4 papers
Empirical Asset Pricing via Ensemble Gaussian Process Regression
Damir FilipoviÄ, Puneet Pasricha
We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic informati…
Foundation Time-Series AI Model for Realized Volatility Forecasting
Anubha Goel, Puneet Pasricha, Martin Magris +1
Time series foundation models (FMs) have emerged as a popular paradigm for zero-shot multi-domain forecasting. These models are trained on numerous diverse datasets and claim to be…
Time-Series Foundation AI Model for Value-at-Risk Forecasting
Anubha Goel, Puneet Pasricha, Juho Kanniainen
This study is the first to analyze the performance of a time-series foundation AI model for Value-at-Risk (VaR), which essentially forecasts the left-tail quantiles of returns. Fou…
Sparse Portfolio Selection via Topological Data Analysis based Clustering
Anubha Goel, Damir FilipoviÄ, Puneet Pasricha
This paper uses topological data analysis (TDA) tools and introduces a data-driven clustering-based stock selection strategy tailored for sparse portfolio construction. Our asset s…