The CFA Analyst Playbook

Remember the following for this analysis session: - Focus company/portfolio: [ticker or company name] - Analysis purpose: [investment decision / client report / portfolio review / risk audit] - Risk tolerance: [conservative / moderate / aggressive] - Benchmark: [S&P 500 / sector ETF / custom] - Time horizon: [short-term / 1 year / 5 years] - Reporting style: [executive summary / detailed technical / academic] Generate all charts and show calculations.

Run a 3-stage DCF valuation on [TICKER]: - Stage 1: 5-year high growth at [X%] revenue CAGR - Stage 2: 5-year transition to [X%] growth - Stage 3: Terminal growth at [X%] - WACC: [X%] - Use the last 3 years of actual financials as base Show the DCF model, sensitivity table (WACC vs terminal growth), and implied share price vs current market price. Generate a waterfall chart of value components.

Value [TICKER] using 5 different methods: 1. DCF (free cash flow to firm) 2. P/E multiple (vs sector average) 3. EV/EBITDA (vs sector average) 4. Price-to-Sales 5. Dividend Discount Model Compare and reconcile the values. What is your blended fair value? Show a football field chart with all ranges.

Calculate intrinsic value using Residual Income Model for [TICKER]. Use a [X%] cost of equity and [X%] long-run ROE convergence. Show: book value per share, residual income per year, and present value breakdown.

Build an efficient frontier for this portfolio: [TICKER1 XX%, TICKER2 XX%, TICKER3 XX%, TICKER4 XX%, TICKER5 XX%] Use 3 years of daily return data. Show: - Current portfolio position on the frontier - Minimum variance portfolio weights - Maximum Sharpe ratio portfolio weights - Plot the frontier with annotated key points Also calculate: annual return, volatility, Sharpe ratio, Sortino ratio, and maximum drawdown for the current allocation.

Run a factor exposure analysis on my portfolio using the Fama-French 3-factor model: [List tickers and weights] Report: alpha, beta, size factor loading, value factor loading. Include R-squared, t-statistics, and p-values. Is the alpha statistically significant at 95% confidence? Plot factor exposure as a radar chart.

Calculate rolling 30-day Sharpe ratio, Sortino ratio, and maximum drawdown for this portfolio over the last 2 years: [List tickers and weights] Plot all three metrics on the same timeline. Highlight periods where Sharpe < 0 and drawdown > 10%.

Price a European call option using Black-Scholes: - Underlying: $[price] - Strike: $[strike] - Risk-free rate: [X%] - Time to expiry: [X days] - Implied volatility: [X%] Calculate all Greeks (Delta, Gamma, Vega, Theta, Rho). Plot the P&L diagram at expiry. Show how each Greek changes as spot price moves +/- 20%.

Create an options payoff diagram for a [long strangle / iron condor / bull call spread / protective put]: [Describe legs: buy/sell, call/put, strikes, premiums] Stock currently at S=[price]. Mark: breakeven points, max profit, max loss, profit zones. Calculate the probability of profit using implied vol.

Build a binomial options pricing tree with 5 steps: - American call and put - S=[price], K=[strike], r=[X%], T=[X year], sigma=[X%] Show the full tree with stock price and option value at each node. Highlight early exercise nodes for the American put.

Calculate 1-day 95% and 99% VaR for this portfolio using three methods: [List tickers and weights] 1. Historical simulation (252 trading days) 2. Parametric (variance-covariance) 3. Monte Carlo (10,000 simulations) Compare the results and explain the differences. Show the return distribution histogram with VaR lines marked. Which method is most conservative? Why?

Run a Monte Carlo stress test with 10,000 scenarios for my portfolio: [List tickers and weights] What is the expected loss in the worst 5% of scenarios? Show: distribution histogram, loss at percentiles (1%, 5%, 10%), expected shortfall (CVaR), and the 5 worst simulated scenarios. Overlay with a 2008-style crash scenario and a COVID-style drawdown.

Perform credit risk analysis on this bond portfolio: [List bonds: issuer, rating, coupon, maturity, face value] Calculate for each position: - Probability of Default (PD) - Loss Given Default (LGD) - Expected Credit Loss (ECL) Aggregate to portfolio-level expected loss. What is the credit VaR at 99% confidence?

Build a full LBO model: - Entry EV: $[X]M at [X]x EBITDA - EBITDA: $[X]M, growing at [X%]/year - Debt: [X%] of purchase price at [X%] interest - Hold period: [X] years - Exit multiple: [X]x EBITDA Show: IRR, MOIC, cash-on-cash return. Generate a sensitivity table: entry multiple vs exit multiple. Plot the debt paydown waterfall and equity value bridge.

Analyze this acquisition scenario: - Acquirer: [Company A] (P/E [X]x, EPS $[X]) - Target: [Company B] (P/E [X]x, EPS $[X]) - Deal: [100% stock / 100% cash / mixed], [X%] premium Calculate: EPS accretion/dilution, breakeven synergies needed, pro-forma P/E, and the impact on acquirer's share price. At what synergy level does the deal become accretive?

Run a CAPM regression for [TICKER] against the S&P 500 using 24 months of monthly return data. Report: alpha, beta, R-squared, t-statistics, p-values. Is the alpha statistically significant at 95% confidence? Plot the security market line with the stock's position.

Build an ARIMA model to forecast quarterly revenue for [TICKER or company] for the next 4 quarters. Use the last 5 years of quarterly revenue data. Show: model parameters (p,d,q), fitted values, forecast with 95% confidence intervals. Plot actual vs fitted vs forecast.

Backtest a [momentum / mean-reversion / value] strategy on the S&P 500: - [Describe entry/exit rules] - Rebalance every [X months] - Period: [start year] to [end year] Report: annual return, Sharpe ratio, max drawdown, win rate, avg gain/loss ratio. Compare vs buy-and-hold benchmark. Plot cumulative returns for both.

Compile all analysis from this session into a professional investment report: Structure: 1. Executive Summary (1 page) — key findings and recommendation 2. Valuation Analysis — DCF, multiples, blended fair value 3. Portfolio Context — risk metrics, factor exposure 4. Risk Assessment — VaR, stress test results 5. Technical Analysis — CAPM, momentum signals 6. Investment Recommendation — BUY / HOLD / SELL with price target 7. Key Risks — what could go wrong Tone: institutional client-facing. Include all charts generated.

Create a 10-slide investment analysis presentation: - Style: Sharp Minimalism - Image model: gemini-2.5-flash-image Slides: 1. Title — Investment Analysis: [TICKER] 2. Executive Summary — key metrics and recommendation 3. Valuation — football field chart with DCF + multiples 4. Financial Overview — revenue, margins, growth trends 5. Portfolio Fit — how this fits the portfolio 6. Risk Profile — VaR, stress test results 7. Technical Signals — CAPM, momentum, mean reversion 8. Competitive Position — vs sector peers 9. Investment Thesis — bull case, bear case, base case 10. Recommendation — price target, risk/reward, timeline Export as PPTX.