Timeweighting

Time-weighting is a method used to adjust the impact of individual data points within a dataset based on the duration or frequency of their occurrence. It is commonly employed in financial analysis, particularly when calculating investment returns or portfolio performance. In this context, time-weighting aims to isolate the performance of an investment from the timing of cash flows, such as deposits or withdrawals.

To achieve time-weighting, an investment's performance is typically measured over discrete periods. The returns for each period are then geometrically linked to arrive at the overall performance. This process ensures that the reported return reflects the actual growth of a hypothetical unit of currency invested at the beginning of the measurement period, regardless of when additional funds were added or removed.

This is distinct from money-weighting, which assigns more importance to data points based on the amount of money involved. Money-weighting is often used to calculate the internal rate of return (IRR) of a series of cash flows, where the timing and size of each flow directly influence the result. Time-weighting, by contrast, provides a more accurate measure of the investment manager's skill in generating returns, as it neutralizes the effect of investor decisions regarding capital contributions. Therefore, time-weighted returns are generally preferred for evaluating the performance of investment funds and their managers.