7 Real CAPM Examples That Will Transform How You See Modern Markets
The Capital Asset Pricing Model (CAPM) stands as the cornerstone of MBA investment courses, even though experts developed it decades ago. This powerful framework connects risk and expected returns, especially with stocks. The model lets you measure systematic risk exposure, required risk premiums, and the cost of equity capital that shapes investment decisions.
The CAPM formula calculates expected returns based on an asset's beta, the risk-free rate, and the equity risk premium. U.S. stocks show an average excess historical annual return of about 7.5%. Real-life markets need specific adaptations of CAPM to work effectively. The model's simplicity and versatility make it popular among investors of all types, despite its theoretical limitations and simplified assumptions.
Fixed Income Investors showcases seven practical CAPM applications that show how this fundamental finance theory works in today's complex markets. These examples will revolutionise your grasp of contemporary investors' CAPM usage beyond textbook theory—from valuing high-growth startups to building beta-neutral portfolios.
CAPM as a Tool for Market Insight
William Sharpe's 1964 derivation of the Capital Asset Pricing Model (CAPM) reshaped financial management from an art into a scientific discipline. Many financial theories have lost relevance with time, but CAPM remains a foundational framework that helps us understand the relationship between risk and expected return in investment analysis.
Why CAPM Still Matters in Modern Finance
CAPM's relevance stems from its recognition that beta is the appropriate measure of risk for a stock within a diversified portfolio. Financial platforms like Yahoo! Finance make this measurement available to professional and individual investors alike. The model highlights a key fact: systematic risk matters more than individual stock volatility in a well-diversified portfolio.
CAPM has substantially changed our approach to assessing investment performance. The Sharpe ratio, which measures excess return relative to risk, came from Sharpe's later research and now stands as modern finance's most common performance metric. This practical use shows CAPM's lasting impact beyond theory.
The model has shaped how people invest. CAPM's market portfolio concept—representing "all assets"—laid the groundwork for the multi-trillion-dollar index fund industry that has grown in the last five decades. Each time you put money in an S&P 500 index fund through your pension plan or directly, you apply CAPM principles.
CAPM brings several benefits compared to other methods of calculating required returns:
The focus stays on systematic risk, matching the reality that most investors hold diversified portfolios where unsystematic risk disappears
A theoretical link exists between required return and systematic risk, backed by extensive research
This is a big deal, as it means that the dividend growth model does not explicitly factor in a company's systematic risk relative to broader markets
Better results come from CAPM than the weighted average cost of capital (WACC) for investment appraisal discount rates
CAPM helps generate investment ideas and reassess holdings, though financial analysts know it shouldn't be the only method for stock valuation.
Limitations and Assumptions to Keep in Mind
Despite its widespread use, CAPM depends on assumptions that might not match real-life scenarios:
Perfect capital markets - No taxes, transaction costs, perfect information, rational investors, and numerous market participants
Single-period transaction horizon - Standard holding periods, usually one year
Diversified portfolios—Investors hold portfolios reflecting the entire market
Risk-free borrowing and lending—Investors can borrow at risk-free rates
Homogeneous expectations—All investors share similar market outlook expectations
The biggest problem lies in the assumption about risk-free rate borrowing. Individual investors face higher borrowing rates than governments, which creates a security market line with a shallower slope than theory suggests.
CAPM doesn't deal very well with beta stability. Critics note that beta relies on historical data and might not accurately show an asset's risk since it only measures the relationship between the asset and market without considering other factors.
Daily changes in the risk-free rate create volatility in the CAPM formula. Past market returns used in calculations might not predict future performance. Finding the right proxy betas for projects or investments can be challenging, which affects how reliable the results are.
Eugene Fama and Kenneth French's analysis of stock returns on major exchanges revealed that beta differences over long periods failed to explain stock performance variations. The linear relationship between beta and individual stock returns also fails to hold up in shorter periods.
In spite of that, CAPM sees widespread use because it offers a simple way to compare investment options. Even with theoretical weaknesses, it gives great insights to assess future expectations and compare investments.
Example 1: CAPM in Valuing High-Growth Startups
Financial analysts face unique challenges when they value high-growth startups, especially if they use traditional models like the Capital Asset Pricing Model (CAPM). Market data helps calculate beta easily for companies that are 5+ years old. Startups work quite differently. Let's get into how financial professionals adapt CAPM principles to these non-public entities.
Estimating Beta for Non-Public Companies
Private companies don't have market data. This creates a basic problem in applying CAPM to startups. Beta measures systematic risk and forms the backbone of the CAPM formula. You can't calculate it directly without stock prices. So analysts must find other ways to estimate this vital parameter.
