Everaldo GUEDES | Econometrics and Finance | Best Researcher Award

Prof. Dr. Everaldo GUEDES | Econometrics and Finance | Best Researcher Award

Professor from FIOCRUZ, Brazil

Dr. Everaldo Freitas Guedes is a distinguished Brazilian statistician and data scientist with a robust academic and professional background. He earned his Ph.D. and Master’s degrees in Computational Modeling and Industrial Technology from SENAI CIMATEC, following a Bachelor’s degree in Statistical Sciences from the Higher School of Statistics of Bahia and a Licentiate in Mathematics from the Faculty of Educational Sciences. Dr. Guedes has held various academic positions, including roles as a substitute professor at the Federal University of Recôncavo da Bahia and as a visiting professor at UNIASSELVI. In the public sector, he serves as an Administrative Analyst specializing in statistics at the Brazilian Company of Hospital Services (EBSERH). His research interests encompass time series analysis, data mining, machine learning, and computational statistics, with applications across finance, climatology, and healthcare. Dr. Guedes has contributed to the development of statistical methodologies, such as the Detrended Multiple Cross-Correlation Analysis (DMC) and the GMZTests R package. His work has been published in reputable journals and presented at various conferences, reflecting his commitment to advancing statistical science and its practical applications.

Professional Profile

Education

Dr. Guedes’s educational journey reflects a strong foundation in statistics and mathematics. He completed his Bachelor’s degree in Statistical Sciences at the Higher School of Statistics of Bahia (2004–2007), providing him with essential skills in data analysis and interpretation. Pursuing his passion for mathematics, he obtained a Licentiate in Mathematics from the Faculty of Educational Sciences (2007–2009), equipping him with pedagogical skills for teaching complex mathematical concepts. His academic pursuits culminated in a Master’s (2011–2014) and a Ph.D. (2012–2020) in Computational Modeling and Industrial Technology at SENAI CIMATEC. His doctoral research focused on the behavior of industrial production, employing advanced time series analysis techniques. Throughout his academic career, Dr. Guedes has demonstrated a commitment to interdisciplinary learning, integrating statistical theory with practical applications in industrial and technological contexts.

Professional Experience

Dr. Guedes has amassed extensive professional experience in both academic and public sectors. In academia, he has served as a substitute professor at the Federal University of Recôncavo da Bahia, teaching courses such as Algebra, Calculus, and Mathematics for Biology. He has also been a visiting professor at UNIASSELVI, contributing to the education of future statisticians and data scientists. In the public sector, Dr. Guedes holds the position of Administrative Analyst specializing in statistics at the Brazilian Company of Hospital Services (EBSERH), where he develops dashboards using Power BI and compiles statistical reports for maternity services. His professional roles have allowed him to apply his statistical expertise to real-world problems, bridging the gap between theoretical research and practical implementation. Additionally, his involvement in various educational institutions underscores his dedication to knowledge dissemination and capacity building in statistical sciences.

Research Interests

Dr. Guedes’s research interests are centered on the application of statistical methods to complex systems. He specializes in time series analysis, focusing on techniques like Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA) to study long-range dependencies in data. His work extends to data mining and machine learning, where he explores patterns in large datasets to inform decision-making processes. Dr. Guedes has applied these methodologies across various domains, including financial markets, climatology, and healthcare. Notably, he has investigated the interdependence of stock market indices using advanced cross-correlation techniques and analyzed climatic variables to understand environmental changes. His interdisciplinary approach demonstrates the versatility of statistical tools in addressing diverse scientific questions.

Research Skills

Dr. Guedes possesses a comprehensive skill set in statistical analysis and computational modeling. He is proficient in programming languages such as R and Python, utilizing them for data analysis, visualization, and the development of statistical packages. His expertise includes the creation of the GMZTests R package, which offers a suite of statistical tests for time series analysis. Dr. Guedes is adept at employing machine learning algorithms for predictive modeling and has experience with big data tools like PySpark. His skills extend to the development of interactive dashboards using Power BI, facilitating data-driven decision-making in organizational settings. Through continuous professional development, including courses on deep learning and data science, Dr. Guedes stays abreast of emerging technologies and methodologies in the field.

