Robo-Advising in Motion: A Model Predictive Control Approach

By Tomasz R. Bielecki, Igor Cialenco

Published 2026-01-14

Everscope rating

1456.8

Relevance to quantitative trading

8 / 10

Implementation complexity

6 / 10

Reproducibility

4 / 5

About this paper

Methodology: Stochastic Model Predictive Control (SMPC) with HMM-Black-Litterman Forecasting. Problem types: Portfolio Optimization, Risk Management, Optimization, Time Series Forecasting.

arXiv:2601.09127 · Paper rankings

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