Early Career Talks on Financial Mathematics and Engineering - Belief Estimation and Robo-Advising

Explore two early career talks in financial mathematics and engineering during this virtual event hosted by the Society for Industrial and Applied Mathematics. Delve into Dena Firoozi's presentation on belief estimation in major-minor LQG mean field games, covering topics such as electronic markets, optimal execution problems, and mean field evolution. Then, discover Sveinn Olafsson's insights on personalized robo-advising, examining the enhancement of investment strategies through client interaction, market dynamics, and adaptive mean-variance criteria. Gain valuable knowledge on cutting-edge research in financial modeling, optimal execution, and the future of automated investment advice under the moderation of Stephan Sturm from Worcester Polytechnic Institute.

Intro
Motivation: Electronic Markets
Optimal Execution Problems: Trading Dynamics
Optimal Execution Problems: Incomplete Information
Major-Minor LQG Mean Field Games
Mean Field Evolution
Major Agent's Kalman Filter
Separation Principle for Major Agent
Minor Agent's Kalman Filter
Best Response Strategies
Mean Field Consistency Equations
Simulation Results
Optimal Execution Problems: Liquidation Objective
Robo-Advisors
Model of Robo-Advising
Research Questions
Market Dynamics
Client's Risk Aversion
Human-Machine Interaction
Robo-Advisor's Model of Client
Adaptive Mean-Variance Criterion
Optimal Investment Strategy
Structure of Optimal Strategy
Computation of Optimal Strategy
Interaction and Portfolio Personalization
Economic Transitions and Investment Performance
Future Developments