Implement a data–driven investment strategy
The investing landscape is increasingly driven by big data and artificial intelligence. For most finance professionals, big data, statistics, and programming are outside their comfort zone. Yet, proficiency in these areas is becoming a prerequisite for successful investing. And while there are plenty of resources on these individual topics, what is missing is a framework for combining these disciplines for investment purposes.
Data–Driven Investing shows readers how investment decisions can be made or improved through the use of alternative datasets and inference techniques. The author covers artificial intelligence algorithms, data visualization, and data sourcing to show how these components come together to form a more robust investment strategy. The goal is to help finance professionals prepare for an investing landscape increasingly driven by big data and artificial intelligence.
- Shows how investing wisdom can be harnessed through science and augmented by data
- Demonstrates how an augmented investing philosophy promises a deeper understanding of future economic performance
- Is essential reading for fund managers, research analysts, quantitative investors, data scientists, and general finance professionals
- Includes a companion website with code, data sets, and videos providing more in–depth information on augmented/data–driven investing
This book comes at a time of increasing investor anxiety with lackluster hedge fund performance, which is causing many funds to explore data–driven investing as a possible evolution of their strategies.