The Future of Finance with ChatGPT and Power BI

Book description

Enhance decision-making, transform your market approach, and find investment opportunities by exploring AI, finance, and data visualization with ChatGPT's analytics and Power BI's visuals

Key Features

  • Automate Power BI with ChatGPT for quick and competitive financial insights, giving you a strategic edge
  • Make better data-driven decisions with practical examples of financial analysis and reporting
  • Learn the step-by-step integration of ChatGPT, financial analysis, and Power BI for real-world success
  • Purchase of the print or Kindle book includes a free PDF eBook

Book Description

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.

What you will learn

  • Dominate investing, trading, and reporting with ChatGPT's game-changing insights
  • Master Power BI for dynamic financial visuals, custom dashboards, and impactful charts
  • Apply AI and ChatGPT for advanced finance analysis and natural language processing (NLP) in news analysis
  • Tap into ChatGPT for powerful market sentiment analysis to seize investment opportunities
  • Unleash your financial analysis potential with data modeling, source connections, and Power BI integration
  • Understand the importance of data security and adopt best practices for using ChatGPT and Power BI

Who this book is for

This book is for students, academics, data analysts, and AI enthusiasts eager to leverage ChatGPT for financial analysis and forecasting. It's also suitable for investors, traders, financial pros, business owners, and entrepreneurs interested in analyzing financial data using Power BI. To get started with this book, understanding the fundamentals of finance, investment, trading, and data analysis, along with proficiency in tools like Power BI and Microsoft Excel, is necessary. While prior knowledge of AI and ChatGPT is beneficial, it is not a prerequisite.

