Inputs
Choose a method, enter values, and calculate beta-based market risk.
Example data table
This sample uses monthly returns. Enter them into series mode to reproduce a typical beta calculation.
| Month | Asset return | Market return |
|---|---|---|
| 1 | 1.2% | 0.8% |
| 2 | -0.4% | -0.2% |
| 3 | 0.9% | 0.6% |
| 4 | 1.5% | 1.0% |
| 5 | -0.7% | -0.4% |
| 6 | 0.3% | 0.2% |
Formula used
Beta (β) measures how sensitive an asset is to market movements:
In return series mode, this equals the slope from a simple linear regression:
The calculator also reports correlation and R-squared to show how well market returns explain asset variation.
How to use this calculator
- Select Return series if you have aligned returns.
- Paste asset and market returns using commas or new lines.
- Optionally enter risk-free and market expected returns for CAPM.
- Click Calculate to view results above the form.
- Use Download CSV or Download PDF for sharing.
Beta as a market sensitivity gauge
Beta measures how an asset’s returns tend to move when the market moves. A beta of 1.0 suggests the asset tracks the market’s swings, while 0.5 indicates roughly half the sensitivity. Negative beta implies the asset often moves opposite the market. Investors use beta to frame systematic risk, not total volatility, because idiosyncratic shocks can dominate short horizons.
Data choices that change the estimate
Your estimate depends on the return series and frequency. Daily returns capture more observations but can be noisy from microstructure effects and non‑synchronous trading. Weekly or monthly data smooths noise but reacts slower to regime shifts. Always align dates, use the same currency, and prefer total‑return data including dividends. A 2–5 year window is common, yet sector cycles may justify shorter or longer samples. Benchmark choice matters: broad indexes fit diversified stocks, while sector indexes may better represent exposure. Remove obvious outliers, consider log returns for larger moves, and document any data cleaning to keep results comparable.
Interpreting outputs beyond beta
Beyond the beta slope, pay attention to correlation and R-squared. High correlation and higher R-squared mean market movements explain more of the asset’s variation, making beta more reliable for market exposure decisions. A low R-squared signals that beta is unstable for forecasting because most moves come from non‑market factors. The calculator’s intercept (alpha) indicates average outperformance relative to the fitted market line.
Using beta for required return estimates
Beta feeds the CAPM-style cost of equity: expected return ≈ risk‑free rate + beta × market risk premium. This is useful for discount rates, hurdle rates, and scenario planning. Use consistent inputs: match the beta horizon to your cash‑flow horizon, and base the market premium on long‑run expectations. Levered firms often adjust beta for capital structure when valuing projects.
Limits, stability, and risk controls
Beta is not constant. It can change with leverage, business mix, and macro conditions, and it often spikes in stress periods. Combine beta with position sizing, drawdown limits, and diversification. For portfolios, betas add as a weighted sum; however, concentrated holdings can still carry high specific risk. Re-estimate periodically, compare multiple windows, and sanity‑check against peer betas.
FAQs
What is beta risk in finance?
Beta risk is the portion of an asset’s risk driven by broad market movements. It reflects systematic exposure that cannot be diversified away, unlike company-specific events that diversification can reduce.
Which market index should I use?
Choose an index that matches your investable universe. Use a broad index for diversified equities, a sector index for narrow exposure, or a local index for domestic assets. Consistency matters more than perfection.
Why can my beta change over time?
Beta shifts with leverage, business mix, liquidity, and macro regimes. Estimation windows also matter: shorter windows react faster but are noisier, while longer windows are smoother yet may miss recent structural changes.
What does low R-squared mean here?
Low R-squared means market returns explain only a small share of the asset’s return variation. In that case, beta is less useful for forecasting market sensitivity because most movements come from non-market factors.
How do I use beta in expected return estimates?
A common approach is expected return = risk-free rate + beta × market risk premium. Use inputs aligned to the same horizon and currency, and treat the result as a planning estimate, not a guarantee.
Can I estimate portfolio beta with this tool?
Yes. Compute each holding’s beta versus the same benchmark, then multiply each beta by its portfolio weight and sum the results. Rebalance weights and re-estimate betas periodically as exposures evolve.