Analysts often look at publicly traded companies that operate similarly to the private company. This "comparable company analysis" (CCA) helps create a proxy for the startup's risk profile. The key is to find businesses that match the startup's operational characteristics, not just ones in the same industry.
Research shows CCA slightly underestimates actual betas of test companies. These differences don't matter much statistically. Company size and earnings-to-price ratio play the biggest role in explaining gaps between estimated and actual betas.
The process of unlevering and relevering betas is vital:
First, identify a set of comparable public companies
Get their equity beta estimates
Unlever these betas to remove the effect of financial leverage
Calculate the average unlevered (asset) beta
Relever the average asset beta using the startup's target debt-to-equity ratio
The unlevering formula looks like this: Asset Beta (βU) = [1/(1+(D/E))] × Equity Beta (βE)
Using Proxy Betas in CAPM Formula
The standard CAPM formula uses your calculated proxy beta: E(ri) = Rf + βi(E(rm) – Rf)
To cite an instance, see a high-growth energy services startup with a target debt-to-equity ratio of 0.5. Analysts might look at similar publicly traded energy services companies like Halliburton (beta 1.6), Schlumberger (beta 1.65), Helix Energy Solutions (beta 1.71), and Superior Energy Services (beta 1.69).
These companies show an equity-weighted average beta of about 1.64, with a weighted average debt-to-equity ratio of 0.34. The unlevered asset beta comes to 1.343. The final beta estimate ends up higher than the industry average after relevering with the startup's target debt-to-equity ratio of 0.5. This reflects increased financial leverage.
You can estimate startup betas in other ways too. Venture capital-specific beta factors from VC investments offer another path. Studies show venture capital betas range from 1.9 to 2.8. The "adjusted market rate method" offers another option. It uses average expected returns for startups at similar lifecycle stages instead of expected market returns in CAPM.
Standard CAPM needs changes beyond traditional risk measurements for startup risk assessment. Risk premiums for startup valuation usually include extra factors:
Management capabilities
Product viability
Insolvency probabilities
Market conditions
Illiquidity considerations
Investor-startup fit criteria
CAPM application to startups needs careful adjustment and professional judgement. Traditional CAPM provides a good starting point. Early-stage company valuation is complex and requires these adaptations to create meaningful results.
Example 2: CAPM in Energy Sector Stocks (ExxonMobil)
Energy stocks are a great way to see the capital asset pricing model in action. The energy sector faces unique challenges when applying CAPM because of its exposure to commodity price changes. ExxonMobil, one of the world's largest publicly traded energy companies, serves as a perfect example to understand how CAPM works in commodity-driven markets.
Volatility and Beta in Commodity-Driven Stocks
Energy stocks have a complex relationship with market volatility because their performance links closely to commodity prices. Research shows that stock market volatility substantially affects commodity prices. This effect is especially noticeable in energy commodities when you compare them to agricultural and metals markets. The negative effect of stock market volatility on commodity prices was more statistically significant during the 2008-09 Global Financial Crisis than during the COVID-19 pandemic.
Beta calculations for energy giants like ExxonMobil show interesting patterns about systematic risk exposure. Current estimates of ExxonMobil's beta show notable variation:
0.90 based on covariance calculations with the S&P 500
0.91 according to newer market analyses
0.47 over a 5-year period, which ranks in the 22.6% percentile for the energy sector
This variation helps us understand the challenges of applying CAPM in practice. The energy sector's overall average beta is approximately 1.09 with a standard deviation of 0.82. These numbers suggest ExxonMobil carries less systematic risk than its industry peers.
Basically, these beta values show how oil price volatility affects stock performance. Research has identified several key drivers of oil price beta in oil industry stocks. Market conditions variables have the strongest statistical support: oil price (positive relationship), bond rate (positive), volatility of oil returns (negative), and cost of carry (positive).
CAPM Return vs Historical Return Comparison
The CAPM formula applied to ExxonMobil using the most detailed data shows revealing results. A complete analysis calculated ExxonMobil's expected rate of return as follows:
E(RXOM) = RF + βXOM[E(R)M – RF] = 4.87% + 0.90[14.65% – 4.87%] = 13.66%
This calculation used:
Risk-free rate (RF): 4.87% (based on long-term Treasury Composite)
Market portfolio expected return: 14.65%
ExxonMobil's beta: 0.90
A newer analysis determined ExxonMobil's cost of equity at 8.09%, calculated as Risk-Free Rate 4.35% + Beta 0.91 × ERP 4.12%. This difference shows how changing market conditions affect CAPM outputs.