Publisher resources

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Table of contents

  1. The Future of Finance with ChatGPT and Power BI
  2. Contributors
  3. About the authors
  4. About the reviewers
  5. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
    4. Download the example code files
    5. Conventions used
    6. Get in touch
    7. Share Your Thoughts
    8. Download a free PDF copy of this book
  6. Part 1: From Financial Fundamentals to Frontier Tech: Navigating the New Paradigms of Data, EVs, and AgTech
  7. Chapter 1: Financial Mastery with ChatGPT: From Basics to AI Insights
    1. Technical requirements
    2. An introduction to key financial concepts and investment principles
      1. Basic investment types and investment strategies
    3. Introducing financial statements
    4. Understanding financial ratios and metrics
      1. Interpreting financial ratios and metrics
    5. The fundamentals of technical analysis
      1. Combining fundamental and technical analysis
    6. Understanding the power of ChatGPT in financial analysis
      1. Integrating ChatGPT into Your Financial Analysis Workflow
    7. Getting started with ChatGPT for finance
      1. Refining your interactions with ChatGPT
    8. ChatGPT for financial analysis – analyzing earnings reports for Palo Alto Networks
      1. Instructions to access and store Palo Alto Networks’ 10-Q reports using sec-api (September 2021–March 2023)
      2. Instructions for analyzing 10-Q reports with ChatGPT
      3. ChatGPT’s analysis and insights
      4. Further exploration with ChatGPT
    9. Combining ChatGPT with fundamental analysis
    10. Summary
  8. Chapter 2: Creating Financial Narratives with Power BI and ChatGPT
    1. Technical requirements
    2. A brief overview of Power BI and its applications in finance
      1. The benefits of combining Power BI with ChatGPT insights
    3. The importance of structuring data in financial analysis
      1. Importing data into Power BI
    4. Visualization techniques in Power BI
      1. Selecting appropriate visualizations for financial data
      2. Tips for creating effective financial visualizations
    5. Creating financial dashboards with Power BI
      1. Arranging financial visuals for clarity in Power BI
      2. Illustration – Power BI dashboard of finance data
    6. Best practices for data modeling, visualization, and ChatGPT integration
      1. Ensuring clean and well-structured data modeling
      2. Choosing the right visualizations for effective communication
      3. Leveraging ChatGPT insights to enhance financial analysis
      4. Ensuring data security and privacy
    7. Walk-through use case – analyzing financial data using Power BI
    8. Walk-through use case – analyzing financial ratios using Power BI and ChatGPT
    9. Summary
  9. Chapter 3: Tesla’s Financial Journey: AI Analysis and Bias Unveiled
    1. Introduction to ChatGPT and AI in financial analysis
      1. Venturing beyond convention—exploring Tesla’s unconventional data sources
      2. Shifting gears—rethinking metrics and KPIs for Tesla
      3. News and earnings call transcripts—unveiling the sentiment spectrum
      4. Tesla: growth drivers and potential risks
      5. Benchmarking and ratio analysis: AI-driven insights
      6. Trading strategies based on risk preference
    2. Case study: Tesla Inc.
      1. Evaluating investment opportunities and risks with AI-driven insights
      2. Tesla trading strategy (aggressive and conservative)
      3. Aggressive trading strategy using options
      4. Conservative trading strategy using position trading
      5. News and market sentiment integration for trading strategies: aggressive and conservative
      6. Power BI visualizations—Tesla
      7. Financial visualizations—data extraction to Power BI visualizations
      8. Instructions
      9. Market competition visualizations–data extraction to Power BI visualization
      10. KPI visualizations–data extraction to Power BI visualization
      11. Final thoughts: leveraging ChatGPT and the OpenAI API in your data visualization workflow
      12. Best practices and ethics in AI-driven financial analysis
    3. Understanding AI model bias
    4. Summary
  10. Chapter 4: John Deere’s AgTech Revolution – AI Insights and Challenges
    1. Digitizing the fields – unleashing a tech revolution with John Deere
      1. Future opportunities and predictions
      2. Digital seedbed – a comparative analysis of AgTech titans
      3. The hidden goldmine – unearthing unconventional data for strategic investments in John Deere
    2. John Deere’s AgTech Revolution – AI Insights and Challenges
      1. Unlocking the power of quantitative investing – a game-changer for agri-business
      2. Quantitative trading example – John Deere
      3. Power BI visualization for quantitative trading example – John Deere
      4. Unveiling the power of advanced financial metrics and valuation methods through Power BI visualization
      5. Unveiling value – harnessing AI for discounted cash flow analysis
      6. Visualizing the future – leveraging Power BI to explore John Deere’s potential in emerging markets with DCF analysis
    3. Embracing the AI revolution with AutoGPT – reshaping financial analysis and trading through autonomous AI
      1. The pros and cons of AutoGPT in financial analysis
      2. Using AutoGPT in finance, investment, and trading
      3. Using AutoGPT for automated trading (moving average trading example)
      4. AutoGPT – financial analysis Monte Carlo simulation
      5. Portfolio rebalancing strategy – AutoGPT
    4. Python power play – fueling financial analysis with advanced code
      1. Weather score calculation – weather trade
      2. Location and crop type – weather trade
      3. Trade threshold suggestions – weather trade
