Time-Series Momentum in a Small European Stock Market: Evidence from a New Historical Financial Dataset

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Abstract

In this paper, we examine the Portuguese stock market for indication of time-series momentum effects using a new historical financial dataset that covers about 120 years of data. We find strong time-series momentum effects that cannot be explained by conventional risk factors. The positive return continuation seems to last for a period of 12 months, being heavily concentrated at the first month. At longer investment horizons, returns tend to mean-revert. The market exhibited significant time-series momentum for all look-back and holding periods of 12 months or less. A strategy with a 1-month lookback period and a 12-month holding period is shown to be the most profitable yielding a Sharpe ratio roughly 5.4 times that generated by a passive strategy. Time-series momentum strategies tend to perform best during extreme up-market periods and deliver the worst returns during down markets. This suggests that the strategy may not offer significant diversification benefits. Our findings add to the evidence that time-series momentum effects are not a product of data mining and are difficult to reconcile with the assertion that stock markets follow a random walk.

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APA

Lobão, J., & Rosário, A. (2023). Time-Series Momentum in a Small European Stock Market: Evidence from a New Historical Financial Dataset. Scientific Annals of Economics and Business, 70(3), 335–352. https://doi.org/10.47743/saeb-2023-0021

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