Awards and Honors

Throughout his career, Dr. Guedes has been recognized for his contributions to statistical science. He received a doctoral scholarship from the Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB), supporting his research in computational modeling. His scholarly work has garnered citations in academic publications, reflecting the impact of his research on the scientific community. Dr. Guedes’s commitment to excellence is further evidenced by his participation in professional development programs and certifications, including Lean Six Sigma and data science courses. These accolades underscore his dedication to advancing statistical methodologies and their practical applications.

Conclusion

Dr. Everaldo Freitas Guedes exemplifies the integration of rigorous academic training with practical experience in statistical analysis and data science. His educational background lays a solid foundation for his multifaceted career, encompassing teaching, research, and public service. Dr. Guedes’s research endeavors demonstrate a commitment to applying statistical methods to real-world problems, contributing valuable insights across various domains. His proficiency in computational tools and continuous pursuit of professional development position him as a leader in the field. Recognitions such as the FAPESB scholarship and citations of his work attest to his impact on the scientific community. Dr. Guedes’s career trajectory reflects a dedication to the advancement of statistical science and its application for societal benefit.

Publications Top Notes

  1. Title: Quantifying the Influence of Climatic Variables on the Incidence of Diseases in Salvador-BA
    Journal: Fluctuation and Noise Letters
    Date: June 2025
    DOI: 10.1142/S0219477525500294
    Contributors: Everaldo Freitas Guedes, Cláudia Ferreira da Cruz, Florêncio Mendes Oliveira Filho

  2. Title: DETRENDED MULTIPLE CROSS-CORRELATION COEFFICIENT BASED ON ρDMCA
    Journal: Fractals
    Date: May 16, 2025
    DOI: 10.1142/S0218348X25500434
    Contributors: E. F. Guedes, R. M. T. S. Dias, A. M. da Silva Filho, G. F. Zebende

  3. Title: Caracterização da rede de internações por diabetes mellitus no estado da Bahia: teoria das redes
    Journal: Revista Baiana de Saúde Pública
    Date: December 31, 2022
    DOI: 10.22278/2318-2660.2022.v46.n4.a3341
    Contributors: Raiara dos Santos Pereira Dias, Aloísio Machado da Silva Filho, Edna Maria de Araújo, Everaldo Freitas Guedes, Florêncio Mendes Oliveira Filho

  4. Title: Statistical Approach to Study the Relationship Between Stock Market Indexes by Multiple DCCA Cross-Correlation Coefficient
    Journal: Fluctuation and Noise Letters
    Date: October 2022
    DOI: 10.1142/S0219477522500456
    Contributors: G. F. Zebende, L. C. Aguiar, Paulo Ferreira, E. F. Guedes

  5. Title: Efficiency and Long-Range Correlation in G-20 Stock Indexes: A Sliding Windows Approach
    Journal: Fluctuation and Noise Letters
    Date: August 2022
    DOI: 10.1142/S021947752250033X
    Contributors: E. F. Guedes, R. P. C. Santos, L. H. R. Figueredo, P. A. da Silva, R. M. T. S. Dias, G. F. Zebende

  6. Title: How Statistically Significant is the DMCA Coefficient?
    Journal: Fluctuation and Noise Letters
    Date: June 2022
    DOI: 10.1142/S0219477522500213
    Contributor: Everaldo Freitas Guedes

  7. Title: Detrended multiple cross-correlation coefficient with sliding windows approach
    Journal: Physica A: Statistical Mechanics and its Applications
    Date: July 2021
    DOI: 10.1016/j.physa.2021.125990
    Contributors: E. F. Guedes, A. M. da Silva Filho, G. F. Zebende