    5. Seeds of fortune – unraveling the correlation between weather patterns and John Deere’s stock performance
      1. Connecting OpenAI with Power BI
    6. Understanding and mitigating LLM “hallucinations” in financial analysis and data visualization
      1. Understanding hallucinations
      2. How can we spot hallucinations?
      3. What can we do about hallucinations?
      4. Minimizing hallucinations in the future
      5. OpenAI is on the case
      6. Trading examples
      7. Power BI visualization examples
    7. Summary
  11. Part 2: Pioneers and Protectors: AI Transformations in Software, Finance, Biotech, and Cybersecurity
  12. Chapter 5: Salesforce Reimagined: Navigating Software and LLMs
    1. Salesforce’s turnaround – a market sentiment perspective
      1. The phoenix’s first flight – recognizing the downtrend
      2. The game plan – activist investors move in
      3. Restoring faith – a bold new direction
      4. Seeing the change – sentiment analysis at work
      5. The payoff – the turnaround
      6. Igniting the AI revolution – Salesforce’s rise into the next era
    2. A comprehensive SWOT analysis for Salesforce
      1. Salesforce – strategic inflection point
    3. Leveraging AI and sentiment – Salesforce sentiment-adjusted options straddle
      1. AI, the Rule of 40 (SaaS metric), and sentiment – mastering the Salesforce stock trade
      2. Visualizing the Salesforce strategy – Power BI meets the Rule of 40
    4. ActivistGPT – activist persona
      1. ActivistGPT – LangChain, ChatGPT, and Streamlit activist AI agent
    5. Open source versus proprietary LLMs
      1. Proprietary models
      2. Open source models
      3. Future of open source versus proprietary models
      4. Best model choice for finance use cases (investing, trading, and financial analysis)
      5. Best model for Power BI narratives – data visualizations
      6. Other major factors when training LLMs
      7. Data quality versus data size
      8. What is OpenAI doing about open source model competition?
    6. Summary
  13. Chapter 6: SVB’s Downfall and Ethical AI: Smart AI Regulation
    1. The pastry chef’s tale – unpacking the collapse of SVB
      1. The silicon storm – dissecting the downfall of SVB
    2. Harnessing the social pulse – the Sentinel Strategy for banking trading decisions
      1. Obtain the Twitter (now X) API (if you don’t have one already)
      2. Data collection
      3. Next steps – pre-processing, applying NLP, and quantifying sentiment
      4. Pre-processing, NLP application, and quantifying sentiment
      5. Tracking traditional indicators
      6. Formulating trading signals
      7. The backtest strategy
      8. Implementing the strategy
    3. Implementing the Financial Fortress trading strategy – a data-driven approach using Python and Power BI
      1. The steps to obtain a FRED API key
      2. Portfolio rebalancing
      3. Risk management
    4. Integrating Twitter (now X) sentiment and CAR – Power BI data visualization
      1. Extracting the data
      2. Loading data into Power BI
      3. Transforming data
      4. Visualizing data with a heat map
    5. Revolutionizing Financial Oversight with BankRegulatorGPT – An AI Persona
      1. Regulatory Actions and Audits – Provide official confirmation of a bank’s financial health
      2. BankRegulatorGPT – Langchain, GPT-4, Pinecone, and the Databutton financial regulation AI agent
      3. BankRegulatorGPT (reflecting traits from leading regulatory bodies such as the Federal Reserve, the Office of the Comptroller of the Currency, and the Federal Deposit Insurance Corporation)
    6. Implementing the Regional Bank ETF trade – a commercial real estate strategy
      1. Visualizing the ETF trade – a Power BI dashboard for the commercial real estate market
      2. The importance of smart AI regulation – navigating pitfalls and seizing opportunities
      3. Navigating the AI revolution – a cautionary tale from the lack of regulation in social media
      4. Global cooperation – a key to ethical AI in finance
      5. AI regulation – a necessary safeguard for the future of finance
      6. AI regulation – a balancing act in the future of finance
      7. AI regulation and legislation – a comprehensive timeline
    7. Summary
  14. Chapter 7: Moderna and OpenAI – Biotech and AGI Breakthroughs
    1. The blockbuster saga – understanding the success of Moderna’s COVID-19 vaccine
    2. Moderna’s mRNA odyssey and the transformation of biomedicine
      1. The impact of mRNA-1273 – battling a pandemic
      2. Harnessing the power of mRNA – a new medicinal frontier
      3. Applications across medical domains
      4. Redefining vaccine development
      5. A new paradigm for pharmaceutical innovation
      6. Strategic partnerships and collaborations
    3. SWOT analysis of Moderna’s strategic landscape
    4. The integration of AI and quantum computing in Moderna’s therapeutic landscape
      1. AI in Moderna’s drug discovery process
      2. AI in Moderna’s clinical trials
      3. AI in Moderna’s pharmacovigilance and post-marketing surveillance
      4. AI in Moderna’s supply chain and manufacturing efficiency
      5. AI in Moderna’s drug development strategy
      6. Integration with quantum computing
    5. The future reimagined – Moderna’s AI-driven symphony in medicine and biotechnology
      1. Moderna – orchestrating the AI symphony in biotechnology
      2. The collaboration with IBM – a milestone in innovation
      3. Digital infrastructure – a backbone of innovation
    6. A new chapter – the Moderna-IBM partnership
      1. IBM partnership – quantum computing and AI
    7. Moderna’s AI Academy – a partnership with CMU for technological innovation
      1. Moderna’s AI Academy in partnership with CMU
    8. Confronting future pandemics – Moderna’s innovation in multi-valent vaccines and AI-driven antivirals
