Build a Roboadvisor in Modelshop

As new generations of customers come to expect services when and where they desire, financial institutions need to adapt their products to meet those expectations. One such example is the advent of automated investment allocation applications, colloquially referred to as Roboadvisors. These applications provide wealth management customers access to intelligent investment advice customized to their specific financial situation without the need to meet face to face with an investment professional.

This video is part one in a four-part demonstration in which we will use Modelshop to construct a Roboadvisor from scratch. We will create the foundation of our model by importing portfolio data from an Excel spreadsheet, create market and strategy relationships inside the data, and define custom calculations to determine suggested sector allocations. In subsequent blogs we will supplement our model with live stock data from open online sources, create industry standard stock performance metrics, incorporate a machine learning model to optimize expected returns, and finally deploy the Roboadvisor to a customer facing web application using Modelshop’s REST APIs.

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