If you are a company that operates in a global marketplace, it's likely you've converted salaries from one currency to another during the recruitment process, when creating compensation ranges, or when running your company's yearly merit cycle. 🌎
You may be wondering what the best practice is when it comes to doing so. We're here to help!
What's the best exchange rate to use?
Pequity recommends using a 6-month trailing average FX conversion. If you utilize Pequity's People Insights page, you'll notice that we default to this value when converting local currencies.
Why does Pequity recommended a 6-mo trailing average?
Using a trailing average evens out the volatility inherent in short-term changes. This approach ensures that there is no undue advantage or disadvantage associated with choosing a specific day for currency conversion, promoting fairness and consistency in financial operations.
It's important to note that there is no universally prescribed best practice when it comes to FX conversion rates. However, utilizing a 6-month trailing average can be advantageous for several reasons. ☝️
A 6-month trailing average incorporates a longer time period, which enables it to capture and smooth out outliers, resulting in a more accurate representation of the FX trend. By doing so, it mitigates the impact of short-term fluctuations and reduces the influence of noise in the data. This approach is particularly beneficial when the goal is to establish a stable and consistent basis for currency conversion.
Many large companies opt for the 6-month trailing average because it strikes a balance between capturing recent trends and avoiding biases associated with specific quarters or extended time periods. It provides a reliable basis for decision-making in foreign exchange transactions, reducing the risk of making choices based on short-term fluctuations while still reflecting current market conditions.
Generally speaking, it is not recommended to use anything less than a 3-month training average FX conversion since that is where you might start to see more volatility when looking at less than a quarter of data.