Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Value and Momentum Everywhere
20131.5k citationsClifford S. Asness, Tobias J. Moskowitz et al.The Journal of Financeprofile →
Quality minus junk
2018306 citationsClifford S. Asness, Andrea Frazzini et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Clifford S. Asness
Since
Specialization
Citations
This map shows the geographic impact of Clifford S. Asness'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 Clifford S. Asness with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clifford S. Asness more than expected).
Fields of papers citing papers by Clifford S. Asness
This network shows the impact of papers produced by Clifford S. Asness. 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 Clifford S. Asness. The network helps show where Clifford S. Asness may publish in the future.
Co-authorship network of co-authors of Clifford S. Asness
This figure shows the co-authorship network connecting the top 25 collaborators of Clifford S. Asness.
A scholar is included among the top collaborators of Clifford S. Asness 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 Clifford S. Asness. Clifford S. Asness 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.
Asness, Clifford S., et al.. (2018). Buyback Derangement Syndrome. The Journal of Portfolio Management. 44(5). 50–57.13 indexed citations
2.
Asness, Clifford S., Andrea Frazzini, Ronen Israel, & Tobias J. Moskowitz. (2015). Fact, Fiction, and Value Investing. SSRN Electronic Journal.12 indexed citations
3.
Asness, Clifford S.. (2014). My Top 10 Peeves. Financial Analysts Journal. 70(1). 22–30.8 indexed citations
4.
Asness, Clifford S., Andrea Frazzini, Ronen Israel, & Tobias J. Moskowitz. (2014). Fact, Fiction, and Momentum Investing. The Journal of Portfolio Management. 40(5). 75–92.68 indexed citations
5.
Asness, Clifford S., Tobias J. Moskowitz, & Lasse Heje Pedersen. (2013). Value and Momentum Everywhere. The Journal of Finance. 68(3). 929–985.1464 indexed citations breakdown →
6.
Asness, Clifford S. & Andrea Frazzini. (2013). The Devil in HML’s Details. The Journal of Portfolio Management. 39(4). 49–68.235 indexed citations
Asness, Clifford S., et al.. (2001). Do Hedge Funds Hedge?. The Journal of Portfolio Management. 28(1). 6–19.326 indexed citations
18.
Asness, Clifford S.. (1998). The Interaction of Value and Momentum Strategies. SSRN Electronic Journal.22 indexed citations
19.
Asness, Clifford S., John M. Liew, & Ross L. Stevens. (1996). Parallels between the Cross-Sectional Predictability of Stock and Country Returns. SSRN Electronic Journal.21 indexed citations
20.
Asness, Clifford S.. (1994). Variables that explain stock returns : simulated and empirical evidence. UMI eBooks.27 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.