The most important insight ended up coming from comparing these CAPM-derived expectations with actual historical performance. Research shows that CAPM consistently underestimates the risk premium for energy utilities compared to historical values by an annualised average of more than 4%. This finding matches broader finance literature about CAPM's mispricing of low-beta, value-orientated stocks.
This underestimation creates a significant concern for investors who use CAPM with energy stocks like ExxonMobil. Fama and French specifically point out that "CAPM estimates of the cost of equity for high beta stocks are too high (relative to historical average returns) and estimates for low beta stocks are too low".
The discrepancy becomes more obvious during periods of market volatility. Historical data reveals that precious metals like gold and silver send volatility information to G7 stock markets and act as safe-haven assets, especially during crisis periods. Energy stocks typically experience greater volatility transmission from commodity markets, which makes systematic risk assessment particularly challenging.
Combining CAPM with alternative beta strategies offers a practical solution to these limitations. Research suggests that including alternative beta strategies in a portfolio's commodity allocation has historically delivered higher returns and lower risk than passive long-only strategies.
Example 3: CAPM in International Equity Allocation
The traditional capital asset pricing model (CAPM) needs major changes when investors work across national borders. The International Capital Asset Pricing Model (ICAPM) builds on the classic formula by adding something missing from domestic models: foreign exchange risk.
Currency Risk and Adjusted Risk-Free Rate
The International CAPM is different from the standard CAPM because it pays investors for their exposure to foreign currencies. Beyond the basic components of time value and market risk premium, ICAPM rewards both direct and indirect exposure to currency changes.
Financial analysts must adjust risk-free rates for different currency zones to put this into practice. They can choose from three main approaches:
Foreign CAPM approach—This uses the target country's variables and assumes separate equity markets. The method automatically adds country risk adjustment through the foreign risk-free rate.
Global CAPM approach—This relies on global variables and assumes worldwide capital supply and demand. It usually uses a mature market's risk-free rate (often U.S.) plus a country risk premium.
Home CAPM approach—This uses the investor's home country variables. It works best for investors who keep most investments in their home market but want some international exposure.
Each method works best in specific situations. The foreign CAPM suits cash flows in foreign currency, while the global approach makes sense for big institutional investors with worldwide diversification.
Currency risk premium calculations play a key role in international investing. Research shows these premiums are smaller than expected but still matter. These premiums must match "the return on a zero-investment portfolio position perfectly correlated with real fluctuations in the currency value".
CAPM in Global Portfolio Optimization
ICAPM suggests investors should hold assets from each country based on that country's share in the world market portfolio. This ideal rarely happens in real life.
Studies of actual investor behaviour show ICAPM predictions only partly come true. The estimated coefficients on international standards are about 0.4 for equity portfolios and 0.2 for bond portfolios. Investors put less money in international assets than ICAPM suggests.
Investors often use these global indices as performance standards to apply ICAPM in portfolio building:
Morgan Stanley Capital International (MSCI) All Country World Index
Datastream Global index
Standard & Poor's Global index
Bond investors commonly use the Lehman Brothers Multiverse index as their standard.
New research shows a three-factor international CAPM works better than the old single-factor World CAPM in conditional asset pricing tests. This improved model has:
A global equity factor in local currencies
Two currency factors: dollar and carry
The dollar factor shows "the average excess return earned by an investor that borrows in the U.S. and invests in a broad portfolio of foreign currencies". The carry factor reflects "the average excess return earned by an investor that goes short (long) in a portfolio of low (high) interest rate currencies". U.S. investors have earned 7.65% average excess returns from this strategy.
The best currency exposure changes based on where investors live and current market conditions. Emerging markets show higher equity market betas than developed markets, which points to stronger global market effects.
Example 4: CAPM in Cost of Capital for Infrastructure Projects
Infrastructure financing creates a complex battleground to apply the capital asset pricing model (CAPM). Financial professionals still use CAPM as their main tool for infrastructure investment and financing decisions, even though debates about its accuracy continue. The cost of capital becomes crucial for projects that need billions in funding and span several decades.
CAPM in Government vs Private Sector Projects
Public and private infrastructure initiatives use CAPM in very different ways. Traditional CAPM calculations find it hard to capture how government support mechanisms change risk-return profiles. The UK government stepped in to help public-private partnership (PPP) projects that couldn't get enough financing after the 2008 Financial Crisis.
