When it comes to analysing financial data, investors and analysts often rely on statistical shortcuts to make sense of complex information. One of the most powerful tools in this arsenal is the empirical rule. Also known as the 68-95-99.7 rule, this simple formula helps to quickly understand the distribution of data—especially when dealing with investments, risk, and forecasting. But how exactly does the empirical rule work, and why is it still so relevant in 2025?
What Is the Empirical Rule?
The empirical rule is a statistical guideline that applies to datasets with a normal (bell-shaped) distribution. It states that for such data:
- About 68% of values fall within one standard deviation of the mean
- About 95% fall within two standard deviations
- About 99.7% fall within three standard deviations
This rule allows analysts to make quick, data-driven judgements about how ‘typical’ or ‘atypical’ a particular data point is within a set. In finance, it’s regularly used to gauge the likelihood of investment returns, volatility, and risks.
The Formula: How the Empirical Rule Works
The empirical rule is based on two main concepts: the mean (average) and the standard deviation (a measure of spread). The formula for calculating the ranges is simple:
- Mean ± 1 standard deviation (σ): captures ~68% of data
- Mean ± 2σ: captures ~95% of data
- Mean ± 3σ: captures ~99.7% of data
For example, if the average annual return on an ASX 200 ETF is 7%, with a standard deviation of 3%, the empirical rule predicts:
- 68% chance: Return will be between 4% and 10% (7% ± 3%)
- 95% chance: Return will be between 1% and 13% (7% ± 6%)
- 99.7% chance: Return will be between -2% and 16% (7% ± 9%)
While not every dataset is perfectly normal, many financial metrics (like returns, price changes, or even loan default rates) tend to approximate this pattern—especially over large sample sizes.
Real-World Examples: The Empirical Rule in Action (2025)
The empirical rule remains a staple in Australian financial analysis in 2025, especially as regulatory bodies and fintech platforms push for greater transparency around risk.
- Risk Assessment for Managed Funds: Fund managers routinely use the empirical rule when presenting expected returns to clients. For instance, if a diversified super fund reports a 5-year average return of 6% with a standard deviation of 2%, members can visualise the range of possible returns—and the likelihood of extreme outliers.
- Volatility Analysis for Crypto Assets: With crypto markets maturing and new ASIC guidance in 2025 on risk disclosure, the empirical rule helps investors gauge the probability of large swings in Bitcoin or Ethereum prices, informing decisions on stop-loss orders or portfolio allocation.
- Loan Default Forecasts: Lenders use the empirical rule to estimate the likelihood of default rates exceeding certain thresholds. This influences both pricing and capital reserves, especially with APRA’s updated prudential standards for 2025 requiring more granular risk modelling.
These applications help investors, advisers, and institutions make faster, more informed decisions—without getting bogged down in complex statistical modelling.
Why the Empirical Rule Still Matters in 2025
Despite advances in big data and AI-driven analytics, the empirical rule’s simplicity makes it indispensable. Here’s why:
- Speed: Provides a quick ‘sense check’ for data analysis, especially when time is of the essence.
- Communication: Helps non-experts grasp risk and variability—crucial in a world where financial literacy is increasingly prioritised by both government and industry.
- Regulatory Alignment: With 2025’s ongoing push for clear risk disclosure (from ASIC and APRA), the empirical rule underpins many standard reporting templates and investor education tools.
However, it’s important to remember the empirical rule only applies when data is approximately normally distributed. Outliers, skewed data, or small sample sizes can reduce its accuracy, so analysts often pair it with visualisations or more advanced statistical techniques.
Conclusion
The empirical rule is more than just a statistical curiosity—it’s a practical, everyday tool that helps Australians make sense of investment risk, returns, and uncertainty. Whether you’re comparing managed funds, analysing market volatility, or forecasting loan performance, mastering the empirical rule can give you an edge in financial decision-making—especially as data-driven investing becomes the new normal in 2025.
