Debojyoti Das

2.6k total citations · 4 hit papers
44 papers, 2.1k citations indexed

About

Debojyoti Das is a scholar working on Economics and Econometrics, Information Systems and Finance. According to data from OpenAlex, Debojyoti Das has authored 44 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Economics and Econometrics, 8 papers in Information Systems and 6 papers in Finance. Recurrent topics in Debojyoti Das's work include Market Dynamics and Volatility (24 papers), Energy, Environment, Economic Growth (10 papers) and Blockchain Technology Applications and Security (8 papers). Debojyoti Das is often cited by papers focused on Market Dynamics and Volatility (24 papers), Energy, Environment, Economic Growth (10 papers) and Blockchain Technology Applications and Security (8 papers). Debojyoti Das collaborates with scholars based in India, United Kingdom and France. Debojyoti Das's co-authors include Rabin K. Jana, Anupam Dutta, M. Kannadhasan, Aviral Kumar Tiwari, David Roubaud, Malay Bhattacharyya, Surya Bhushan Kumar, Xuan Vinh Vo, Muhammad Shahbaz and Indranil Ghosh and has published in prestigious journals such as Journal of Cleaner Production, Tourism Management and Technological Forecasting and Social Change.

In The Last Decade

Debojyoti Das

40 papers receiving 2.0k citations

Hit Papers

Informational efficiency of Bitcoin—An extension 2017 2026 2020 2023 2017 2020 2019 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debojyoti Das India 20 1.8k 574 480 336 310 44 2.1k
Tony Klein United Kingdom 18 1.7k 0.9× 644 1.1× 564 1.2× 255 0.8× 295 1.0× 56 1.9k
Refk Selmi France 21 1.5k 0.8× 455 0.8× 341 0.7× 307 0.9× 333 1.1× 56 1.6k
Jamal Bouoiyour France 18 1.3k 0.7× 459 0.8× 337 0.7× 354 1.1× 289 0.9× 68 1.6k
Francisco Jareño Spain 25 2.1k 1.1× 418 0.7× 615 1.3× 406 1.2× 464 1.5× 97 2.3k
Emmanuel Joel Aikins Abakah Ghana 27 2.8k 1.5× 552 1.0× 913 1.9× 305 0.9× 605 2.0× 104 3.0k
Stephanos Papadamou Greece 24 1.9k 1.0× 436 0.8× 992 2.1× 661 2.0× 196 0.6× 110 2.3k
Mariya Gubareva Portugal 28 2.1k 1.2× 514 0.9× 708 1.5× 323 1.0× 319 1.0× 89 2.4k
Lee A. Smales Australia 25 1.9k 1.1× 436 0.8× 1.1k 2.2× 464 1.4× 144 0.5× 101 2.3k
Md Akhtaruzzaman Australia 19 2.1k 1.1× 357 0.6× 898 1.9× 197 0.6× 144 0.5× 40 2.3k
Muhammad Tahir Suleman New Zealand 27 1.9k 1.0× 204 0.4× 608 1.3× 457 1.4× 364 1.2× 90 2.3k

Countries citing papers authored by Debojyoti Das

Since Specialization
Citations

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

Fields of papers citing papers by Debojyoti Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debojyoti Das

