Madhu Veeraraghavan

3.1k total citations
112 papers, 2.0k citations indexed

About

Madhu Veeraraghavan is a scholar working on Accounting, Finance and Economics and Econometrics. According to data from OpenAlex, Madhu Veeraraghavan has authored 112 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Accounting, 76 papers in Finance and 35 papers in Economics and Econometrics. Recurrent topics in Madhu Veeraraghavan's work include Corporate Finance and Governance (71 papers), Financial Markets and Investment Strategies (70 papers) and Auditing, Earnings Management, Governance (33 papers). Madhu Veeraraghavan is often cited by papers focused on Corporate Finance and Governance (71 papers), Financial Markets and Investment Strategies (70 papers) and Auditing, Earnings Management, Governance (33 papers). Madhu Veeraraghavan collaborates with scholars based in Australia, India and United States. Madhu Veeraraghavan's co-authors include Yangyang Chen, Edward Podolski, Cameron Truong, S. Ghon Rhee, Michael E. Drew, Leon Zolotoy, Philip Gharghori, Abhinav Goyal, Tony Naughton and Ferdinand A. Gul and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Financial Economics and Management Science.

In The Last Decade

Madhu Veeraraghavan

103 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Madhu Veeraraghavan Australia 22 1.4k 927 708 456 135 112 2.0k
Andy C.W. Chui Hong Kong 15 1.2k 0.8× 1.2k 1.3× 811 1.1× 329 0.7× 152 1.1× 28 1.9k
P. Eric Yeung United States 19 1.8k 1.3× 764 0.8× 538 0.8× 632 1.4× 73 0.5× 48 2.1k
Lubomir P. Litov United States 20 2.4k 1.7× 1.3k 1.4× 823 1.2× 759 1.7× 84 0.6× 53 2.9k
Markku Kaustia Finland 16 1.1k 0.8× 1.1k 1.2× 924 1.3× 183 0.4× 138 1.0× 39 1.8k
Jens Hagendorff United Kingdom 22 1.8k 1.3× 1.0k 1.1× 579 0.8× 493 1.1× 40 0.3× 67 2.3k
Gregor Matvos United States 19 1.3k 1.0× 1.5k 1.6× 1.4k 2.0× 317 0.7× 81 0.6× 48 2.7k
Scott E. Yonker United States 16 1.9k 1.4× 854 0.9× 763 1.1× 524 1.1× 49 0.4× 28 2.5k
Angie Low Singapore 15 2.3k 1.7× 775 0.8× 866 1.2× 824 1.8× 64 0.5× 35 2.9k
Joshua Matthew Pollet United States 16 1.2k 0.9× 1.5k 1.6× 753 1.1× 207 0.5× 179 1.3× 34 2.0k
Denis Sosyura United States 16 1.7k 1.2× 1.3k 1.5× 722 1.0× 605 1.3× 100 0.7× 32 2.4k

Countries citing papers authored by Madhu Veeraraghavan

Since Specialization
Citations

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

Fields of papers citing papers by Madhu Veeraraghavan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Madhu Veeraraghavan

This figure shows the co-authorship network connecting the top 25 collaborators of Madhu Veeraraghavan. A scholar is included among the top collaborators of Madhu Veeraraghavan 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 Madhu Veeraraghavan. Madhu Veeraraghavan 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.
Chen, Yangyang, Po‐Hsuan Hsu, Edward Podolski, & Madhu Veeraraghavan. (2024). In the mood for creativity: Sunshine-induced mood, inventor performance, and firm value. Journal of Empirical Finance. 78. 101527–101527.
2.
Ranganathan, Kavitha & Madhu Veeraraghavan. (2023). Pre-and-aftermarket IPO underpricing: Does use of proceeds disclosure matter?. Journal of Contemporary Accounting & Economics. 19(3). 100379–100379. 4 indexed citations
3.
Chen, Yangyang, Po‐Hsuan Hsu, Aleksandra Kacperczyk, Edward Podolski, & Madhu Veeraraghavan. (2019). The Extra-Organizational Determinants of Innovation: Sunshine Exposure and Inventor Performance. SSRN Electronic Journal. 2 indexed citations
4.
Chen, Yangyang, Po‐Hsuan Hsu, Edward Podolski, & Madhu Veeraraghavan. (2016). In the Mood for Creativity: Sunshine-Induced Mood, Inventor Performance, and Firm Value. SSRN Electronic Journal. 2 indexed citations
5.
Chen, Yangyang, Ferdinand A. Gul, Madhu Veeraraghavan, & Leon Zolotoy. (2015). Executive Equity Risk-Taking Incentives and Audit Pricing. The Accounting Review. 90(6). 2205–2234. 103 indexed citations
6.
Skully, Michael T., et al.. (2014). Is the accrual anomaly robust to firm-level analysis?. International Review of Financial Analysis. 34. 157–165. 3 indexed citations
7.
Gharghori, Philip, et al.. (2012). Value versus growth: Australian evidence. Accounting and Finance. 53(2). 393–417. 15 indexed citations
8.
Hunton, James E., et al.. (2010). Individualism, Uncertainty Avoidance, and Earnings Momentum in International Markets. SSRN Electronic Journal. 4 indexed citations
10.
Clements, Adam, et al.. (2009). The death of the overreaction anomaly? A multifactor explanation of contrarian returns. Investment Management and Financial Innovations. 6(1). 76–85. 20 indexed citations
11.
Marsden, Alastair, et al.. (2008). Heuristics of representativeness, anchoring and adjustment, and leniency: Impact on earnings' forecasts by Australian analysts. ResearchSpace (University of Auckland). 47(2). 83–102. 7 indexed citations
12.
Dempsey, Michael, et al.. (2008). Are company size and stock beta, liquidity and idiosyncratic volatility related to stock returns? Australian evidence. SHILAP Revista de lepidopterología. 2 indexed citations
13.
Drew, Michael E., Alastair Marsden, & Madhu Veeraraghavan. (2007). Does Idiosyncratic Volatility Matter? New Zealand Evidence. Review of Pacific Basin Financial Markets and Policies. 10(3). 289–308. 16 indexed citations
14.
Gharghori, Philip, Ronald Lee, & Madhu Veeraraghavan. (2007). Anomalies and Stock Returns: Australian Evidence. SSRN Electronic Journal. 14 indexed citations
15.
Veeraraghavan, Madhu, et al.. (2006). Firm size, beta and stock returns: Evidence from Germany and the United Kingdom. 1(1). 107–123. 1 indexed citations
16.
Drew, Michael E., et al.. (2005). Market Timing, Selectivity And Alpha Generation: Evidence From Australian Equity Superannuation Funds. SHILAP Revista de lepidopterología. 6 indexed citations
17.
Veeraraghavan, Madhu, et al.. (2005). A multifactor model explanation of the cross-section of expected stock returns: Evidence from Indonesia, Singapore and Taiwan. RMIT Research Repository (RMIT University Library).
18.
Veeraraghavan, Madhu, et al.. (2004). On the robustness of the Fama and French multifactor model: Evidence from France, Germany and United Kingdom. RePEc: Research Papers in Economics. 3(2). 155–176. 29 indexed citations
19.
Ye, Min, Madhu Veeraraghavan, & Michael E. Drew. (2004). Do Momentum Strategies Work?: - Australian Evidence, Discussion Paper No 169. QUT Business School. 1 indexed citations
20.
Drew, Michael E. & Madhu Veeraraghavan. (2003). Beta, Firm Size, Book-to-Market Equity and Stock Returns: Further Evidence from Emerging Markets. QUT Business School. 1 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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