ChatGPT/AI for Finance Professionals: Investing & Analysis

Explore what, why, and how of section two, mastering basic and advanced prompting—from role and few-shot prompts to data structuring with tables. Practice with real-life prompts to boost research quality.

Explore prompts and role prompting with custom instructions to define your AI persona for finance research, using Pablo the financial analyst with CFA and MBA, for concise, table-ready, 360-degree analysis.

Learn how few-shot prompting guides ai like ChatGPT to output in specific formats for finance reporting, with markdown tables and up-to-date sources.

master chain of thought prompting by breaking complex finance tasks into sequential prompts, generating structured analyses like buy vs build and IP ownership tables, and improving coherence and relevance.

Apply in style prompting to convert financial bullet points into sentences in the voice of a chief financial officer or investor relations executive for press release style communications.

Extract information from data and structure it into a markdown table with ChatGPT for earnings reports, sec filings, and executive summaries.

Learn to summarize long texts with ChatGPT and other large language models for finance professionals, using role-based prompts, output formats, and title generation, demonstrated on press releases and finance-focused examples.

Explore the five AI risks in finance, including data security, copyright, bias, and governance, ethics, and regulatory guidance for responsible use of AI tools like ChatGPT and Bart.

Provide five-step prompts to configure ChatGPT for finance executives, covering custom instructions and explanations of income statements, balance sheets, and cash flows with real-life examples.

Apply a five-step prompt workflow in chatgpt for finance: customize instructions, deliver concise bullet-point answers with tech-company examples, and format income, balance, and cash flow prompts.

learn how to access financial data using bing, google, bard, and cloud tools and import it into excel, google sheets, or pdfs to save time in financial modeling.

Learn practical methods to pull financial data from websites and documents using ChatGPT, then export to Excel, Google Sheets, PDF, or CSV with formatted tables.

Learn to pull Microsoft income statements from sec.gov into a table and export to Excel or Google Sheets using Bing Chat, Bard, and Claude, including large-file uploads.

Open the attached pdf, copy its data into a ChatGPT table, add a 2022–2023 year-over-year column, and download the result as Excel; optionally use Claude to recreate the table.

Demonstrates using ChatGPT to convert data into a table, render markdown formats, and export to excel, csv, pdf, or word, then compute the percent year-over-year change between 2022 and 2023.

Learn a six-part investment research framework and a 100-page template using AI prompts and ChatGPT to build qualitative, quantitative, and financial analyses.

Learn to conduct qualitative and quantitative investment research using excel-based financial statements, including income statements, balance sheets, and three valuation methods: price to revenue, price to earnings, and DCF.

Perform qualitative analysis of a company's management team, starting with the CEO and CFO, assessing founder involvement, strengths and weaknesses, investor sentiment, and board influence using AI prompts.

Analyze company history with chatgpt by assessing material pivots since founding, using examples like intel, and generating follow-up due diligence questions for robust investing analysis.

Analyze a company's products and services with a ChatGPT prompt to generate strengths, weaknesses, and descriptions. Learn to create revenue charts from data and integrate them into our research report.

Explore how catalysts spark investor interest and how drivers shape stock performance across sectors, with examples from Apple product launches, The Hunger Games films, and same-store sales.

Analyze cyclical and secular trends to gauge a company's performance through economic cycles and long-term market shifts, using healthcare, iPhone pricing, and smartphone adoption as examples.

Analyze a company's target market with ChatGPT, focusing on consumer devices like iPhone and iPad, China as market, and enterprise and automotive opportunities, with due diligence tips and data insights.

Learn to use ChatGPT to identify direct and indirect competitors, capture names, websites, products, advantages, and disadvantages, and compile sources into a comprehensive competitive landscape.

Analyze production and distribution by comparing direct sales with higher margins to indirect channels, using Apple stores, Best Buy, and Udemy as practical examples.

Explore top suppliers and components using ChatGPT, including Foxconn, Samsung, and Broadcom, assess geopolitical risk, and generate revenue-exposure tables for Apple suppliers.

Analyze commodities exposure across a company’s supply chain, including inputs from copper and aluminium. Assess hedging policies and use ChatGPT for due diligence on silicon, cobalt, and rare earths.

Compare internal versus outsourced r&d and decide when to buy versus build, using a ChatGPT prompt to analyze whether a company can invest and produce products, and generate charts.