Government support comes in several ways:
Minimum revenue guarantees
Direct subsidies
Preferential loans
Equity investments
Tax reductions
Debt guarantees
These steps change how we calculate risk. Research shows that government debt guarantees (GDG) lower lender risk premiums, which helps projects become more financially viable. Standard CAPM formulas don't account for such guarantees directly, creating a challenge.
Private sector infrastructure projects need a different approach. Most projects work through special purpose vehicles with set lifespans, unlike the endless economic life CAPM assumes for most equities. Private investments in Portugal's highway expansion used 73% debt financing, and most projects had leverage between 70% and 90%.
CAPM gives unrealistic results when debt levels go above 80% of total investment. High leverage values in the formula lead to equity return numbers that don't make sense for project financing.
Estimating Equity Premium in Long-Term Projects
Infrastructure investments face unique challenges in calculating equity premiums. Infrastructure investors must look beyond basic CAPM components (risk-free rate, beta, equity risk premium) and think about sector-specific factors.
Infrastructure projects follow different rules for picking the risk-free rate. PPP contracts base this rate on cash flow currency rather than where the project is located. Long-dated government bonds (15-25 years) usually provide the baseline because these projects run for many years.
Beta estimation becomes particularly tricky for infrastructure assets. Too few comparable listed funds exist, which leads to statistically weak betas that don't show how stock prices really move with the market. Infrastructure investors should know that market betas might not show their project's actual risk profile.
CAPM's equity risk premium component brings more challenges. Infrastructure assets show different risk-return patterns compared to regular companies. Many risks that affect traditional equities—like changing input prices and competition-driven product prices—don't affect infrastructure returns the same way.
Project size and complexity affect costs significantly. Bigger and more complex projects tend to need more equity and capital. Highway projects use length to measure complexity, and longer routes cost more in both equity and capital.
Economic conditions around us change how we use CAPM for infrastructure. Both equity and overall capital costs went up sharply during the financial crisis. Long-term projections must account for these economic shifts.
Many infrastructure investors use the weighted average cost of capital (WACC) instead of pure CAPM for projects with high leverage. Experts suggest using CAPM just to double-check internal rate of return methods when valuing infrastructure assets.
Example 5: CAPM in Evaluating ESG Investments
ESG investing creates unique challenges for traditional capital asset pricing models. Investors now prioritise sustainability, and financial markets adjust their pricing. These changes demand updates to standard CAPM frameworks.
Beta Behavior of ESG vs Non-ESG Portfolios
Research shows stocks with high ESG scores have lower volatility and systematic risk than their counterparts. Companies with strong ESG profiles handle market shocks better. Their reduced risk shows up as lower beta values in CAPM calculations.
Studies looking at ESG scores and beta coefficients show a clear pattern. Green practices lead to lower systematic risk over time. ESG and non-ESG portfolio betas differ in several ways:
Strong ESG performance reduces systematic risk by cutting capital costs
ESG investments face nowhere near the climate, social, and governance risks
ESG integration cuts portfolio risk in markets of all types
Martín-Cervantes and Valls Martínez's research found that ESG factors "constitute the main variable on the formation, determination, and sign of betas". This finding suggests ESG elements change how we measure systematic risk through CAPM.
CAPM Return vs Social Impact Premium
Adding ESG priorities to investor utility functions creates unexpected results in modified CAPM. Asset pricing theory suggests investors should expect better returns from stocks with poor ESG scores if these scores reflect risk factors.
Market equilibrium models with ESG show high-scoring "Green" assets yield lower expected returns than "Brown" assets with weak ESG ratings. Data shows a one-standard-deviation boost in ESG features leads to 2.73% lower annual expected returns. This reduction jumps to 3.41% yearly after ESG bias correction.
This negative ESG premium comes from investor priorities rather than risk features. Pastor et al.'s equilibrium model found that "assets with higher ESG scores have negative CAPM alphas, whereas assets with lower ESG scores have positive alphas". Sustainability-focused investors pay extra to hold green assets and accept lower financial returns that match their values.
Financial literature calls this the "sin premium"—better returns from companies in controversial industries like tobacco, alcohol, and gambling. Hong and Kacperczyk found institutions sensitive to public opinion, such as endowments and pension funds, avoid these "sin stocks".
Green assets sometimes outperform brown assets during ESG investor proportion changes. This happens as prices adjust to growing ESG demand in the market, which temporarily pushes up green asset prices compared to brown ones.
Example 6: CAPM in Financial Modeling for IPO Pricing
Precise valuation methodologies play a vital role in setting appropriate IPO prices. The capital asset pricing model (capm) forms the foundation for determining discount rates in financial models that shape IPO valuations.
