems and Time Series Analysis (17 papers) and Monetary Policy and Economic Impact (12 papers). Stefano Grassi is often cited by papers focused on Financial Risk and Volatility Modeling (19 papers), Complex Systems and Time Series Analysis (17 papers) and Monetary Policy and Economic Impact (12 papers). Stefano Grassi collaborates with scholars based in Italy, United Kingdom and Denmark. Stefano Grassi's co-authors include Leopoldo Catania, Francesco Ravazzolo, Paolo Santucci de Magistris, Herman K. van Dijk, Tommaso Proietti, Roberto Casarin, Nalan Baştürk, Alfredo De Massis, Ivan Miroshnychenko and Elena Stanghellini and has published in prestigious journals such as Proceedings of the National Academy of Sciences, International Journal of Cancer and Journal of Econometrics.

In The Last Decade

Stefano Grassi

41 papers receiving 464 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Stefano Grassi Italy	13	310	170	128	111	85	51	481
Cathy Yi‐Hsuan Chen Germany	11	282 0.9×	222 1.3×	114 0.9×	66 0.6×	53 0.6×	37	449
Michael Hanke Liechtenstein	13	221 0.7×	271 1.6×	25 0.2×	134 1.2×	70 0.8×	52	478
Markus Rudolf Germany	10	239 0.8×	274 1.6×	59 0.5×	121 1.1×	50 0.6×	43	537
Sergio Pastorello Italy	11	282 0.9×	200 1.2×	58 0.5×	192 1.7×	89 1.0×	26	638
Rand Kwong Yew Low Australia	11	305 1.0×	309 1.8×	21 0.2×	116 1.0×	79 0.9×	30	480
Keven Bluteau Canada	10	741 2.4×	471 2.8×	136 1.1×	108 1.0×	132 1.6×	25	928
Pilar Grau Carles Spain	13	243 0.8×	138 0.8×	30 0.2×	41 0.4×	18 0.2×	33	537
Anna Chernobai United States	14	274 0.9×	321 1.9×	139 1.1×	105 0.9×	30 0.4×	25	760
Nikola Gradojević Canada	18	645 2.1×	447 2.6×	115 0.9×	299 2.7×	143 1.7×	52	894
Gil Cohen Israel	12	234 0.8×	182 1.1×	50 0.4×	135 1.2×	43 0.5×	87	590

Countries citing papers authored by Stefano Grassi

Since Specialization

Citations

This map shows the geographic impact of Stefano Grassi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stefano Grassi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Grassi more than expected).

Fields of papers citing papers by Stefano Grassi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stefano Grassi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stefano Grassi. The network helps show where Stefano Grassi may publish in the future.

Co-authorship network of co-authors of Stefano Grassi

This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Grassi. A scholar is included among the top collaborators of Stefano Grassi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stefano Grassi. Stefano Grassi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Grassi, Stefano, et al.. (2025). Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach. Journal of commodity markets. 40. 100502–100502.

2.

Grassi, Stefano & Francesco Violante. (2025). Generalized Autoregressive Conditional Betas: Longitudinal Feedback in Multifactor Asset Pricing. Journal of Business and Economic Statistics. 43(4). 1132–1144.

3.

Buccheri, Giuseppe, et al.. (2023). Estimating Risk in Illiquid Markets: A Model of Market Friction with Stochastic Volatility. Journal of Financial Econometrics. 22(2). 531–574.

4.

Miroshnychenko, Ivan, et al.. (2023). The COVID-19 pandemic and family business performance. Small Business Economics. 62(1). 213–241. 31 indexed citations

5.

Belotti, Federico, et al.. (2023). Simultaneous bandwidths determination for DK-HAC estimators and long-run variance estimation in nonparametric settings. Econometric Reviews. 42(3). 281–306. 3 indexed citations

6.

Colladon, Andrea Fronzetti, Stefano Grassi, Francesco Ravazzolo, & Francesco Violante. (2022). Forecasting financial markets with semantic network analysis in the COVID-19 crisis. View. 5 indexed citations

7.

Miroshnychenko, Ivan, et al.. (2021). Family Influence and Firm Performance: Evidence from the Covid-19 pandemic. Academy of Management Proceedings. 2021(1). 15047–15047. 1 indexed citations

8.

Baştürk, Nalan, et al.. (2018). Forecast density combinations of dynamic models and data driven portfolio strategies. Journal of Econometrics. 210(1). 170–186. 11 indexed citations

9.

Baştürk, Nalan & Stefano Grassi. (2016). Time-Varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies. SSRN Electronic Journal. 5 indexed citations

10.

Ferroni, Filippo, Stefano Grassi, & Miguel A. León‐Ledesma. (2015). Fundamental shock selection in DSGE models. Econstor (Econstor). 3 indexed citations

11.

Baştürk, Nalan, Stefano Grassi, Lennart F. Hoogerheide, Anne Opschoor, & H. K. van Dijk. (2015). The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference. SSRN Electronic Journal. 1 indexed citations

12.

Nicolosi, Marco, Stefano Grassi, & Elena Stanghellini. (2014). Item Response Models to Measure Corporate Social Responsibility. SSRN Electronic Journal. 1 indexed citations

13.

Casarin, Roberto, Stefano Grassi, Francesco Ravazzolo, & Herman K. van Dijk. (2013). Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox. SSRN Electronic Journal. 2 indexed citations

14.

Casarin, Roberto, Stefano Grassi, Francesco Ravazzolo, & Herman K. van Dijk. (2013). Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox. SSRN Electronic Journal. 4 indexed citations

15.

Nicolosi, Marco, Stefano Grassi, & Elena Stanghellini. (2011). How to Measure Corporate Social Responsibility. RePEc: Research Papers in Economics. 96. 3 indexed citations

16.

Grassi, Stefano & Tommaso Proietti. (2010). Has the Volatility of U.S. Inflation Changed and How?. Kent Academic Repository (University of Kent). 2(1). 13 indexed citations

17.

Cangi, Maria Giulia, Sara Piccinin, Lorenza Pecciarini, et al.. (2008). Constitutive overexpression of CDC25A in primary human mammary epithelial cells results in both defective DNA damage response and chromosomal breaks at fragile sites. International Journal of Cancer. 123(6). 1466–1471. 14 indexed citations

18.

Biondi, Andrea, et al.. (2003). Scientific evidence in European environmental rule-making : the case of the landfill and end-of-life vehicles directives. Florence Research (University of Florence). 1.

19.

Grassi, Stefano & Andrea Gragnani. (2003). IL PRINCIPIO DI PRECAUZIONE NELLA GIURISPRUDENZA COSTITUZIONALE. Florence Research (University of Florence). 149–169.

20.

Grassi, Stefano, et al.. (2002). Istituzioni di diritto pubblico. CEDAM eBooks. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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