Massimo Guidolin

5.9k total citations
165 papers, 3.3k citations indexed

About

Massimo Guidolin is a scholar working on Finance, Economics and Econometrics and General Economics, Econometrics and Finance. According to data from OpenAlex, Massimo Guidolin has authored 165 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 142 papers in Finance, 103 papers in Economics and Econometrics and 57 papers in General Economics, Econometrics and Finance. Recurrent topics in Massimo Guidolin's work include Financial Markets and Investment Strategies (105 papers), Monetary Policy and Economic Impact (54 papers) and Financial Risk and Volatility Modeling (41 papers). Massimo Guidolin is often cited by papers focused on Financial Markets and Investment Strategies (105 papers), Monetary Policy and Economic Impact (54 papers) and Financial Risk and Volatility Modeling (41 papers). Massimo Guidolin collaborates with scholars based in Italy, United Kingdom and United States. Massimo Guidolin's co-authors include Allan Timmermann, Eliana La Ferrara, Francesca Romana Rinaldi, Simona Mola, Śılvia Gonçalves, Stuart Hyde, Giovanna Nicodano, Daniele Bianchi, David G. McMillan and Daniel L. Thornton and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Financial Economics and American Economic Review.

In The Last Decade

Massimo Guidolin

159 papers receiving 3.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Massimo Guidolin Italy 26 2.4k 2.1k 956 485 390 165 3.3k
Michael Weber United States 30 1.8k 0.8× 2.2k 1.1× 1.4k 1.5× 970 2.0× 334 0.9× 185 3.6k
Stephen F. LeRoy United States 24 1.9k 0.8× 2.7k 1.3× 1.4k 1.4× 525 1.1× 264 0.7× 68 3.6k
Nelson C. Mark United States 32 2.6k 1.1× 3.6k 1.7× 3.1k 3.3× 374 0.8× 223 0.6× 66 4.8k
Tarun Ramadorai United Kingdom 29 2.6k 1.1× 2.3k 1.1× 695 0.7× 1.6k 3.4× 153 0.4× 96 3.7k
Narayana Kocherlakota United States 32 1.6k 0.7× 3.9k 1.9× 1.9k 2.0× 1.2k 2.4× 247 0.6× 84 4.6k
Rossen Valkanov United States 26 3.7k 1.5× 3.5k 1.7× 1.7k 1.8× 745 1.5× 718 1.8× 59 5.0k
Christos Floros Greece 27 1.5k 0.6× 2.3k 1.1× 674 0.7× 914 1.9× 289 0.7× 132 3.1k
Amir Yaron United States 27 3.1k 1.3× 3.6k 1.7× 1.8k 1.9× 1.3k 2.6× 194 0.5× 52 5.2k
Sunil Sharma United States 18 1.3k 0.5× 1.2k 0.6× 618 0.6× 404 0.8× 207 0.5× 56 2.1k
Robert Whitelaw United States 28 4.0k 1.7× 2.7k 1.3× 752 0.8× 1.4k 3.0× 574 1.5× 63 4.6k

Countries citing papers authored by Massimo Guidolin

Since Specialization
Citations

This map shows the geographic impact of Massimo Guidolin'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 Massimo Guidolin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Guidolin more than expected).

Fields of papers citing papers by Massimo Guidolin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Guidolin. 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 Massimo Guidolin. The network helps show where Massimo Guidolin may publish in the future.

Co-authorship network of co-authors of Massimo Guidolin

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Guidolin. A scholar is included among the top collaborators of Massimo Guidolin 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 Massimo Guidolin. Massimo Guidolin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Guidolin, Massimo, et al.. (2024). Strong vs. stable: the impact of ESG ratings momentum and their volatility on the cost of equity capital. Journal of Asset Management. 25(7). 666–699. 1 indexed citations
2.
Guidolin, Massimo, et al.. (2024). Do US Active Mutual Funds Make Good of Their ESG Promises? Evidence from Portfolio Holdings. Risks. 12(2). 41–41. 1 indexed citations
3.
Guidolin, Massimo, et al.. (2023). Strong vs. Stable: The Impact of ESG Ratings Momentum and Their Volatility on the Cost of Equity Capital. SSRN Electronic Journal. 3 indexed citations
4.
Guidolin, Massimo, et al.. (2023). New ESG rating drivers in the cross‐section of European stock returns. The Journal of Financial Research. 46(S1). 4 indexed citations
5.
Guidolin, Massimo, et al.. (2021). Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit. BOA (University of Milano-Bicocca). 7 indexed citations
6.
Bianchi, Daniele, Monica Billio, Roberto Casarin, & Massimo Guidolin. (2019). Modeling Systemic Risk with Markov Switching Graphical SUR Models. ARCA (Università Ca' Foscari Venezia). 39 indexed citations
7.
Guidolin, Massimo, et al.. (2018). Comparing in- and out-of-sample approaches to variance decomposition-based estimates of network connectedness an application to the Italian banking system. SHILAP Revista de lepidopterología. 2(3). 661–701. 4 indexed citations
8.
Guidolin, Massimo, et al.. (2017). Volatility as an Alternative Asset Class: Does It Improve Portfolio Performance?. SHILAP Revista de lepidopterología. 1(4). 334–362. 2 indexed citations
9.
Guidolin, Massimo, et al.. (2016). Transmission Channels of Financial Shocks to Stock, Bond, and Asset-Backed Markets: An Empirical Model. Palgrave Macmillan UK eBooks. 1 indexed citations
10.
Guidolin, Massimo, et al.. (2016). Ambiguity Aversion and Underdiversification. Research Explorer (The University of Manchester). 20 indexed citations
11.
Guidolin, Massimo, et al.. (2016). An empirical analysis of changes in the relative timeliness of issuer-paid vs. investor-paid ratings. Journal of Corporate Finance. 59. 88–118. 18 indexed citations
12.
Guidolin, Massimo, et al.. (2014). Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests. Universidad de Chile. 35 indexed citations
13.
Bianchi, Daniele, Massimo Guidolin, & Francesco Ravazzolo. (2013). Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section. SSRN Electronic Journal. 5 indexed citations
14.
Guidolin, Massimo, et al.. (2010). Does the Macroeconomy Predict U.K. Asset Returns in a Nonlinear Fashion? Comprehensive Out-of-Sample Evidence. SSRN Electronic Journal. 4 indexed citations
15.
Guidolin, Massimo, et al.. (2010). Ex Post Portfolio Performance with Predictable Skewness and Kurtosis. RePEc: Research Papers in Economics. 1–67.
16.
Guidolin, Massimo & Eliana La Ferrara. (2010). The economic effects of violent conflict: Evidence from asset market reactions. Journal of Peace Research. 47(6). 671–684. 138 indexed citations
17.
Guidolin, Massimo & Stuart Hyde. (2009). What tames the Celtic Tiger? Portfolio implications from a Multivariate Markov Switching model. Applied Financial Economics. 19(6). 463–488. 6 indexed citations
18.
Guidolin, Massimo. (2008). Asset Pricing and Portfolio Choice. 85(11). 5724–5727. 6 indexed citations
19.
Timmermann, Allan & Massimo Guidolin. (2004). Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns. SSRN Electronic Journal. 22 indexed citations
20.
Guidolin, Massimo & Allan Timmermann. (2003). Economic Implications of Bull and Bear Regimes in UK Stock Returns. RePEc: Research Papers in Economics. 5 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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