Automated Insights in Finance Using Machine Learning & AI

Explore the application of machine learning and AI in finance through this 45-minute talk. Discover how quantitative hedge fund managers leverage automated processing to extract actionable insights from alternative data sources. Learn about sentiment analysis from textual data, construction of scoring models from complex datasets, and the use of alternative data like extreme weather to quantify impact on companies. Delve into robust portfolio construction by blending alternative data-derived factors with traditional ones, and explore machine learning techniques for asset pricing. Gain valuable insights into the broad applications of AI in finance, including automated intelligence, news sentiment analysis, smart beta strategies, and the challenges of correlation vs causation in alternative data analysis.

Introduction
About Bloomberg
What is AI
What is Bloomberg
Automated Intelligence on Demand
News
Sentiment
Topic Codes
Clean Clustering
Smart Beta
Alpha vs Beta
Myths
Digging Deeper
Correlation vs Causation
Traditional vs Machine Learning
Alternative Data
Snowfall Data
Retail Data
Snowfall Exposure
Trading Strategy
Cyclones
Weather Data
Technical Details
Data Source
Training Strategy
Future Predictions
Forecasting
SuperForecasting
Whisper
Identifying Errors
Median Absolute Deviation
Sequential Ensemble
Sourcing the Truth
The Challenge
The Confusion
Build the Right Models
Analyst Rankings
Tradable vs Nontradable
Scoring