Explore intellectual property analysis using ChatGPT, covering copyrights, trademarks, and patents, with guidance on expiry dates, official databases, and due diligence for tech companies.

Identify material lawsuits and their dollar amounts from 10-K risk sections, compile them into a table, and visualize trends using ChatGPT and up-to-date search tools.

Explore ethics research on a company by tagging topics like sustainability and environmental responsibility, and use ChatGPT to analyze accusations of unethical practices, accounting fraud, and price fixing abuses.

Use ChatGPT to perform customer service due diligence by analyzing Yelp, Twitter (X), and consumer reports, noting Apple store insights, and the link between customer service quality and profits.

Explore how recruiting strategy and turnover shape retention, quantify average tenure, and analyze stock option retention via four-year vesting (25% per year) and golden handcuffs that encourage staying.

Analyze a company's sales strategies using upselling, cross-selling, and calls to action, and apply ChatGPT prompts for pricing, advertising, contingency plans, GDPR, and competitive insights for finance professionals.

Explore how corporate culture shapes risk taking and innovation using ChatGPT analysis of Apple’s culture, embracing mistakes, emotional branding, and creating new markets.

Porter five forces framework with ChatGPT to analyze supplier power, buyer power, rivalry, substitution, and new entrants, using Apple as a practical example.

Navigate the four phases of the product life cycle—introduction, growth, maturity, decline—and apply this framework to assess product position with ChatGPT and examples like Apple VR and IBM mainframes.

Explain the Boston Consulting Group framework and how to map products to star, cash cow, dog, and question mark using Apple as an example, with Bard and ChatGPT prompts.

Explore SWOT analysis using ChatGPT to assess Apple, detailing strengths (brand, halo ecosystem), weaknesses (iPhone dependence, closed ecosystem), opportunities (AR/VR, Apple TV), and threats (regulation, competition).

Map a company's merger and acquisition history with ChatGPT, capture large deals and cash or stock terms, and visualize a chart of past deals with product portfolio gaps and competition.

Use ChatGPT to analyze a company's corporate strategy with open-ended prompts. Highlight ecosystem building, vertical integration, consumer experience, global expansion, strategic partnerships, diversification, and data driven decision making.

Master quantitative research and total addressable market analysis using Apple, the $20 billion TAM threshold, and AI prompts to calculate TAM for financial modeling.

Analyze market growth and total addressable market for each product using ChatGPT, Bard, and Bing Chat; compare up-to-date results and generate a chart for the report.

Perform quantitative market share research using prompts to extract market share for each product, rank the top products and compare with competitors, and visualize results with multiple charts.

Learn to analyze geographic revenue exposure using ChatGPT and Bard to pull top ten country data, compare results, export charts, and capture future exposure comments.

Analyze vertical exposure with ChatGPT and multiple AI tools, compile verticals and percent revenue, identify overexposure, explore current and future opportunities, and create charts for finance research reports.

Learn to analyze a company's product exposure using chatgpt by ranking products by revenue and percent of revenue, tagging key items, and generating revenue charts.

Analyze foreign exchange exposure and constant currency growth across currencies using ChatGPT, Bard, and Bing chat, and assess hedging policies with derivatives to offset currency volatility.

Learn to obtain average selling price and volume data with ChatGPT, applying price and volume as revenue drivers for cyclical and commodity stocks. Create charts from results.

Use ChatGPT prompts with cost tags to analyze the cost of production and cost of goods sold per unit. Generate charts for the largest products to support due diligence.

Quantify inventory from a research perspective using ChatGPT, compute inventory turnover as cost of goods sold divided by average inventory, and assess how high inventory can bankrupt a company.

Learn to calculate a customer's lifetime value using gross profit, churn, and retention, and apply it to advertising budgets with examples from Amazon, Coca-Cola, and Apple.

Analyze cost of acquisition (CAC) by comparing online campaign metrics to revenue per customer, illustrated with Apple’s 10-K calculation and Bard analyst estimates.

Analyze customer concentration risk by applying the 5% revenue rule and screening for 10% plus customers, using ChatGPT or cloud AI to review disclosures in annual reports and 10-Ks.

Analyze shareholder concentration by listing holders and changes, including activist investors such as Carl Icahn who unlock value. Compare growth versus value investors and investment purgatory with eBay and PayPal.

