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

Leveraging AI and sentiment – Salesforce sentiment-adjusted options straddle

Creating a strategy combining AI-powered CRM evolution with a sentiment-adjusted straddle strategy would involve monitoring the sentiment regarding Salesforce’s AI-powered CRM evolution and setting up options trades based on that sentiment.

A sentiment-adjusted straddle strategy involves buying a call option and a put option with the same expiry date but different strike prices, which you adjust based on the sentiment.

This is a simplified overview of the steps to implement the strategy using Python, considering that you have access to options pricing data and sentiment analysis results:

  1. Set up your environment: Start by setting up your Python environment and importing the necessary libraries. If you don’t have Python and pip installed, you should do that first. Once you have Python set up, you can install the libraries using pip, the Python package installer. Open up your...