Should You Take That Startup Equity? Use This Calculator to Find Out
By
Samara Garcia
•
Feb 23, 2026
A senior ML engineer is choosing between two offers. One is a fast-growing AI startup with meaningful equity. The other is Big Tech with predictable RSUs. Both look competitive on paper, but only one could change their financial future. The real question is not salary. It is how to value risk versus upside.
That is where the cost of equity matters. It explains the return someone needs to justify taking startup stock instead of guaranteed cash or low-risk investments. Using simple models like CAPM, engineers and hiring leaders can compare volatility, growth potential, and real expected value instead of relying on gut instinct.
Key Takeaways
A cost of equity calculator uses the capital asset pricing model (CAPM) to estimate the required return on startup equity, helping you determine if an offer fairly compensates you for risk.
The CAPM formula, Re = Rf + β × (Rm − Rf), combines the risk-free rate, beta, and market risk premium to output a percentage like 9% or 15%, representing the minimum return you should expect.
Startup equity typically requires a much higher expected return (15–25%) than FAANG RSUs (7–12%) because of elevated volatility and illiquidity.
Fonzi AI’s Match Day format helps startups and candidates align on fair, transparent compensation by requiring upfront salary commitments and using structured, bias-audited evaluations.
This article includes a ready-to-use CAPM framework and comparison table so you can build your own calculator in Excel or adapt it for hiring conversations.
What Is the Cost of Equity? (And Why It Matters for Startup Compensation)
Cost of equity is the minimum rate of return that equity investors demand for holding shares in a company. Unlike cost of debt, which is simply the interest a company pays on borrowings, the cost of equity reflects the opportunity cost and risk premium shareholders require.
This metric appears in three critical contexts:
Investor valuation: VCs and institutional investors use the cost of equity to calculate discount rates for future cash flows when pricing funding rounds.
Company hurdle rates: CFOs use it as the benchmark return that new projects must exceed to create shareholder value.
Employee offer evaluation: When you accept more equity and less salary, you’re effectively investing at that required rate of return.
Consider a Series B AI startup raising at a $250M valuation in 2025. Investors backing that round typically expect 18–25% annualized returns to compensate for the substantial risk profile, far above the historical 9–11% total return for public markets. When an engineer accepts equity instead of cash, they’re implicitly accepting that same cost of capital threshold.
While sophisticated investors build full discounted cash flow models, most hiring managers and candidates can get 80% of the insight from a straightforward CAPM-based estimate. The formula provides a reasonable baseline without requiring a corporate finance degree.
How the CAPM Cost of Equity Calculator Works
The capital asset pricing model is the standard academic and Wall Street framework for connecting expected return to market risk. It answers a simple question: what return should I expect from this particular investment, given how volatile it is relative to the overall market?
The core capm formula is:
Cost of Equity (Re) = Rf + β × (Rm − Rf)
Here’s what each component means:
Rf (Risk-Free Rate): The yield on a default-free government bond, typically the 10-year US Treasury. This represents the return you could earn with virtually zero volatility.
β (Beta): A measure of how sensitive the asset is to market swings. A beta of 1.0 means the stock moves in line with the market; a beta above 1.0 indicates more risk.
Rm − Rf (Equity Risk Premium): The extra return the market provides over risk-free assets, historically around 4–6% based on long-run S&P 500 data.
A web-based capm calculator or Excel sheet automates this relationship. You input your assumptions for each variable, and the tool outputs Re, your required rate of return, often displayed as a percentage like 9% or 13.5%.
CAPM Formula and Components: Step-by-Step
Before trusting any cost of equity calculator output, you need to understand what drives the numbers. Each component in the capm equation has meaningful implications for how you interpret risk.
The full-form relationship states that the expected rate of return on equity equals the risk-free rate plus beta times the equity risk premium. Small changes in any input can meaningfully shift your output.
For example, using Rf = 4.2%, Rm = 9.5%, and beta = 1.3:
Re = 4.2% + 1.3 × (9.5% − 4.2%) = 4.2% + 1.3 × 5.3% = 4.2% + 6.89% = 11.09%
Change beta to 1.8, and the result jumps to 13.74%. That difference represents real money when evaluating equity grants.
Component 1: Risk-Free Rate (Rf)
The risk-free rate typically uses the yield on default-free government bonds matching the duration of expected cash flows. In the US, the 10-year Treasury yield serves as the standard benchmark.
