Miguel de Carvalho

659 total citations
43 papers, 349 citations indexed

About

Miguel de Carvalho is a scholar working on Statistics and Probability, Finance and Economics and Econometrics. According to data from OpenAlex, Miguel de Carvalho has authored 43 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistics and Probability, 14 papers in Finance and 11 papers in Economics and Econometrics. Recurrent topics in Miguel de Carvalho's work include Financial Risk and Volatility Modeling (13 papers), Statistical Methods and Inference (10 papers) and Statistical and numerical algorithms (8 papers). Miguel de Carvalho is often cited by papers focused on Financial Risk and Volatility Modeling (13 papers), Statistical Methods and Inference (10 papers) and Statistical and numerical algorithms (8 papers). Miguel de Carvalho collaborates with scholars based in United Kingdom, Portugal and Chile. Miguel de Carvalho's co-authors include António Rua, Paulo Canas Rodrigues, Daniela Castro‐Camilo, A. C. Davison, Timothy Hanson, Alejandro Jara, Filipe J. Marques, Jennifer L. Wadsworth, Adam J. Branscum and Todd A. Alonzo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Miguel de Carvalho

39 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Miguel de Carvalho United Kingdom 11 122 86 86 68 68 43 349
Reg Kulperger Canada 12 116 1.0× 225 2.6× 43 0.5× 65 1.0× 102 1.5× 45 479
Taoufik Bouezmarni Canada 13 270 2.2× 174 2.0× 151 1.8× 15 0.2× 79 1.2× 35 467
Eckhard Liebscher Germany 10 309 2.5× 229 2.7× 125 1.5× 24 0.4× 52 0.8× 37 518
Alejandro Quintela-del-Rı́o Spain 12 215 1.8× 82 1.0× 88 1.0× 18 0.3× 53 0.8× 46 374
Yingxing Li China 9 189 1.5× 83 1.0× 74 0.9× 20 0.3× 90 1.3× 33 412
Clément Dombry France 12 99 0.8× 191 2.2× 44 0.5× 14 0.2× 61 0.9× 47 419
Zhibiao Zhao United States 9 237 1.9× 146 1.7× 59 0.7× 15 0.2× 82 1.2× 25 392
Victoria Zinde‐Walsh Canada 12 218 1.8× 150 1.7× 47 0.5× 22 0.3× 154 2.3× 37 421
Marie Kratz France 11 65 0.5× 212 2.5× 22 0.3× 36 0.5× 139 2.0× 46 440
Tertius de Wet South Africa 14 343 2.8× 246 2.9× 69 0.8× 24 0.4× 59 0.9× 58 545

Countries citing papers authored by Miguel de Carvalho

Since Specialization
Citations

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

Fields of papers citing papers by Miguel de Carvalho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel de Carvalho. 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 Miguel de Carvalho. The network helps show where Miguel de Carvalho may publish in the future.

Co-authorship network of co-authors of Miguel de Carvalho

This figure shows the co-authorship network connecting the top 25 collaborators of Miguel de Carvalho. A scholar is included among the top collaborators of Miguel de Carvalho 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 Miguel de Carvalho. Miguel de Carvalho 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.
Tankişi, Hatice, Kirsten Pugdahl, Birger Johnsen, et al.. (2025). Electrodiagnostic criteria for neuromuscular transmission disorders suggested by a European consensus group. Clinical Neurophysiology Practice. 10. 79–83. 1 indexed citations
2.
Carvalho, Miguel de, et al.. (2024). Semiparametric Bayesian modelling of nonstationary joint extremes: How do big tech’s extreme losses behave?. Journal of the Royal Statistical Society Series C (Applied Statistics). 74(2). 447–465.
3.
Carvalho, Miguel de, et al.. (2024). Heavy-Tailed NGG-Mixture Models. Bayesian Analysis. 20(4). 1 indexed citations
4.
Carvalho, Miguel de, et al.. (2024). Bayesian smoothing for time-varying extremal dependence. Journal of the Royal Statistical Society Series C (Applied Statistics). 73(3). 581–597. 3 indexed citations
5.
6.
Carvalho, Miguel de, et al.. (2022). Regression-type analysis for multivariate extreme values. Extremes. 25(4). 595–622. 3 indexed citations
7.
Carvalho, Miguel de, et al.. (2020). Modeling Interval Trendlines: Symbolic Singular Spectrum Analysis for\n Interval Time Series. arXiv (Cornell University). 6 indexed citations
8.
Carvalho, Miguel de, et al.. (2019). Technological improvements or climate change? Bayesian modeling of time-varying conformance to Benford’s Law. PLoS ONE. 14(4). e0213300–e0213300. 1 indexed citations
9.
Carvalho, Miguel de, et al.. (2018). Brexit: Tracking and disentangling the sentiment towards leaving the EU. International Journal of Forecasting. 36(3). 1128–1137. 2 indexed citations
10.
Carvalho, Miguel de & António Rua. (2016). Real-time nowcasting the US output gap: Singular spectrum analysis at work. International Journal of Forecasting. 33(1). 185–198. 29 indexed citations
11.
Castro‐Camilo, Daniela & Miguel de Carvalho. (2016). Spectral density regression for bivariate extremes. Stochastic Environmental Research and Risk Assessment. 31(7). 1603–1613. 12 indexed citations
12.
Carvalho, Miguel de & A. C. Davison. (2014). Spectral Density Ratio Models for Multivariate Extremes. Journal of the American Statistical Association. 109(506). 764–776. 25 indexed citations
13.
Jara, Alejandro, et al.. (2013). Bayesian Nonparametric ROC Regression Modeling. Bayesian Analysis. 8(3). 39 indexed citations
14.
Carvalho, Miguel de & António Rua. (2013). Extremal Dependence in International Output Growth: Tales from the Tails. Oxford Bulletin of Economics and Statistics. 76(4). 605–620. 2 indexed citations
15.
Carvalho, Miguel de, K. F. Turkman, & António Rua. (2013). Dynamic Threshold Modelling and the US Business Cycle. Journal of the Royal Statistical Society Series C (Applied Statistics). 62(4). 535–550. 3 indexed citations
16.
Carvalho, Miguel de, et al.. (2013). Leadership and commitment on Portuguese Rugby National Team. International Journal of Academic Research. 5(2). 187–191. 1 indexed citations
17.
Rodrigues, Paulo Canas & Miguel de Carvalho. (2012). Spectral modeling of time series with missing data. Applied Mathematical Modelling. 37(7). 4676–4684. 21 indexed citations
18.
Carvalho, Miguel de, Paulo Canas Rodrigues, & António Rua. (2011). Tracking the US business cycle with a singular spectrum analysis. Economics Letters. 114(1). 32–35. 37 indexed citations
19.
Carvalho, Miguel de. (2011). Confidence intervals for the minimum of a function using extreme value statistics. International Journal of Mathematical Modelling and Numerical Optimisation. 2(3). 288–288. 4 indexed citations
20.
Carvalho, Miguel de, et al.. (2010). Digging out the PPP hypothesis: an integrated empirical coverage. Empirical Economics. 42(3). 713–744. 6 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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