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Shweta Bajpai
Assistant Professor- Senior Scale
Profile Summary
Dr. Shweta Bajpai is a finance academic specialising in asset pricing, empirical finance, and green finance. She holds a PhD in Finance from IIT Roorkee and is a UGC-NET JRF awardee.
Her research spans asset pricing models, market microstructure, liquidity, tail risk, and climate finance, with publications in ABDC- and Scopus-listed journals such as Financial Research Letters and Journal of Prediction Markets. She actively presents her work at leading national and international forums.
Work Experience
Dr. Bajpai has over seven years of academic experience. She is currently Assistant Professor (Selection Grade) at UPES and has previously taught at Amity University Lucknow.
Her experience includes teaching core finance courses, doctoral supervision, curriculum development, and academic coordination.
Research Interests
Asset pricing; market microstructure; liquidity and tail risk; cross-section of stock returns; green finance; carbon risk.
Teaching Philosophy
Her teaching approach is student-centric and application-oriented, using case studies, simulations, and empirical analysis in R and Python.
She encourages inquiry, collaboration, and analytical thinking, helping students develop practical skills relevant to financial markets.
Courses Taught
Corporate Finance; Financial Management.
Awards and Grants
UGC-NET JRF awardee; recipient of MHRD Fellowship during PhD. Awarded an ICSSR research grant (₹6.5 lakh) for a project on Atal Pension Yojana. Also selected for ICSSR Postdoctoral Fellowship and Uttar Pradesh CM Research Fellowship.
Scholarly Activities
Dr. Bajpai’s research focuses on asset pricing, climate finance, and financial markets, with publications in ABDC- and Scopus-indexed journals. She has presented at major academic platforms including the India Finance Conference (IIM A, B, C), IIM Lucknow, IIT (ISM) Dhanbad, and the World Finance & Banking Symposium.
Her work explores emerging areas such as green finance and carbon risk, using empirical and data-driven methods. She actively contributes to research through conference participation, workshops, and academic collaborations.
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