  8. Title: Analysis of intentional lethal violent crimes: A sliding windows approach
    Journal: Physica A: Statistical Mechanics and its Applications
    Date: April 2021
    DOI: 10.1016/j.physa.2020.125653
    Contributors: A. M. da Silva Filho, G. F. Zebende, E. F. Guedes

  9. Title: DCCA cross-correlation coefficient with sliding windows approach
    Journal: Physica A: Statistical Mechanics and its Applications
    Date: August 2019
    DOI: 10.1016/j.physa.2019.121286
    Contributor: Everaldo Guedes

  10. Title: An econophysics approach to study the effect of BREXIT referendum on European Union stock markets
    Journal: Physica A: Statistical Mechanics and its Applications
    Date: June 2019
    DOI: 10.1016/j.physa.2019.04.132
    Contributor: Everaldo Guedes

Kun Cai | Econometrics and Finance | Best Researcher Award

Dr. Kun Cai | Econometrics and Finance | Best Researcher Award

University of International Business and Economics, China

Kun Cai is a rising scholar in the field of international trade and global value chains, currently based at the Global Value Chains Research Institute of the University of International Business and Economics, Beijing. Her research integrates empirical and quantitative methods to investigate productivity growth, knowledge spillovers, and the structural evolution of trade networks. Her work is notable for addressing complex issues such as firm ownership heterogeneity and domestic value-added in exports. Kun has made significant contributions to the construction and application of China’s input–output databases, which have facilitated detailed analysis of production networks across cities and provinces. Her collaboration with well-regarded economists and participation in large-scale national research projects further reflect her growing academic stature. She has co-authored publications in high-impact journals and participated in international conferences such as the ASSA/CEANA Annual Meeting and the Global Value Chain Development Report Workshop. Her blend of rigorous quantitative research and policy-relevant insight makes her work particularly valuable in contemporary discussions around industrial upgrading and technological self-reliance. As a researcher, Kun demonstrates both depth and innovation in tackling current economic challenges through data-intensive and policy-engaged approaches. Her trajectory indicates strong promise for leadership in her field in the near future.

Professional Profile

Education

Kun Cai has a solid academic background in economics, marked by progressive specialization in trade and industrial organization. She is currently pursuing her Ph.D. in Economics at the University of International Business and Economics in Beijing (2019–2025), where she is conducting cutting-edge research on knowledge diffusion and productivity growth within production networks. Her doctoral work distinguishes itself by introducing firm ownership and upstream-downstream linkages into dynamic trade models, which are then empirically tested using advanced input–output data. Prior to her Ph.D., she obtained a Master’s degree in Economics from East China University of Political Science and Law (2015–2018), where she built her foundation in economic theory, quantitative analysis, and policy studies. Her undergraduate degree was completed at the Southwestern University of Finance and Economics (2011–2015), a well-regarded institution in China for economics and finance. This educational progression reflects both breadth and depth in economic knowledge, with a continuous emphasis on research and analytical skills. Through this trajectory, she has gained proficiency in dealing with complex economic data, academic writing, and policy interpretation, setting a strong foundation for a research-intensive academic career. Her academic training has equipped her with the tools necessary to contribute meaningfully to both scholarly literature and public policy discourse.

Professional Experience

Kun Cai’s professional experience revolves around academic research, data analysis, and large-scale economic modeling, primarily through her involvement with the Global Value Chains Research Institute. As a doctoral researcher, she has played critical roles in major national research initiatives, including a flagship project funded by the National Natural Science Foundation of China. In this role, she served both as a Research Assistant and Project Secretary. Her responsibilities included processing microdata from China Customs and economic censuses, updating provincial input–output tables, and aligning multiple economic datasets. She also coordinated project logistics such as organizing expert meetings, drafting reports, and compiling documentation for project deliverables. These experiences have enhanced her practical skills in data management, empirical modeling, and collaborative research. In addition to research execution, she has also demonstrated capability in academic publishing and international communication through her co-authored journal articles and conference presentations. Her hands-on work with input-output databases that distinguish firm ownership is a unique technical contribution, positioning her as a resourceful analyst in global trade and productivity studies. This blend of technical, administrative, and academic experience highlights her capability to handle multifaceted research tasks while contributing intellectually and operationally to complex, interdisciplinary projects.