This figure shows the co-authorship network connecting the top 25 collaborators of Debojyoti Das. A scholar is included among the top collaborators of Debojyoti Das 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 Debojyoti Das. Debojyoti Das 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
2.
Das, Debojyoti, et al.. (2024). Bis-arylidene oxindoles for colorectal cancer nanotherapy. Bioorganic Chemistry. 146. 107294–107294. 4 indexed citations
3.
Das, Debojyoti, et al.. (2023). A naphthalimide appended rhodamine based biocompatible fluorescent probe: Chemosensor for selective detection of Hg2+ ion, live cell imaging and DFT study. Journal of Photochemistry and Photobiology A Chemistry. 446. 115168–115168. 17 indexed citations
4.
Jana, Rabin K., Indranil Ghosh, Debojyoti Das, & Anupam Dutta. (2021). Determinants of electronic waste generation in Bitcoin network: Evidence from the machine learning approach. Technological Forecasting and Social Change. 173. 121101–121101. 25 indexed citations
5.
Jana, Rabin K., Indranil Ghosh, & Debojyoti Das. (2021). A differential evolution-based regression framework for forecasting Bitcoin price. Annals of Operations Research. 306(1-2). 295–320. 48 indexed citations
6.
Dutta, Anupam, Debojyoti Das, Rabin K. Jana, & Xuan Vinh Vo. (2020). COVID-19 and oil market crash: Revisiting the safe haven property of gold and Bitcoin. Resources Policy. 69. 101816–101816. 238 indexed citations breakdown →
7.
Das, Debojyoti, M. Kannadhasan, & Malay Bhattacharyya. (2020). Oil price shocks and emerging stock markets revisited. International Journal of Emerging Markets. 17(6). 1583–1614. 12 indexed citations
8.
Kannadhasan, M. & Debojyoti Das. (2019). Has Co-Movement Dynamics in Brazil, Russia, India, China and South Africa (BRICS) Markets Changed After Global Financial Crisis? New Evidence from Wavelet Analysis. Asian Academy of Management Journal of Accounting and Finance. 15(1). 1–25. 6 indexed citations
9.
Das, Debojyoti, et al.. (2019). Does Bitcoin hedge crude oil implied volatility and structural shocks? A comparison with gold, commodity and the US Dollar. Finance research letters. 36. 101335–101335. 134 indexed citations
10.
Das, Debojyoti & M. Kannadhasan. (2019). Emerging stock market co-movements in South Asia: wavelet approach. International Journal of Managerial Finance. 15(2). 236–256. 8 indexed citations
11.
Das, Debojyoti & M. Kannadhasan. (2018). Do global factors impact bitcoin prices?: evidence from wavelet approach. Journal of Economic Research (JER). 23(3). 227–264. 41 indexed citations
12.
Singh, Ritu, Debojyoti Das, Rabin K. Jana, & Aviral Kumar Tiwari. (2018). A wavelet analysis for exploring the relationship between economic policy uncertainty and tourist footfalls in the USA. Current Issues in Tourism. 22(15). 1789–1796. 49 indexed citations
13.
Tiwari, Aviral Kumar, Malay Bhattacharyya, Debojyoti Das, & Muhammad Shahbaz. (2018). Output and stock prices: New evidence from the robust wavelet approach. Finance research letters. 27. 154–160. 7 indexed citations
14.
Das, Debojyoti. (2018). The Politics of Swidden farming (Jhum). Anthem Press eBooks. 2 indexed citations
15.
Das, Debojyoti, et al.. (2017). Do precious metal spot prices influence each other? Evidence from a nonparametric causality-in-quantiles approach. Resources Policy. 55. 244–252. 55 indexed citations
16.
Das, Debojyoti. (2017). Tropical cyclones and coastal communities: the dialectics of social and environmental change in the Sundarban delta. Journal of the Indian Ocean Region. 13(2). 257–275. 5 indexed citations
17.
Das, Debojyoti, et al.. (2017). The relationship between oil prices and US economy revisited. Energy Sources Part B Economics Planning and Policy. 13(1). 37–45. 15 indexed citations
18.
19.
Das, Debojyoti, et al.. (2009). Anticonvulsant Activity of <I>Cleome rutidosperma</I> Linn. in Strychnine Induced Tonic Convulsion in Mice. Journal of Pharmaceutical Research. 8(1). 49–49. 1 indexed citations
20.
Das, Debojyoti. (2006). Demystifying the myth of shifting cultivation: agronomy in the north-east. Economic and political weekly. 41(47). 4912–4917. 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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