They add up

  • Log returns allow us to assess cumulative returns over time by simply adding individual log returns.
  • This is particularly useful when assessing returns over multiple periods
  • Simple returns require more complex compounding, making them harder to work with in time-series contexts.

They normalize extreme values

  • Log returns help transform financial data closer to a normal distribution (bell-shaped), which can make trading tools and statistical models easier to interpret
  • Extreme values and outliers tend to be moderated compared to simple returns, which is crucial when

Summary

Log returns offer a mathematically sound and statistically practical way to quickly assess returns, particularly when analyzing volatile securities, modeling over time, and comparing different assets like stocks, and ETFs.