iFUNDit: Visual Profiling of Fund Investment Styles

MPhil Thesis Defence


Title: "iFUNDit: Visual Profiling of Fund Investment Styles"

By

Mr. Bon Kyung KU


Abstract

The analysis of fund investment style is crucial for both fund managers 
and investors. It reveals the underlying investment strategy of a fund, 
which determines its performance. A clear profiling of a fund’s investment 
strategy provides other fund managers with invaluable insights to enhance 
their investment strategies, and help investors assess the suitability of 
the fund investments regarding style preference and risk management. 
However, analyzing a fund’s investment styles is challenging, as it 
requires a comprehensive analysis of high dimensional temporal data that 
are often difficult to explore, even for experienced fund managers.

To address this issue, we propose iFUNDit, an interactive visual analytic 
system for fund investment style analysis. The system decomposes funds’ 
various attributes into two categories, namely, the performance attributes 
and the investment style factors; and visualize them in a set of coupled 
visualizations: a distribution view to display performance attributes of 
funds and managers, a cluster view to show the grouping of investment 
styles in the market, and a detail view to delineate the temporal 
evolution of investment style. The system provides a holistic overview of 
fund data and facilitates a streamlined analysis of investment styles at 
the fund and manager level. We demonstrate the effectiveness of the system 
through interviews with domain experts, and case studies by using the 
China mutual fund data set.


Date:  			Tuesday, 18 August 2020

Time:			10:00am - 12:00noon

Zoom meeting:		https://hkust.zoom.us/j/3941396622

Committee Members:	Prof. Huamin Qu (Supervisor)
  			Dr. Dimitris Papadopoulos (Chairperson)
 			Dr. Xiaojuan Ma


**** ALL are Welcome ****