Quantify the uncertainty in your stock valuations with statistical confidence intervals. Get more realistic price targets that account for market volatility and estimation errors.
Calculate statistically sound price ranges for your stock valuations
This calculator helps you determine realistic valuation ranges for stocks by applying statistical confidence intervals to your estimates. Enter your valuation inputs below to see a probability-based price range.
Point estimates for stock prices are misleading - probability ranges provide a more realistic view of potential outcomes
Confidence intervals provide a realistic range of potential price outcomes rather than overly precise point estimates that rarely materialize.
Quantify the probability of downside scenarios to better understand your risk exposure and set appropriate position sizes for your risk tolerance.
Understand how model uncertainty and market volatility impact valuation precision, leading to more informed investment decisions.
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How probability-based approaches improve traditional valuation methods
Traditional stock price targets suggest a precision that doesn't exist in reality. There are several problems with single-point valuation estimates:
Exact price targets imply a level of certainty that's impossible in complex, dynamic markets with many variables.
Point estimates fail to account for natural price fluctuations and the range of possible outcomes due to market volatility.
All valuation models have inherent errors and assumptions that create uncertainty not reflected in a single estimate.
Binary "buy/sell" decisions based on rigid price targets fail to account for the probabilistic nature of investment outcomes.
Statistical confidence intervals offer significant advantages over traditional point estimates for stock valuations:
Confidence intervals explicitly acknowledge and quantify the uncertainty inherent in all valuation models.
By providing probability distributions, investors can make more nuanced decisions based on their risk preferences.
Understand the probability of downside scenarios, allowing for more appropriate position sizing and risk management.
Confidence intervals naturally widen with longer time horizons, reflecting increased uncertainty over extended periods.
Institutional investors and hedge funds routinely use probability distributions rather than point estimates for their analyses.
Everything you need to know about valuation confidence intervals
A valuation confidence interval is a statistical range that expresses the uncertainty in a stock's estimated future price. Unlike a single-point price target, a confidence interval provides a range of values within which the future stock price is likely to fall with a specific probability (e.g., 95% confidence).
The calculation of a confidence interval incorporates:
By using confidence intervals, investors gain a more realistic understanding of the potential range of future prices and can make better-informed decisions based on their risk tolerance and investment goals.
The confidence interval provides you with a statistically sound range of potential future stock prices. Here's how to interpret the results:
Additionally, the calculator provides key probability insights:
These probability-based insights allow you to make more nuanced investment decisions, appropriately size positions, and set realistic expectations for potential outcomes.
Historical volatility is a key input for the confidence interval calculation. Here are several ways to find this information:
General volatility benchmarks (if you can't find the specific value):
For the most accurate confidence intervals, try to use volatility measures specific to your stock rather than industry averages.
The choice of confidence level depends on your analysis needs and risk assessment goals:
| Confidence Level | Description | Best For |
|---|---|---|
| 50% - 70% | Narrower interval, higher chance of price falling outside the range | Understanding the most likely outcomes, less concerned with extreme scenarios |
| 80% - 90% | Balanced approach, covers most probable scenarios | General investment planning, moderate risk assessment |
| 95% | Standard statistical confidence level, covers nearly all plausible outcomes | Comprehensive risk assessment, standard for most investment analyses |
| 99% | Very wide interval, includes extreme scenarios | Conservative risk management, stress testing, worst-case scenario planning |
Professional investors often use multiple confidence levels for different purposes:
The default 95% confidence level in our calculator is the most commonly used in statistical analysis and provides a good balance between capturing potential outcomes while not being excessively wide.
Valuation confidence intervals improve investment decision-making in several ways:
Wider confidence intervals indicate higher uncertainty, suggesting smaller position sizes. Narrower intervals may justify larger positions.
The ratio of upside potential (distance to upper bound) versus downside risk (distance to lower bound) helps evaluate the attractiveness of an investment.
Understanding the probability distribution can help time entries toward the lower end of the confidence interval.
The lower bound of a confidence interval can provide a statistically informed reference point for stop loss placement.
Stocks with wider confidence intervals (higher uncertainty) should be balanced with more stable investments.
By incorporating statistical confidence into your valuation process, you can make more nuanced investment decisions based on probability distributions rather than simplistic binary outcomes.
The confidence interval model provides valuable statistical insights, but it's important to understand its assumptions and limitations:
Key assumptions:
Accuracy considerations:
Best practices for accuracy:
Despite these limitations, confidence intervals provide a much more realistic framework for understanding potential stock price outcomes than single-point estimates, which inherently provide no information about uncertainty.
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