Analyze a company's employees and locations, including outsourced staff and turnover, for geopolitical and currency risk, using ChatGPT, Bard, and Bing chat to synthesize insights.

Analyze insider buying and selling data with ChatGPT, perform regression to assess price impact, and focus on chief executive officers and founders using form filings.

Explore how global GDP growth correlates with company revenue across industries, highlighting cyclical and countercyclical patterns, using World Bank and IMF data.

Learn to analyze MAU and DAU data, and their correlation with revenue growth and profitability for social media firms, using ChatGPT, Bard, and Bing Chat.

Analyze the link between social media followers and revenue using regression with ChatGPT, Bard, and Bing Chat, then explore historical website presence via the Wayback Machine for due diligence.

Conduct financial research using ChatGPT to analyze stock details, guidance, historical revenue and margins, and competition, then build a financial model and value the company.

Learn to pull stock details with ChatGPT, Bard, and Bing Chat, including ticker, price, volume, beta, and top competitors, and to chart market capitalization data.

Understand revenue and earnings guidance, ranges, and midpoints, and how analysts model them. The lecture warns about AI hallucinations and urges double-checking data with actual press releases.

Analyze revenue and EPS results versus expectations using ChatGPT, Bard, and Bing Chat to streamline data gathering, compare with Wall Street estimates, and note limitations.

Learn to analyze historical revenue growth with ChatGPT, compute year-over-year changes, and explain drivers for gains and declines; normalize trends for seasonality and accurate forecasting.

Analyze competitors' historical revenue growth by compiling top ten peers' revenue data and generating charts with ChatGPT, Googlebot prompts, and embedded visuals for clear, data-driven insights.

Analyze historical EPS growth for public companies using ChatGPT, building a 20-year EPS table, comparing year-over-year changes with revenue trends, and validating data with gap versus non-gap accounting.

Analyze the competition's historical eps growth by compiling quantitative eps data for the top ten competitors, including the most recent and prior year, using a Bard workflow.

Understand how the income statement works, starting from revenue to margins. Forecast revenue to model COGS, gross profit, operating and net margins, depreciation, EBITDA, GAAP vs non-GAAP, and cash flow.

Learn how a balance sheet links assets, liabilities, and equity, with current and long-term items, retained earnings, and the relationship to the income statement and returns on assets and equity.

Learn how the cash flow statement explains cash changes by starting with net income and adjusting for depreciation, accounts receivable, inventory, and accounts payable in operating, investing, and financing activities.

Compute gross profit as revenue minus cost of goods sold and gross profit margin as gross profit divided by revenue, illustrated with Apple's 1,000 revenue and 300 cost.

Analyze the ten largest competitors' historical gross margins with ChatGPT and visualize results via a bar chart. Highlight that software and internet-based models yield higher gross margins.

Analyze Apple's historical operating margin by comparing operating profit to revenue, explain EBITDA equivalence, and discuss drivers such as revenue growth and expense reduction, with a ChatGPT-generated 20-year chart.

Paste the competition's historical operating margin into ChatGPT and generate a bar chart for your document; Microsoft shows the highest margins due to software efficiency and low inventory.

Explore price to earnings and price to revenue to value companies, linking earnings per share and earnings growth to multiples, peg, and future cash flow valuation.

Analyze historical price-to-earnings and price-to-earnings growth (PEG) ratios, compute the PEG from P/E and EPS growth, and emphasize double-checking data when using AI tools.

Analyze historical PE and PEG valuations of the five largest competitors, compare PE, EPS growth, and PEG ratios using ChatGPT and Bard, and chart the results.

Explore valuing a company with the price to revenue ratio, using Apple as an example, and note the ratio can stay above the S&P 500 average.

Analyze the biggest competitors' price-to-revenue ratios, extract the five largest figures, and export them to sheets or paste into a research report using Bard and ChatGPT for visualization.

Analyze seasonality on a quarterly basis by examining fiscal year timing, quarter over quarter changes, and seasonality factors to inform the income statement in a financial model.

Analyze accounting red flags by verifying auditor changes with AI, identifying the auditor (Deloitte vs KPMG) and explaining reasons, then cross-check with official sources like SEC.gov and Apple's investor relations.