Research Interests

Kun Cai’s research interests lie at the intersection of international trade, productivity growth, and knowledge spillovers within global and domestic production networks. Her primary focus is on understanding how ownership structures and supply chain positioning influence the diffusion of knowledge and technological progress. Her dissertation specifically adds depth to this domain by developing a dynamic general equilibrium model that integrates firm heterogeneity and upstream-downstream linkages to assess knowledge diffusion across three dimensions: country, industry, and firm ownership. She also has strong interests in the measurement and evolution of domestic value-added in the context of China’s export economy. Her work explores how industrial policies shape local content and supply chain integration, with implications for economic independence and industrial upgrading. Kun’s long-standing involvement with the development of China’s interprovincial and inter-city input-output databases reflects a methodological interest in large-scale empirical tools for economic analysis. These tools not only enable her research but also contribute to the global research community. Furthermore, she is engaged with the economic dimensions of the electric vehicle sector, particularly in evaluating localization, technology independence, and value creation. Collectively, her research addresses pressing questions in trade policy, innovation diffusion, and industrial development through a rigorous, data-driven lens.

Research Skills

Kun Cai possesses an impressive array of research skills, particularly in empirical economic modeling, database development, and statistical programming. Her work on interprovincial and inter-city input–output databases demonstrates advanced capabilities in data collection, processing, and integration. She is proficient in statistical software such as Stata, MATLAB, and R, which she uses for spatial econometric modeling, regression analysis, and visualization. These technical tools are instrumental in her quantitative analysis of productivity spillovers and value-added trade dynamics. Kun also has experience using Tableau for interactive data presentation, which enhances the accessibility and policy relevance of her research findings. Her academic work frequently involves complex data structures such as trade statistics, economic census data, and firm-level records, which she handles with accuracy and methodological rigor. In terms of research communication, Kun has co-authored peer-reviewed papers and book chapters, showing her skill in scholarly writing and collaboration. She has also presented her findings at international conferences, demonstrating her ability to convey complex concepts to academic and policy audiences alike. Her bilingual fluency in Mandarin and English enables her to operate effectively in both domestic and international research environments. Overall, her skill set aligns well with high-level academic research in economics and policy analysis.

Awards and Honors

Kun Cai has been recognized for her academic achievements through a series of competitive scholarships and awards during her doctoral studies. She was awarded the First-Class Academic Scholarship for the 2021–2022 academic year, highlighting her exceptional academic performance and research contributions. In addition, she received the Second-Class Academic Scholarship in three different academic years—2019–2020, 2020–2021, and 2022–2023—demonstrating consistent excellence in coursework and research engagement. These honors reflect her dedication, analytical ability, and high academic standing within her institution. Beyond scholarships, her inclusion as a co-author in several major research publications and presentations at internationally recognized conferences also signifies informal recognition of her capabilities by senior researchers and institutions. Her involvement in a nationally funded research project further testifies to the trust placed in her skills by principal investigators. These accolades are not just academic milestones but also indicators of her growing reputation in the field of global value chain research. They highlight her potential as a future leader in economics, especially in areas relating to industrial policy, trade, and knowledge diffusion. Taken together, her honors and achievements affirm her suitability as a strong candidate for awards recognizing excellence in research.

