Mark Salmon

2.3k citations
66 papers · 1.0k · h-index 17

Impact in

Papers in

    • Complex Systems and Time Series Analysis 11
    • Market Dynamics and Volatility 10
    • Economic theories and models 9
    • Financial Markets and Investment Strategies 15
    • Financial Risk and Volatility Modeling 10

Mark Salmon

64 papers receiving 913 citations

Peers

Mark Salmon
Comparison fields: 5 of 114
  • Finance 396
  • General Economics, Econometrics and Finance 288
  • Economics and Econometrics 520
  • Statistics and Probability 92
  • Health Informatics 13
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Citations per field
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Citations per year

Countries citing papers authored by Mark Salmon

Since Specialization
Citations

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

Fields of papers citing papers by Mark Salmon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mark Salmon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Salmon Line = papers co-authored together Mark Salmon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1982108
2
Learning and Rationality in Economics
1995105
3 198397
4 200983
5 202176
6
SENTIMENT AND BETA HERDING
200634
7 201829
8 202028
9 201127
10 200325
11 198623
12 200422
13 200721
14 199620
15 201219
16 199219
17 200917
18 199316
19 200215
20 200815

About Mark Salmon

Mark Salmon is a scholar working on Economics and Econometrics, Finance, General Economics, Econometrics and Finance, Management Science and Operations Research and Statistics and Probability, having authored 66 papers that have together received 1.0k indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (16 papers), Financial Markets and Investment Strategies (15 papers), Complex Systems and Time Series Analysis (11 papers), Market Dynamics and Volatility (10 papers), Financial Risk and Volatility Modeling (10 papers), Economic theories and models (9 papers), Stock Market Forecasting Methods (4 papers) and Advanced Statistical Methods and Models (4 papers). The work is most often cited by research in Finance (396 citations), General Economics, Econometrics and Finance (288 citations), Economics and Econometrics (520 citations), Statistics and Probability (92 citations) and Health Informatics (13 citations). Mark Salmon has collaborated with scholars based in United Kingdom, United States and South Korea. Frequent co-authors include Alan Kirman, Soosung Hwang, Éric Bouyé, Nicholas M. Kiefer, Roman Kozhan, Paul Marriott, Frank Critchley, Paul Fisher, Niels Haldrup and Christoph Schleicher. Their work appears in journals such as Journal of Economic Dynamics and Control, European Journal of Finance, Macroeconomic Dynamics, Digital Health and The Annals of Statistics.

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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