Spot CFO change red flags with ChatGPT by questioning resignation reasons, verifying turnover, and cross-checking executive tenure, as illustrated by Apple’s CFO tenure example.

Analyze how accounts receivable growth can outpace revenue, why the cash flow from operations matters, and how to assess accounts receivable versus revenue using a financial model and ChatGPT.

Learn how bookings equal revenue plus the change in deferred revenue, and how deferred revenue as a balance sheet liability signals future pipeline health, illustrated with Oracle and Apple examples.

Analyze inventory with cost of goods sold to flag liquidity risks. Compare inventory growth to cost of goods sold on the balance sheet, and review quick and working capital ratios.

Learn to identify earnings restatements and their impact on investor confidence in management. Use Apple’s history of reclassifications and disclosures to distinguish benign errors from material restatements.

Analyze changes in revenue disclosure, comparing granular line items to totals, and distinguish organic from non-organic growth while noting the impact of large acquisitions by Microsoft and Oracle.

Analyze organic versus non organic revenue growth to identify red flags in earnings. Review case studies of acquisitions like LinkedIn and the buy versus build dynamic.

Compare GAAP and non GAAP accounting, and learn how the cash flow statement reconciles cash and non cash items, including depreciation and stock compensation.

Explore changes in revenue recognition and how to verify them by consulting the 10-K and official sources such as investor relations and sec.gov, using ChatGPT to navigate the process.

Analyze material charges and write-offs to evaluate a company's cash balance, noting one-time events, kitchen-sink quarters, and examples like inventory write-downs and iPhone sales charges, with ChatGPT and Bard.

Analyze material lawsuits related to accounting practices for Apple, using ChatGPT to locate sources and assess billion-dollar cases like defective batteries and Apple Pay, with discussion on competition.

Identify additional accounting concerns using ChatGPT, review revenue recognition, supply chain disruption costs, inventory valuation and write-downs, and ESG data gaps to inform financial modeling.

Build a financial model to forecast revenue, income statement, balance sheet, and cash flow, then value the company via discounted cash flow, price-to-earnings, and price-to-revenue, with your own assumptions.

Explore 25 modeling and valuation best practices, focusing on forecasting revenue, treating most items as a percent of revenue, and spotting patterns and sector-specific drivers.

Master discounted cash flow and net present value concepts, build a sensitivity analysis with bearish/neutral/bullish scenarios, and refine target prices using growth, WACC, and TAM.

Explore revenue analysis with historical Apple data and build income statements using AI tools, Excel, Google Sheets, and sec.gov filings to assemble credible financial statements.

Discover adding financial data to models with ChatGPT and Bard, while avoiding hallucinations by sourcing directly from 8-K reports and company releases.

Forecast revenue from historical trends and normalize for black swan events, then document data sources and notes in the model, emphasizing primary sources like press releases and 10-K filings.

Explore income statement analysis and forecasting, focusing on revenue, gross profit, EPS, and cash flow, with DCF valuation and free cash flow concepts using Apple as a case study.

Forecast your financial statements and value the company with three methods—discounted cash flow, price to earnings, and price to revenue—and blend targets to set a price target.

Calculate a company's value with discounted cash flow by forecasting five years of free cash flow, determining terminal value, and applying the weighted average cost of capital.

Compute terminal value from the final year cash flow using long-term growth, then discount with WACC and perform sensitivity analysis to estimate equity value and a target price.

Explore price to revenue valuation by entering stock price and cost of capital, computing market cap, applying revenue multiples, and deriving bullish, bearish, and just right targets.

Explore price to earnings valuation and target prices across bearish, just right, and bullish scenarios, using earnings growth, p/e ratios, and discounting with WACC or DCF.

Compute blended average target price by averaging the three methodologies—dcf bullish, bearish, and just right—then paste the results into the average valuation alongside price to revenue and price to earnings.

Learn how to apply technical analysis—RSI, 50- and 200-day moving averages, channel formations, and the VIX—after fundamentals and valuation to inform prudent trading decisions.

Learn to perform technical analysis with ChatGPT, Bard, and Bing Chat. Examine relative strength index (RSI), 50- and 200-day moving averages, short interest ratio, options activity, and support and resistance.

Use ai to create a one-page executive summary from the research document by uploading to cloud ai, then extract qualitative research, financial research, technical analysis, and conclusions, and verify data.