Expected Return: A Guide to Investment Profitability

Key takeaways

• Expected return is an estimate of the average profit or loss an investment is likely to produce, typically based on historical outcomes. It is not a guarantee.
• It is calculated as the expected value of possible returns, using probabilities or portfolio weights.
• Expected return is a core input in financial models such as modern portfolio theory (MPT) and the Capital Asset Pricing Model (CAPM), and is used alongside risk measures (e.g., standard deviation) to evaluate investments.
• Distinguish between systematic risk (market-wide) and unsystematic risk (asset- or firm-specific); both affect the likelihood of realizing the expected return.

What is expected return?

The expected return is the average return an investor anticipates from an investment over time, based on possible outcomes and their probabilities. Conceptually it is the long-run mean return you would observe if the same investment or decision were repeated many times.

Basic formula

Expected return (for discrete outcomes):
Expected Return = Σ (Return_i × Probability_i)

Example:
If there is a 50% chance of +20% and a 50% chance of −10%:
Expected return = 0.5×20% + 0.5×(−10%) = 5%

CAPM (expected return relative to market)

The Capital Asset Pricing Model expresses expected return relative to the risk-free rate and market risk:
Expected return = r_f + β × (r_m − r_f)

Where:
* r_f = risk-free rate
* β = asset beta (sensitivity to market)
* r_m = expected market return

Calculating portfolio expected return

A portfolio’s expected return is the weighted average of the expected returns of its components:

Portfolio Expected Return = Σ (weight_i × expected return_i)

Example:
Portfolio value = $1,000,000
* Alphabet (GOOG): $500,000 → weight 50%, expected return 15%
* Apple (AAPL): $200,000 → weight 20%, expected return 6%
* Amazon (AMZN): $300,000 → weight 30%, expected return 9%

Portfolio expected return = 0.50×15% + 0.20×6% + 0.30×9% = 11.4%

Measuring risk: standard deviation and risk types

Expected return alone doesn’t describe risk. Standard deviation measures the dispersion of returns around the mean and is commonly used as a proxy for volatility.

Sample standard deviation (conceptual):
SD ≈ sqrt( Σ (xi − x̄)² / (n − 1) )

Risk types:
* Systematic risk — affects the entire market or a large sector (not diversifiable).
* Unsystematic risk — specific to a company or industry (diversifiable through portfolio construction).

Illustrative example:
Two investments with five-year returns:
* Investment A: 12%, 2%, 25%, −9%, 10% → expected return ≈ 8%, SD ≈ 11.26%
* Investment B: 7%, 6%, 9%, 12%, 6% → expected return ≈ 8%, SD ≈ 2.28%

Both have the same expected return, but A is far riskier.

Limitations and practical considerations

• Expected return is an estimate based on historical data or modeled probabilities and does not guarantee future performance.
• Results depend on the accuracy of probabilities and return estimates; errors or optimistic assumptions produce misleading expectations.
• Always consider expected return alongside risk measures (standard deviation, beta, scenario analysis) and align expectations with investment horizon and objectives.
• Diversification reduces unsystematic risk but not systematic risk.

Bottom line

Expected return is a useful predictor of average investment outcomes and a foundational input for portfolio construction and pricing models. Treat it as an estimate—use it together with risk metrics and sound assumptions when making investment decisions.