Policy Portfolio Construction
Our policy portfolio construction methodologies include the use of multi–period portfolio optimization techniques considering forward looking time variation of investment opportunities, and dynamic rebalancing strategies.
These are not necessarily limited to traditional asset classes but can also include illiquid asset classes and risk factor based analysis.
Machine Learning based Tactical Asset Allocation
Our machine learning based tactical asset allocation strategies attempt to achieve positive absolute return using sophisticated machine learning techniques, forecasting returns on assets such as stocks and currencies dynamically.
Strategic Asset Allocation for Robo–Advisory
Our asset allocation methodologies for Robo–Advisory include risk tolerance diagnosis for retail investors, strategic asset allocation, and glide path estimation (risk adjustment mechanism considering the change in risk tolerance due to the increase in age). These are provided to Mizuho Bank’s Robo–Advisory platform, "SMART FOLIO". We also conduct research on robust optimization, taking into account estimation error of expected return and risk.