Good portfolios from bad forecasts: The anatomy of LLM volatility estimates
Finance Research Letters, 109, 110572.
Research record
Publications
Anjana Yatawara’s work runs along complementary lines: time series, stochastic modeling and financial econometrics; statistics for artificial intelligence; artificial intelligence in mathematics and statistics education; and environmental statistics and data science.
The methodological papers and the applied papers feed each other — the volatility work supplies the machinery for dependence and memory, and the environmental and education work supplies the questions that make it worth building.
Peer-reviewed journal articles, work accepted for publication, conference proceedings and peer-reviewed conference papers, manuscripts under review or in revision, and selected works in progress.
Yatawara’s name is emphasised in each author list. Review and revision status is stated as it stood in September 2026.
Peer-reviewed
Journal articles
Does trading volume improve long-term volatility forecasts? Evidence from the MF2-GARCH framework
Journal of Forecasting.
Air pollution exposure inequality across U.S. income and racial groups, 2000–2023: A hybrid monitor–satellite analysis with two new shape diagnostics
Atmospheric Environment: X, 31, 100492.
Co-first authors Tom Regpala and Eric Palafox are CSUB undergraduates he mentors.
Income-based exposure disparities across California counties, 2000 to 2023: A generalizable statistical framework
Environmental Research: Health, 4(1), 011002.
First author Kayla Ko is a CSUB undergraduate he mentors.
Evaluating fine-scale air-quality heterogeneity using a low-cost multipollutant sensor network in Twin Cities, Minnesota
ACS ES&T Air, 3(4), 1057–1068.
Forthcoming
Accepted for publication
Structured AI-Tutoring for Computer Architecture Courses
Accepted June 23, 2026ASEE Computers in Education Journal, 2026 FIE Special Issue.
Peer-reviewed
Conference proceedings and conference papers
WIP: Structured AI Tutoring in Engineering Education
Proceedings of the 2025 IEEE Frontiers in Education Conference (FIE), 1–5.
Computer-Aided Instruction for K–12 Teachers: A Cognitive Apprenticeship Approach to LLM Integration
2025 Artificial Intelligence x Humanities, Education, and Art (AIxHEART), 13–16.
The Multiplicative Factor Multi-Frequency Exponential GARCH ((MF)2-EGARCH)
Proceedings of the Joint Statistical Meetings, Business and Economic Statistics Section.
The Asymmetric Hyperbolic Generalized Autoregressive Conditional Heteroscedastic (A-HYGARCH) Model
Proceedings of the Joint Statistical Meetings, Business and Economic Statistics Section.
Under review
Manuscripts under review, revision and editorial consideration
Grouped by research area. Status as it stood in September 2026.Artificial Intelligence in Mathematics & Statistics Education
From Answer Generators to Thinking Partners: Scaffolded LLM Tutors in Statistics Education
Third revision submittedJournal of Statistics and Data Science Education.
From an Apparent Gain to a Composition Artefact: A Three-Condition Study of Generative AI in an Undergraduate Proof-Based Mathematics Course
Submitted; under editorial assessmentComputers & Education: Artificial Intelligence.
Statistics for Artificial Intelligence
Empirical Asset Pricing via Large Language Models
Revised manuscript submittedThe Journal of Finance and Data Science.
Time Series, Stochastic Modeling & Financial Econometrics
When Variance Arrives: Intraday Timing Information in Realized-Variance Forecasting
Under reviewJournal of Econometrics.
The Timescale Structure of Volatility Memory
Under considerationJournal of Financial Econometrics.
The Shape of Volatility Memory
Under considerationQuantitative Finance.
A Multiplicative-Factor Multi-Frequency Conditional-Mean Model for Count Time Series
Revised manuscript submittedJournal of Time Series Analysis.
Quasi-Maximum Likelihood Estimation of EGARCH(p,q): Continuous Invertibility, Consistency, and Asymptotic Normality under Verifiable Conditions
Under editorial assessmentEconometric Theory.
Do Volatility Components Explain the Heavy Tails of GARCH Residuals?
Under considerationInternational Review of Economics & Finance.
Spatial & Environmental Statistical Methodology
Lagged Causal Effects from Spatially Aggregated Data: A Change-of-Support Distributed-Lag Framework with Design Diagnostics
Under considerationSpatial Statistics.
In progress
Selected works in progress
Prediction-Powered Inference with Model-Assisted Validation Labels
(MF)2-GARCH-A: Volatility Modeling with a Sign-Sensitive Long-Run Component
Multiple-Regime Hyperbolic GARCH (MR-HYGARCH)
Improving Influenza Forecasting: A GRU-CNN Hybrid Model with Yeo-Johnson Scaling
Doctoral work
Dissertation
The Multiplicative Factor Multi-Frequency Exponential GARCH ((MF)2-EGARCH)
Ph.D. dissertation, Missouri University of Science and Technology.
Advisor: Dr. V. A. Samaranayake.
Drafts of working papers are available on request
Manuscripts under review and works in progress can be sent on request. The published record is also listed on Google Scholar and ORCID.