Book Image

The Future of Finance with ChatGPT and Power BI

By : James Bryant, Aloke Mukherjee
2.5 (4)
Book Image

The Future of Finance with ChatGPT and Power BI

2.5 (4)
By: James Bryant, Aloke Mukherjee

Overview of this book

In today's rapidly evolving economic landscape, the combination of finance, analytics, and artificial intelligence (AI) heralds a new era of decision-making. Finance and data analytics along with AI can no longer be seen as separate disciplines and professionals have to be comfortable in both in order to be successful. This book combines finance concepts, visualizations through Power BI and the application of AI and ChatGPT to provide a more holistic perspective. After a brief introduction to finance and Power BI, you will begin with Tesla's data-driven financial tactics before moving to John Deere's AgTech strides, all through the lens of AI. Salesforce's adaptation to the AI revolution offers profound insights, while Moderna's navigation through the biotech frontier during the pandemic showcases the agility of AI-focused companies. Learn from Silicon Valley Bank's demise, and prepare for CrowdStrike's defensive maneuvers against cyber threats. With each chapter, you'll gain mastery over new investing ideas, Power BI tools, and integrate ChatGPT into your workflows. This book is an indispensable ally for anyone looking to thrive in the financial sector. By the end of this book, you'll be able to transform your approach to investing and trading by blending AI-driven analysis, data visualization, and real-world applications.
Table of Contents (13 chapters)
Free Chapter
1
Part 1: From Financial Fundamentals to Frontier Tech: Navigating the New Paradigms of Data, EVs, and AgTech
6
Part 2: Pioneers and Protectors: AI Transformations in Software, Finance, Biotech, and Cybersecurity

Integrating Twitter (now X) sentiment and CAR – Power BI data visualization

Including both the weighted Twitter (now X) sentiment and the CAR in a single visualization can certainly provide a comprehensive view of your trading strategy. It’s a fantastic way to see the relationship between social sentiment and the financial health of a bank at a glance.

In this section, you will integrate weighted Twitter (now X) sentiment CAR into a single Power BI dashboard for an in-depth look at your trading strategy. You start by exporting the previously collected data from Python to a CSV file. Then, you load this data into Power BI and use its Power Query Editor for any necessary data transformations. Then, you visualize this data using a heat map, allowing you to instantly perceive the relationship between social sentiment and a bank’s financial health. The finalized, interactive dashboard can be shared with others, offering a comprehensive and dynamic view that supports...