{'fraction_non_alphanumeric': 0.013556618819776715, 'fraction_numerical': 0.003189792663476874, 'mean_word_length': 5.64021164021164, '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}}
Portfolio Rebalancing and Score-based Portfolio Choice

Factor strategies in equity portfolio management come with high portfolio turnover. In this paper we propose a rebalancing strategy that balances transactions costs with the expected return contribution of the desired portfolio transaction. We follow score-based factor strategies, that sort stocks according to characteristics and seek to hold those stocks which score highest. Thus, high variability of characteristics translates into high propensity to change portfolio constituents. Our heuristic strategy forms expectations of how long a stock will be part of the portfolio and decides to transact only if the expected return contribution over the holding period exceeds transaction costs. We conduct our analysis for scores built on the characteristics underlying the five factor setting in Fama and French (2015). We find that in a large-cap transaction cost setting, neither our heuristic strategy nor automatic rebalancing significantly outperforms the other strategy. In an elevated transaction cost environment however, we find that our heuristic strategy significantly outperforms for three of the five characteristics with higher average returns also for the other two characteristics.