Analysis of Advisor Portfolio using Multivariate Time Series and Cosine Similarity

TL;DR

This paper analyzes mutual fund advisors' portfolios using multivariate time series and cosine similarity to identify patterns, aiding sales strategies by matching products to advisors' interests.

Contribution

It introduces a method to analyze advisor portfolios with multivariate time series and cosine similarity, revealing patterns to improve targeted sales approaches.

Findings

Identified distinct portfolio patterns among advisors

Enhanced matching of products to advisor interests

Potential to increase sales efficiency

Abstract

In mutual fund, an investment adviser gives advice to clients about investing in securities such as stocks, bonds, mutual funds, or exchange traded funds. Some investment advisers manage portfolios of securities. In this paper, we analyze advisor portfolio for each advisor so as to recognize the pattern in each adviser's portfolio. Such analysis helps the sales people to sell the fund company products to the suitable advisors desirable to the nature of the product they want to sell. This is done by analyzing the kind of products advisors have been interested in which will help to boost the sales of the products as sales people will be reaching the appropriate advisors.