      1. Revolutionizing cancer care – Moderna’s mRNA ambitions in oncology
      2. The brave new world of medicine – Moderna’s pioneering path to personalized therapies
      3. Moderna’s strategic move toward outsourcing pharma manufacturing
    9. Moderna Momentum – a data-driven, sentiment-sensitive strategy for an mRNA masterstroke
    10. The future of biotech trading – the Moderna Momentum trade visualization
      1. Prerequisites
    11. Introducing the future of drug development and regulatory approval with FoodandDrugAdminGPT – an AI persona
    12. Unleashing collaborative intelligence – Microsoft Jarvis (GitHub)
      1. A new epoch in AI – the multifaceted excellence of HuggingGPT and its integration with Gradio models
      2. Unleashing creativity with Gradio – a gateway to simplified demos and GUIs for Hugging Face models
      3. Choosing the right AI model – HuggingGPT (Jarvis) versus GPT-4 for domain-specific expertise
      4. Harnessing specialized intelligence – FoodandDrugAdminGPT’s implementation using HuggingGPT for multimodal solutions in the regulatory landscape
      5. HuggingGPT model and Gradio demo
    13. Section 1 – investment insight with FoodandDrugAdminGPT – a comprehensive query guide
      1. Why it matters
    14. Section 2 – Moderna’s drug pipeline – tailored insight for investment and Wall Street analysis
      1. Why it matters
    15. Section 3 – Unlocking Moderna’s pipeline – critical questions for investors using HuggingfaceGPT
      1. Why it matters
      2. Overall implications
      3. Section 1 – investment insight with FoodandDrugAdminGPT – a comprehensive query guide
      4. Section 2 – Moderna’s drug pipeline – tailored insight for investment and Wall Street analysis
      5. Section 3 – unlocking Moderna’s pipeline – critical questions for investors using HuggingfaceGPT
    16. Revolutionizing biotech with GPT-4 – Moderna’s pathway to accelerated drug discovery
      1. OpenAI’s pinnacle against tech giants
      2. OpenAI and Moderna – a new frontier in drug discovery
      3. OpenAI’s history and focus on AGI
      4. OpenAI’s AGI initiatives – a trailblazing journey toward intelligence revolution
      5. AGI – alignment and why it matters – conducting the symphony of intelligence
      6. AGI principles and future scenarios in finance – your financial partner of tomorrow
    17. Summary
  15. Chapter 8: CrowdStrike: Cybersecurity in the Era of Deepfakes
    1. The concert and cybersecurity analogy – concert security for the digital stage
    2. GPT-4, multimodal activity, and financial exposure – a cautionary tale
      1. The multimodal capabilities of GPT-4
      2. Amazon One and the age of biometrics
      3. Cybersecurity risks in finance
      4. The implications for data visualization
      5. Protecting sensitive information
      6. Understanding CrowdStrike’s security capabilities
      7. CrowdScore – a paradigm shift in threat management
      8. The SCORE analysis of CrowdStrike – navigating financial cyber risks and opportunities
    3. CrowdStrike and Dell Technologies: a strategic alliance in commercial cybersecurity
      1. The alliance: building a comprehensive cyber defense
      2. Financial implications and cybersecurity
      3. The power of data visualization
      4. Conclusion: the future of cybersecurity and finance
    4. Analyzing CrowdStrike’s earnings call transcripts with AI and NLP
      1. The role of earnings call transcripts in finance
      2. Aggressive trading (using options) – buying call options on Beazley and Hiscox and selling put options on CrowdStrike
      3. Example functions with highlighted replacement areas
      4. Conservative trading (using stock) – buying stock in Beazley and Hiscox and buying stock in CrowdStrike once it falls 5% from its current price
      5. Example functions with highlighted replacement areas
    5. The ultimate guide to investment dashboards – Power BI meets ChatGPT
      1. Power BI visualizations
      2. Aggressive trading using options on Beazley, Hiscox, and CrowdStrike
      3. Conservative trade: buying stock in Beazley, Hiscox, and CrowdStrike after a 5% fall
      4. Power BI alert configuration (example for CrowdStrike put alert but can be used for Crowdstrike stock alert too)
      5. Harnessing Python’s power for aggressive trading: a code-driven odyssey
      6. The Zen of conservative trade: unleashing Python for steady gains
    6. Visual alchemy: transmuting raw data into golden insights with Power BI
      1. Creating Power BI visualizations
    7. Integration with ChatGPT (GPT-4)
    8. HackerGPT (AI Persona) – monitoring and analyzing cybersecurity regulatory changes and breaches
      1. HackerGPT – reflecting traits from leading cybersecurity experts
      2. HackerGPT meets FinGPT – a comprehensive guide to analyzing the financial cybersecurity landscape
    9. Revolutionizing the future of AI-driven development with MetaGPT – the ultimate catalyst for multi-agent systems
      1. What is MetaGPT?
      2. Role-based collaboration in MetaGPT
      3. MetaGPT workflow
    10. Introduction to the MetaGPT model (cybersecurity investment opportunities)
      1. Roles and responsibilities
    11. Compromising real-world LLM-integrated applications with indirect prompt injection
    12. Future-proofing LLMs – solutions on the horizon
    13. Deepfakes and their multi-faceted impact – a closer look with AI and data visualization
      1. AI literacy – your passport to the future
      2. Navigating AI’s landscape – considerations and guidelines
    14. Summary
  16. Index
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Product information

  • Title: The Future of Finance with ChatGPT and Power BI
  • Author(s): James Bryant, Aloke Mukherjee
  • Release date: December 2023
  • Publisher(s): Packt Publishing
  • ISBN: 9781805123347