In late 2025 and early 2026, risk-free rates are no longer an afterthought. Treasury yields sit around 4–5%, which sets a much higher baseline for any equity offer. When you build a cost of equity calculator, pull a recent average from Yahoo Finance or the Federal Reserve and treat it as the minimum return investors expect.
The implication is simple but powerful. If Treasuries pay 5%, even low-risk equities must clear that bar to be attractive. For startups, this pushes required returns up across the board. And for global or remote first teams, the benchmark may shift between local sovereign yields and USD-denominated bonds depending on where investors anchor their expectations.
Component 2: Beta (β)
Beta measures non-diversifiable risk, specifically, how sensitive a stock or portfolio is to overall market movements. The values are interpreted as follows:
Beta Value | Interpretation |
β = 1.0 | Moves exactly with the market |
β > 1.0 | More volatile than the market (higher systematic risk) |
β < 1.0 | Less volatile than the market |
Public companies have betas calculated from historical data using regression analysis. You can find beta values on Bloomberg, MarketWatch, or Yahoo Finance.
For startups, you must approximate. Here are reasonable guidelines:
Early-stage AI infrastructure startup: β = 1.5 – 2.0
Series B/C SaaS platform with recurring revenue: β = 1.0 – 1.3
Pre-revenue frontier tech company: β = 2.0 – 3.0+
Higher beta directly increases the cost of equity output, reflecting that employees and investors should expect more upside to compensate for elevated volatility.
Component 3: Equity Risk Premium (ERP = Rm − Rf)
The market risk premium represents the extra return investors demand for holding equities over risk-free assets. Based on historical data from long-run S&P 500 performance, this premium typically ranges from 4–6%.
To calculate ERP for your capm model, subtract your chosen risk-free rate from your assumed expected market return:
If Rf = 4.5% and Rm = 9.5%, then ERP = 5.0%
Many corporate finance teams use an ERP of around 5–6% in internal planning models. The market return represents the average return you’d expect from a diversified equity portfolio.
For very high-risk sectors like frontier AI or crypto infrastructure, some practitioners add an additional size premium or startup premium on top of the standard ERP. When talking to candidates about risk, hiring managers can reference this adjustment qualitatively.
Worked CAPM Cost of Equity Example (Including a 9% Output)
Let’s see how a calculator transforms abstract inputs into actionable numbers that help you evaluate a potential investment in startup equity.
Example 1: Lower-Risk Public Tech Company
Suppose you’re evaluating equity at a mature, profitable tech company:
Rf = 4%
Rm = 10%
β = 0.83
Using the following formula:
Re = 4% + 0.83 × (10% − 4%) = 4% + 0.83 × 6% = 4% + 4.98% = 8.98% ≈ 9%
This output suggests the stock is slightly less volatile than the overall market. A 9% expected return is reasonable for this risk profile.
Example 2: High-Growth AI Startup
Now consider a Series B AI startup where you’d estimate higher volatility:
Rf = 4.5%
Rm = 11%
β = 1.7
Re = 4.5% + 1.7 × (11% − 4.5%) = 4.5% + 1.7 × 6.5% = 4.5% + 11.05% = 15.55%
This higher cost of equity reflects the additional risk you’re taking. The startup’s equity must deliver substantially higher returns to justify the volatility and potential returns uncertainty.
Key interpretation points:
A 9% cost of equity implies a relatively stable, lower-risk investment
A 15%+ cost of equity signals high upside but substantial downside risk
Use these percentages to compare equity offers across different companies
Building Your Own Cost of Equity Calculator (CAPM) for Startup Offers
Most readers can build a functional CAPM-based calculator in Excel or Google Sheets in under 20 minutes. Here’s how to structure it:
Step 1: Define Input Cells
Cell B1: Risk-Free Rate (e.g., 4.5%)
Cell B2: Expected Market Return (e.g., 10%)
Cell B3: Beta (e.g., 1.5)
Cell B4: Optional Startup Risk Premium (e.g., 2%)
Step 2: Create the Formula Cell
Cell B6: =B1 + B3 * (B2 - B1) + B4
This calculates Re = Rf + β × (Rm − Rf) + any additional startup premium.
