Improving Venture Capital Analysis using Data-Driven Research and Models

Client Background

The clients were investors interested in technology companies and venture capital. They realized there is a need for a data-driven methodology to analyze technology companies and reduce investment risks.

Industry: Investment Management

Location: USA

Engagement: Data and Technology

2X

faster portfolio customization

Problem Statement

Investors need an objective, data-driven methodology to analyze technology companies to make informed investment decisions and reduce risks associated with investing in the space.
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Objectives

Develop a proprietary adoption index that measures and scores the adoption of
technology companies.
Utilize various metrics and factors sourced from different data sources.
Create proprietary investment portfolios, research, and recommendations for various
investment vehicles and accounts.
4. Implement a technology stack for data analysis, visualization, and API development.
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Solution:

Identified relevant metrics and factors for measuring technology adoption.
Developed a process to consume and clean data from various sources.
Assigned proprietary weights to each metric and factor based on their importance.
Tested the index using backtests and projections.
Used the index to create investment portfolios, research, and recommendations.
Implemented a technology stack for data analysis, visualization, and API development.
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