Colloquium
- Colloquium
- STAT 5924
- Thursdays
- 3:30 pm to 4:30 pm
- 1860 Litton-Reaves Hall
Colloquium Schedule Fall 2025
Bio: Ricky Rambharat (Sufficient Statistics LLC)
Ricky Rambharat is an applied statistician who worked at the Office of the Comptroller of the Currency (OCC), the national bank regulator for the U.S., for the past 18 years. He earned his PhD in Statistics from Carnegie Mellon University in 2005. Interestingly, following a 2-year stint at Duke University, he joined the OCC in 2007 at the onset of the Global Financial Crisis. As such, he got immediate exposure to challenging empirical issues confronting the nation’s largest banks, and these issues called upon his expertise in statistics to adequately establish quantitative guardrails to support the “Safety & Soundness” mission of the OCC. Ricky’s tenure at the OCC exposed him to banking supervisory matters in market risk, compliance risk, sampling and regulatory policy analysis. He has presented at reputable conference venues, published in leading journals, collaborated with both U.S. and international regulators and academics. The next phase of Ricky’s career will take him to the Defense Industry.
Abstract:
The Standard & Poor's 100 Index (S&P 100 Index) trades both American and European-style options, which is atypical as most underlying trade options with only one of these features. As such, the options on the S&P 100 Index can be empirically assessed for adherence to prevailing theoretical results. One particular result, due to R. Myneni (1992, AOAP), establishes that the price of an American put option can be decomposed into its early-exercise premium (EEP) and the price of the corresponding European put option. This result suggests that option-implied measures of volatility should adhere to this decomposition. The present study investigates the extent of parity in the option-implied volatility signals between American and equivalently structured (same strike and tenor) European put options on the S&P 100 Index. Leveraging statistical process control, we document the extent of agreement in the implied volatilities of S&P 100 American and European put options during a time frame that spans before, during, and after the Global Financial Crisis (GFC, approximately 2007-2009). We further augment our study to investigate the statistical agreement between the market price of volatility risk of American and equally specified European put options on the S&P 100 Index. Our results indicate that parity between these volatility signals generally hold, thus adhering to theory, but notable statistical departures are evident, particularly during periods of extreme financial distress, thus affording likely profitable arbitrage opportunities.
Bio:
Dr. Wu is a Professor and Chair of the Department of Health Services Administration and Policy, as well as the Assistant Dean of Global Engagement at Temple University College of Public Health. She is a multidisciplinary researcher who applies data management, AI/ML, NLP/LLM, and digital twins in the fields of life science, medicine, public health, and social work, including cancer radiotherapy, diabetes, cardiovascular disease, infectious diseases, aging, Alzheimer's disease, and other neurodegenerative conditions. She collaborates with academia, community health centers, research institutes, industrial partners, and local communities. Her research has secured funding from various agencies, such as NSF, NIH, USAID, PCORI, JDRF, RWJF, and more.
See more details at https://cph.temple.edu/directory/huanmei-wu-tuo12759
Presentation Title: From Concept to Practice: Real-World Applications of Digital Twins for Health
Abstract:
Digital Twins for Health (DT4H) are virtual representations of individuals or health systems that are continuously updated with real-world data. Once largely theoretical, DT4H technologies are now moving into practice and transforming fields including medicine, public health, dentistry, and social work. This presentation will introduce the concept of DT4H and explain how digital twins are constructed through the integration of data, computational algorithms, AI/ML models, and feedback loops. Real-world examples will be highlighted, including applications in precision medicine, chronic disease management, drug development, and health resource allocation. Particular attention will be given to the essential role of data science and statistics in ensuring data quality, developing robust models, and validating outcomes. The talk will also examine challenges, opportunities, and ethical considerations in the adoption of digital twins. By the end, the audience will gain a clear understanding of how DT4H is being applied today and the pathways it opens for advancing patient care and public health.
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Contact Information
Department of Statistics (MC0439)
Hutcheson Hall, RM 406-A, Virginia Tech
250 Drillfield Drive
Blacksburg, VA 24061
Phone: 540-231-5657
Department Head:
Robert B. Gramacy