{'fraction_non_alphanumeric': 0.015856236786469344, 'fraction_numerical': 0.008456659619450317, 'mean_word_length': 5.230263157894737, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Asymmetry, Tail Risk and Time Series Momentum

Similar to the cross-sectional momentum crashes, the time series momentum experiences deep and persistent drawdowns in the stressed time of slumps in the upward momentum, rebounds in the downward momentum, and long time sideways market. We measure the upside and downside risk using the upper and lower partial moments, which are derived from the individual asset’s daily return. The time series momentum reversals are partly forecasted by the asymmetric structure of the tail-distributed upside and downside risk. An implementable systematic rule-based decision function is designed to manage the signals given by the time series momentum. Its empirical application on the Chinese commodity futures markets documents improvements in terms of both the Sharpe ratio and the Sortino ratio from 2008 to 2019. These results are robust across the time series momentum with different looking back windows.