Step 3: Add Usability Features
Consider adding dropdowns for “Company Stage” (Seed, Series A, Series B+) linked to default beta ranges:
Stage | Default Beta | Additional Premium |
Seed | 2.0 | 3% |
Series A | 1.7 | 2% |
Series B+ | 1.3 | 1% |
Step 4: Create a Candidate View Tab
Include outputs that translate Re into intuitive metrics:
Implied multiple vs Treasuries (Re ÷ Rf)
Years to double the value at a given growth rate
Comparison vs historical FAANG average return
Comparing Startup Equity vs FAANG RSUs Using Cost of Equity
A common decision in 2026: an experienced backend engineer choosing between a mid-stage AI startup and a FAANG RSU-heavy role. How do you compare these rationally?
Using CAPM outputs provides useful context. FAANG equity typically has a lower beta (around 1.0) and thus a lower cost of equity, perhaps a 7–10% required return. Startup equity, with a beta ranging from 1.5 to 2.5, may require 15–25% expected returns to justify the risk.
This means an engineer receiving $100,000 in Google RSUs (with a lower required return) might rationally reject $200,000 in startup equity if that startup’s cost of equity is dramatically higher. The risk-adjusted values could be comparable, or even favor the more certain option.
For hiring leaders, understanding this dynamic helps you communicate why your equity package is compelling despite lower certainty. It also helps calibrate grants so candidates feel properly compensated for the discount rate they’re implicitly accepting.
Example Table: FAANG RSUs vs AI Startup Options
Component | FAANG-Like Public Tech | Series C AI Startup |
Risk-Free Rate (Rf) | 4.3% | 4.3% |
Expected Market Return (Rm) | 9.0% | 11.0% |
Beta (β) | 1.0 | 1.8 |
Calculated Cost of Equity (Re) | 9.3% | 16.4% |
Risk Summary | Low volatility, high liquidity | Higher volatility, illiquid until exit |
The higher startup cost of equity reflects the extra return candidates should demand for accepting more volatility and illiquidity in their compensation portfolio.
Limitations of CAPM (And How to Use It Wisely for Offers)
While CAPM provides a foundational framework for pricing risky securities, it relies on simplifying assumptions that don’t always hold in practice.
Single-factor model: The CAPM uses only market risk (beta) as the risk measure, ignoring factors such as size, momentum, and sector dynamics.
Beta estimation challenges: For private startups, you must estimate beta from comparables rather than calculate it from historical price data.
Behavioral realities: Research by Kahneman and Tversky shows that investors don’t always act rationally, contradicting the CAPM’s assumptions about investor behavior.
Illiquidity discount: Employee equity in startups isn’t easily tradeable, so personal risk exposure is often higher than beta-based models suggest.
Practical guidance for hiring teams:
Treat CAPM as a baseline sanity check rather than the precise truth. Layer qualitative factors on top:
Founder quality and execution track record
Runway length and burn rate
Sector dynamics (AI infra vs consumer)
Your personal risk tolerance and financial situation
You don’t need perfect precision. You need a consistent framework so equity offers and narratives are internally coherent during hiring conversations.
How Fonzi AI Helps You Communicate and Structure Equity More Effectively
Fonzi AI is a curated talent marketplace focused on elite AI and engineering roles, where equity is a central component of nearly every offer discussion.
The Match Day format, time-boxed hiring events with upfront salary transparency, helps companies present unified, well-structured compensation packages. Behind the scenes, you can incorporate cost of equity logic to ensure your grants make mathematical sense.
Fonzi uses multi-agent AI for:
Fraud detection to verify candidate credentials
Structured evaluation with consistent scoring criteria
Audited assessments that enhance fairness, reduce bias in recruitment, and lower liability
This automation frees your recruiting team to focus on high-touch activities: explaining equity value, discussing growth trajectories, and helping candidates understand risk-reward tradeoffs.
By combining a CAPM-style cost of equity calculator with Fonzi’s high-signal candidate pool, startups can quickly test different compensation mixes. Offer more equity for candidates seeking earlier-stage risk, or emphasize cash with lower upside for those prioritizing stability.
Summary
CAPM turns equity from a vague promise into a number that candidates can actually reason about. With a simple calculator or spreadsheet, abstract risk becomes a clear percentage that makes startup offers comparable to Big Tech packages.
For hiring AI and engineering talent, this clarity matters. Candidates increasingly expect founders and hiring leaders to explain not just how much equity they’re offering, but what return that risk implies. Teams that can articulate this well win trust and close faster.
CAPM is a starting point, not a verdict. Pair it with judgment about company risk, growth potential, and individual expectations to design equity offers that feel both fair and compelling.
Ready to apply it? Build your cost of equity calculator, then explore how Fonzi AI helps you source, evaluate, and close top-tier engineers who value data-backed compensation and thoughtful hiring.
