3 citations · 4 across the 5 of their papers we have counts for
5 papers
Learning Nonlinear Factor Models with Unknown Monotone Links from Incomplete and Noisy Data
Yutong Chao, Resat Gökhan, Jalal Etesami +1
We study a nonlinear factor model in which observed responses depend on low-rank latent factors through an unknown monotone link function. This setting is challenging and largely u…
Quantum Reservoir Computing for Realized Volatility Forecasting
Qingyu Li, Chiranjib Mukhopadhyay, Abolfazl Bayat +1
Recent advances in quantum computing have demonstrated its potential to significantly enhance the analysis and forecasting of complex classical data. Among these, quantum reservoir…
Optimizing Portfolio with Two-Sided Transactions and Lending: A Reinforcement Learning Framework
Ali Habibnia, Mahdi Soltanzadeh
This study presents a Reinforcement Learning (RL)-based portfolio management model tailored for high-risk environments, addressing the limitations of traditional RL models and expl…
Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework
Jalal Etesami, Ali Habibnia, Negar Kiyavash
We propose a nonparametric and time-varying directed information graph (TV-DIG) framework to estimate the evolving causal structure in time series networks, thereby addressing the…
Forecasting in Big Data Environments: an Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)
Ali Habibnia, Esfandiar Maasoumi
This paper considers improved forecasting in possibly nonlinear dynamic settings, with high-dimension predictors ("big data" environments). To overcome the curse of dimensionality…