Michel van der Wel

837 total citations
32 papers, 363 citations indexed

About

Michel van der Wel is a scholar working on Finance, General Economics, Econometrics and Finance and Economics and Econometrics. According to data from OpenAlex, Michel van der Wel has authored 32 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Finance, 17 papers in General Economics, Econometrics and Finance and 13 papers in Economics and Econometrics. Recurrent topics in Michel van der Wel's work include Monetary Policy and Economic Impact (17 papers), Stochastic processes and financial applications (15 papers) and Financial Risk and Volatility Modeling (13 papers). Michel van der Wel is often cited by papers focused on Monetary Policy and Economic Impact (17 papers), Stochastic processes and financial applications (15 papers) and Financial Risk and Volatility Modeling (13 papers). Michel van der Wel collaborates with scholars based in Netherlands, United States and Denmark. Michel van der Wel's co-authors include Siem Jan Koopman, Dick van Dijk, Borus Jungbacker, Anne Opschoor, Albert J. Menkveld, Jonathan H. Wright, Asani Sarkar, Bent Jesper Christensen, Nick Taylor and Richard Paap and has published in prestigious journals such as Journal of Financial Economics, The Economic Journal and Journal of Econometrics.

In The Last Decade

Michel van der Wel

31 papers receiving 353 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michel van der Wel Netherlands 10 283 176 164 28 21 32 363
Fulvio Pegoraro France 16 397 1.4× 241 1.4× 247 1.5× 15 0.5× 10 0.5× 31 526
Ken Nyholm Germany 10 297 1.0× 164 0.9× 134 0.8× 21 0.8× 13 0.6× 29 362
Bruno Feunou Canada 12 592 2.1× 400 2.3× 137 0.8× 33 1.2× 16 0.8× 47 656
Florian Ielpo France 12 278 1.0× 292 1.7× 108 0.7× 18 0.6× 10 0.5× 46 417
Julio Cacho-Diaz Netherlands 2 245 0.9× 155 0.9× 44 0.3× 22 0.8× 9 0.4× 2 341
Sophie A. Ladoucette Belgium 7 97 0.3× 111 0.6× 85 0.5× 46 1.6× 33 1.6× 12 215
K. Ben Nowman United Kingdom 13 507 1.8× 240 1.4× 370 2.3× 45 1.6× 22 1.0× 39 644
Loriano Mancini Switzerland 9 518 1.8× 271 1.5× 99 0.6× 31 1.1× 30 1.4× 23 559
Ke‐Li Xu United States 10 202 0.7× 127 0.7× 108 0.7× 23 0.8× 118 5.6× 36 301
Dobrislav Dobrev United States 9 640 2.3× 534 3.0× 194 1.2× 66 2.4× 30 1.4× 21 735

Countries citing papers authored by Michel van der Wel

Since Specialization
Citations

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

Fields of papers citing papers by Michel van der Wel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michel van der Wel. 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 Michel van der Wel. The network helps show where Michel van der Wel may publish in the future.

Co-authorship network of co-authors of Michel van der Wel

This figure shows the co-authorship network connecting the top 25 collaborators of Michel van der Wel. A scholar is included among the top collaborators of Michel van der Wel 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 Michel van der Wel. Michel van der Wel 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.
Wel, Michel van der, et al.. (2024). A Smooth Shadow-Rate Dynamic Nelson-Siegel Model for Yields at the Zero Lower Bound. Journal of Business and Economic Statistics. 43(2). 298–311.
2.
Kole, Erik, et al.. (2024). Heterogeneous macro and financial effects of ECB asset purchase programs. Journal of International Money and Finance. 143. 103073–103073. 2 indexed citations
3.
Wel, Michel van der, et al.. (2022). A Smooth Shadow-Rate Dynamic Nelson-Siegel Model for Yields at the Zero Lower Bound. SSRN Electronic Journal. 1 indexed citations
4.
Kole, Erik, et al.. (2021). Heterogeneous Macro and Financial Effects of ECB Asset Purchase Programs. SSRN Electronic Journal. 1 indexed citations
5.
Wel, Michel van der & Yaoyuan Zhang. (2021). Global Evidence on Unspanned Macro Risks in Dynamic Term Structure Models. SSRN Electronic Journal. 1 indexed citations
6.
Christensen, Bent Jesper & Michel van der Wel. (2019). An asset pricing approach to testing general term structure models. Journal of Financial Economics. 134(1). 165–191. 5 indexed citations
7.
Paap, Richard, et al.. (2018). What do professional forecasters actually predict?. International Journal of Forecasting. 34(2). 288–311. 1 indexed citations
8.
Wel, Michel van der, et al.. (2017). Intraday price discovery in fragmented markets. Data Archiving and Networked Services (DANS). 27 indexed citations
9.
Christensen, Bent Jesper, et al.. (2016). Estimating dynamic equilibrium models using mixed frequency macro and financial data. Journal of Econometrics. 194(1). 116–137. 4 indexed citations
10.
Wel, Michel van der, et al.. (2015). Common Factors in Commodity Futures Curves. SSRN Electronic Journal. 10 indexed citations
11.
Paap, Richard, et al.. (2015). What Do Professional Forecasters Actually Predict?. SSRN Electronic Journal. 1 indexed citations
12.
Opschoor, Anne, Dick van Dijk, & Michel van der Wel. (2014). Improving Density Forecasts and Value-at- \nRisk Estimates by Combining Densities. Data Archiving and Networked Services (DANS). 3 indexed citations
13.
Wel, Michel van der, et al.. (2014). Intraday Price Discovery in Fragmented Markets. SSRN Electronic Journal. 1 indexed citations
14.
Dijk, Dick van, Siem Jan Koopman, Michel van der Wel, & Jonathan H. Wright. (2013). Forecasting interest rates with shifting endpoints. Journal of Applied Econometrics. 29(5). 693–712. 38 indexed citations
15.
Koopman, Siem Jan & Michel van der Wel. (2013). Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model. International Journal of Forecasting. 29(4). 676–694. 17 indexed citations
16.
Dijk, Dick van, Siem Jan Koopman, Michel van der Wel, & Jonathan H. Wright. (2012). Forecasting Interest Rates with Shifting Endpoints. SSRN Electronic Journal. 2 indexed citations
17.
Pan, Lei, et al.. (2012). Measuring Convergence Using Dynamic Equilibrium Models: Evidence from Chinese Provinces. SSRN Electronic Journal. 1 indexed citations
18.
Christensen, Bent Jesper & Michel van der Wel. (2010). An Asset Pricing Approach to Testing General Term Structure Models Including Heath-Jarrow-Morton Specifications and Affine Subclasses. SSRN Electronic Journal. 2 indexed citations
19.
Wel, Michel van der, Albert J. Menkveld, & Asani Sarkar. (2009). Are Market Makers Uninformed and Passive? Signing Trades in the Absence of Quotes. SSRN Electronic Journal. 3 indexed citations
20.
Koopman, Siem Jan, et al.. (2008). Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson-Siegel Model with Time-Varying Parameters. SSRN Electronic Journal. 32 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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