This study investigates the measurement bias introduced by the widespread use of overlapping returns in time series momentum (TSM) research, which can materially overstate the strength of TSM signals. Using a univariate AR(1) framework, simulations, and S&P 500 and S&P/ASX 200 index data from 1996 to 2019, we link TSM strength to return autocorrelation, volatility and the look-back horizon under both overlapping and non-overlapping return constructions. The analysis shows that overlapping returns mechanically accumulate autocorrelation, generating the familiar monotonic increase in measured TSM strength as the look-back period lengthens. Empirically, we find that return autocorrelation is the dominant driver of measured TSM strength and that the monotonic look-back profile becomes weaker and less systematic when non-overlapping returns are used. The AR(1) framework predicts a negative relation between volatility and TSM strength, and we observe this sign in both markets, but the estimated effects are not statistically significant at conventional levels. These results highlight the risk that overlapping returns artificially inflate momentum signals, with implications for backtesting robustness and portfolio risk management.