Conclusion

Kun Cai is a promising researcher whose work stands at the confluence of international trade, productivity, and policy-driven economic modeling. Her research is methodologically sound, conceptually innovative, and directly relevant to ongoing global discussions around industrial upgrading, localization, and knowledge transfer. Through her doctoral work and participation in national research projects, she has made valuable contributions to both academic literature and data infrastructure development. Her strengths include empirical rigor, policy relevance, and collaborative research experience, as evidenced by her journal publications, working papers, and conference presentations. While her current focus is centered on China, expanding her work to comparative or global studies could enhance her research scope and influence. Additionally, more leadership in independent research initiatives would further elevate her profile as a principal investigator. Nevertheless, her progress to date reflects strong commitment, intellectual maturity, and impactful scholarship. Given the quality of her work, the relevance of her research agenda, and the technical competencies she has developed, Kun Cai is a suitable and commendable nominee for the Excellence in Research Award. Her potential for continued growth and contribution to the academic community is evident, and she represents the kind of scholar that such recognition is intended to support.

Publications Top Notes

  1. Title: An inter-city input-output database distinguishing firm ownership in the Greater China area during 2002–2017

  2. Authors: Wang, Yafei; Xu, Dingyi; Zheng, Heran; Yang, Peihao

  3. Journal: Scientific Data

  4. Year: 2025

Ahmed BenSaïda | Econometrics and Finance | Best Researcher Award

Prof. Ahmed BenSaïda | Econometrics and Finance | Best Researcher Award

Faculty from University of Sousse, Tunisia

Dr. Ahmed Bensaïda is a distinguished full professor of finance at Effat University in Jeddah, Saudi Arabia. With over two decades of academic experience, he has significantly contributed to the fields of finance and accounting. His academic journey began with a Ph.D. from the University of Tunis, Tunisia, and a Master’s degree from Nagasaki University, Japan. Dr. Bensaïda’s research interests encompass financial markets, behavioral finance, chaotic dynamics, risk management, spillovers and contagion, and asset pricing. He has authored numerous publications in these areas, reflecting his deep engagement with both theoretical and practical aspects of finance. His teaching portfolio includes undergraduate, postgraduate, and Ph.D. courses, demonstrating his versatility and commitment to education. Dr. Bensaïda has also played vital roles in academic administration, contributing to curriculum development, accreditation processes, and academic councils. His international exposure, combined with his extensive research and teaching experience, positions him as a leading figure in the field of finance education and research.

Professional Profile

Education

Dr. Ahmed Bensaïda’s academic foundation is rooted in a robust international education. He earned his Ph.D. in Finance from the University of Tunis, Tunisia, where he developed a strong analytical and theoretical understanding of financial systems. Prior to this, he completed his Master’s degree at Nagasaki University in Japan, an experience that provided him with a global perspective on financial practices and economic theories. This diverse educational background has equipped Dr. Bensaïda with a unique blend of Eastern and Western academic philosophies, enriching his teaching and research methodologies. His academic pursuits have been characterized by a commitment to excellence and a continuous quest for knowledge, laying the groundwork for his subsequent contributions to academia and the field of finance.

Professional Experience

Dr. Ahmed Bensaïda’s professional journey in academia spans over 20 years, marked by progressive roles and responsibilities. He began his career as a contractual lecturer at the Higher Institute of Management, University of Tunis, in 2002. He then served at HEC Sousse, University of Sousse, and FSEG Mahdia, University of Monastir, where he held positions ranging from lecturer to assistant professor, and eventually associate professor. In these roles, he was instrumental in developing course syllabi, managing academic departments, and contributing to scientific councils. In 2019, Dr. Bensaïda joined Effat University as an associate professor and was promoted to full professor in 2020. At Effat, he has been actively involved in student advising, accreditation management, and serving on various academic councils. His extensive experience reflects a deep commitment to academic excellence and leadership in higher education.

