Artificial Intelligence


Multi-Dimensional Asset Allocation Strategy with DA-RNN

Authors: Tae Young Lee

Most RoboAdvisors reflect the perspective of investment banks, which differs from commercial banks in Korea. Most customers who use commercial banks have a conservative approach. In customer-focused thinking, the more you design your Robo Advisor, the more important it is to minimize customer losses. It was designed with the belief that the guarantee of principal through defense of the bear market would be a solid foundation to be returned to profits from the bear market. The traditional asset allocation model is dedicated to simple predictions that take risk as a parameter of volatility and draw the expected return to calculate the optimal share of the asset. This is not a big problem when the market is good, but it's going to cause a loss of the customer's principal in a booming market. This is not in line with the bank's robovisor idea, and we have created deep learning algorithms to defend against the bear market.

Comments: 7 Pages. Draft Paper

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Submission history

[v1] 2019-09-06 00:09:05

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