Research area
AI for Finance
Attempts to integrate machine-learning techniques to the problems in financial domain has been widely done in both the industry and the academia. Among the machine-learning technologies, we focus on deep reinforcement learning which is efficient in solving sequential decision making problems under complex states.
For the shortest time-frame of trading, we are trying to develop an optimal high-frequency trading policy by training the dynamics of the limit order books. For longer time-frame of investing, we are in progress to solve portfolio optimization under various constraints with deep reinforcement learning.
Sample paper: “Extended Framework for Deep Reinforcement Learning Applied to High-Frequency Trading”
FinTech
Due to the limited human resources in the financial sector, asset management services have been offered only to the riches in the form of private banking service. Through technology, the domain of FinTech aims to provide these expensive financial services to the public at low cost.
With this motivation in mind, we have developed a personalized life-cycle goal-based investment service. With the research as a starting point, we are currently trying to increase the scalability of our solution, which is, to solve the problem with lower computational cost in a faster manner.
Sample paper: “Personalized Goal-Based Investment via Multi-Stage Stochastic Goal Programming”
Investment Management
Another key research area is investment management. We aim to develop quantitative technologies that can improve investment performance. The main efforts have been spent on modeling uncertainties as well as obtaining optimal investment decisions based on such uncertainty models.
Sample paper: “Dynamic Asset Allocation for Varied Financial Markets under Regime Switching Framework”
Financial Optimization
Optimization plays a central role in financial decision making. We study various financial optimization problems such as robust optimization, stochastic programming, dynamic programming from the perspective of optimal decision making under uncertainty.
Sample paper: “Deciphering Robust Portfolios”