{'fraction_non_alphanumeric': 0.02205128205128205, 'fraction_numerical': 0.012307692307692308, 'mean_word_length': 5.1545741324921135, '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}}
Dynamic Asset Allocation Based on Valuation and Momentum Applied to a Global All-Equity Portfolio

There has been considerable research into dynamic global tactical asset allocation (GTAA) strategies driven by simple measures of Valuation and Momentum applied to a baseline balanced portfolio of equities and fixed income (see Blitz and van Vliet 2008, Wang and Kochard 2011, Gnedenko and Yelnik 2014, and Dewey and Haghani 2016). In sum, this research has found that historically, these Valuation-and-Momentum-driven investment approaches have produced higher returns and more attractive risk-adjusted returns than a static-weight approach. However, the above-cited research has been mostly silent on the question of how such an approach could be implemented and would have performed in the context of an All-Equity portfolio, where the Valuation and Momentum signals would drive a dynamic allocation between different regional equity markets. This note explores this question. It finds that such a dynamic approach would have produced higher absolute returns, and higher risk-adjusted returns, than a static approach would have produced. However, the improvement in simulated historical returns is less than the improvement that Valuation and Momentum deliver when applied to a balanced baseline portfolio of equities and fixed income. For example, simulated historical returns for the All-Equity strategy described below over the past roughly 40 years had about 50% more variability but only 20% higher returns than did a similar dynamic Global Balanced strategy. We examine a form of the strategy that can be followed by any investor with a simple brokerage account, using low-cost, liquid and widely available ETFs or index funds, and without use of leverage or shorting. The implementation we explore in this note trades monthly, with turnover averaging about 50% per annum. It is be based on data that is freely available in the public domain.