Research Interests

Dr. Ahmed Bensaïda’s research interests are diverse and interdisciplinary, focusing on areas critical to understanding and navigating modern financial systems. His work delves into financial markets, exploring the dynamics that drive market behavior and asset pricing. He has a keen interest in behavioral finance, examining how psychological factors influence investor decisions and market outcomes. Dr. Bensaïda also investigates chaotic dynamics within financial systems, aiming to understand complex, nonlinear behaviors that traditional models may overlook. His research on risk management addresses strategies to mitigate financial uncertainties, while his studies on spillovers and contagion analyze how economic shocks propagate across markets. Through these research endeavors, Dr. Bensaïda contributes valuable insights into the mechanisms that underpin financial stability and efficiency.

Research Skills

Dr. Ahmed Bensaïda possesses a comprehensive set of research skills that enable him to conduct rigorous and impactful studies in finance. He is adept at quantitative analysis, employing statistical and econometric methods to model financial phenomena and test hypotheses. His proficiency in data analysis tools allows him to handle large datasets, extract meaningful patterns, and derive actionable insights. Dr. Bensaïda’s expertise extends to developing theoretical frameworks that integrate concepts from economics, psychology, and mathematics to explain complex financial behaviors. He is skilled in academic writing, effectively communicating his findings through scholarly publications. Additionally, his experience in interdisciplinary research equips him to collaborate across fields, enriching his studies with diverse perspectives and methodologies.

Awards and Honors

Throughout his academic career, Dr. Ahmed Bensaïda has been recognized for his contributions to finance education and research. While specific awards and honors are not detailed in the available information, his promotion to full professor at Effat University in 2020 signifies a recognition of his academic achievements and leadership. His involvement in key academic councils and accreditation processes further reflects the esteem in which he is held by his peers and institutions. Dr. Bensaïda’s consistent progression through academic ranks and his active participation in shaping academic programs underscore his commitment to excellence and the impact of his work in the field of finance.

Conclusion

Dr. Ahmed Bensaïda’s distinguished career in finance academia is marked by a blend of international education, extensive teaching experience, and a profound research portfolio. His contributions to understanding complex financial systems, investor behavior, and market dynamics have enriched both academic literature and practical applications in finance. As a full professor at Effat University, he continues to mentor students, lead academic initiatives, and engage in research that addresses contemporary financial challenges. Dr. Bensaïda’s dedication to education and research exemplifies the role of academia in advancing knowledge and informing practice in the ever-evolving field of finance.

Publications Top Notes

  • Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold

    • Authors: A. BenSaïda, R. Chemkha, A. Ghorbel, T. Tayachi

    • Year: 2021

    • Citations: 202

  • Herding and excessive risk in the American stock market: A sectoral analysis

    • Authors: H. Litimi, A. BenSaïda, O. Bouraoui

    • Year: 2016

    • Citations: 173

  • Good and bad volatility spillovers: An asymmetric connectedness

    • Author: A. BenSaïda

    • Year: 2019

    • Citations: 152

  • Herding effect on idiosyncratic volatility in US industries

    • Author: A. BenSaïda

    • Year: 2017

    • Citations: 131

  • Volatility spillover shifts in global financial markets

    • Authors: A. BenSaïda, H. Litimi, O. Abdallah

    • Year: 2018

    • Citations: 116

  • The contagion effect in European sovereign debt markets: A regime-switching vine copula approach

    • Author: A. BenSaïda

    • Year: 2018

    • Citations: 81

  • High level chaos in the exchange and index markets

    • Authors: A. BenSaïda, H. Litimi

    • Year: 2013

    • Citations: 78

  • Noisy chaos in intraday financial data: Evidence from the American index

    • Author: A. BenSaïda

    • Year: 2014

    • Citations: 70

  • Shapiro-Wilk and Shapiro-Francia normality tests

    • Author: A. BenSaïda

    • Year: 2022

    • Citations: 67

  • The shifting dependence dynamics between the G7 stock markets

    • Authors: A. BenSaïda, S. Boubaker, D.K. Nguyen

    • Year: 2018

    • Citations: 59