CAPM-Based Discount Rate in DCF Models
Discounted cash flow (DCF) models use the weighted average cost of capital (WACC) as their discount rate for IPO pricing. WACC combines debt and equity components to calculate a company's overall capital cost. Here's the WACC formula:
WACC = ((Cost of debt * (1 - tax rate) * (weight of debt)) + ((Cost of equity) * (weight of equity))
The capm formula is the key component used to calculate the cost of equity within WACC:
Cost of equity = Risk-free rate + (Risk premium * Beta)
Companies seeking IPOs face unique challenges in determining discount rates because they don't have public trading history. This means financial analysts must look at similar public companies in the same industry to find proxy betas. Small businesses and startups usually need risk premiums above the typical 4-8% range that established public companies use.
Research shows that the capital asset pricing model (CAPM) needs adjustments based on company age and industry type. A biotech startup might start with Amgen's beta of 0.5 but adjust it up to 1.0 to account for extra risks.
Sensitivity Analysis on Beta and Market Premium
Beta measures how volatile a stock is compared to the market. The market has a beta of 1.0, and higher values show more volatility. IPO modelling requires careful analysis of different beta values because small changes can lead to big differences in valuation.
Here's a real-world example: a stock with a 1.3 beta would give a 9.5% expected return with a 3% risk-free rate and 8% market return. Underwriters test multiple scenarios with different betas to set the right IPO price ranges.
Beta estimation for IPO candidates depends on several key factors:
Financial leverage (debt-to-equity ratio)
Business cyclicality
Fixed vs. variable cost structure
Operational leverage
The capm market model gives analysts a starting point, but they need to test various scenarios for IPO valuation. This testing includes looking at the equity risk premium, which usually falls between 4% and 6% based on S&P 500 returns over government bond yields.
The capm finance model works best when analysts balance theory with real market conditions to find prices that work for both companies and investors.
Example 7: CAPM in Quantitative Trading Strategies
Quantitative trading strategies showcase a modern application of the capital asset pricing model in today's markets. Algorithmic and autonomous trading has changed how individual stocks' returns match broader market movements. This transformation creates new challenges and opportunities for quantitative strategists.
Beta-Neutral Portfolio Construction
Beta-neutral portfolios balance long and short positions to achieve a portfolio beta of zero and eliminate market risk. Recent studies show that many "market-neutral" hedge funds generate returns that relate closely to market standards. The main challenge comes from forecasting beta accurately. Higher forecast errors lead to funds experiencing more residual beta exposure.
Research shows that common methods to build beta-neutral portfolios don't work well, especially during volatile market periods. The most accurate beta forecasting happens when portfolios use realised betas from daily returns over the previous year.
CAPM Alpha as a Signal in Backtesting
CAPM alpha serves as the key signal for strategy development in quantitative trading. Traders use private analyst explanations about future market index prices and calculated betas to predict price movements during trading simulations. The capm formula's expected return becomes valuable to analyse potential price changes.
The Kalman filter-based dynamic cap market model works best to build equity market-neutral portfolios with a positive alpha. This model helps estimate the equivalent option "Greeks" for volatility index derivatives and enhances risk management capabilities.
Conclusion
You've seen how CAPM shapes investment decisions in markets of all types. These seven examples show that CAPM still works as a key framework to link risk and expected returns in modern finance, even with its theoretical limits.
CAPM stays relevant because it works well in practice. The model provides us a well-laid-out way to measure systematic risk. We can use it with high-growth startups through proxy betas or analyse energy stocks that depend on complex commodity prices. On top of that, it helps with international portfolios where currency issues make things more complex.
Financial experts adapt CAPM to tackle specific challenges. Project financing in infrastructure needs us to think over government support and long-term plans. ESG investments just need us to understand how sustainability changes traditional risk-return relationships. IPO pricing relies on smart proxy beta choices when there's no trading history.
Maybe even more important, CAPM has grown beyond theory into advanced quantitative trading strategies. Teams build beta-neutral portfolios to remove market risk, while CAPM alpha is a key signal in algorithmic trading systems.
People keep using the model because it's the quickest way to compare investments based on systematic risk. Although real-world tests challenge some of its predictions, CAPM provides valuable insights when evaluating whether future expectations are reasonable.
Markets get more complex every day. Knowing how to use CAPM and understand its limits gives you valuable perspective. The model might not capture everything perfectly, but it gives us a logical framework to make investment decisions. This mix of elegant theory and practical use explains why CAPM remains central to financial analysis after so many years.