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Multi-Asset Seasonality and Trend-Following Strategies

Nick Baltas
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Nick Baltas: Quantitative Research Group, UBS Investment Bank, Queen Mary University of London and Imperial College Business School

Bankers, Markets & Investors, 2016, issue 140, 47-62

Abstract: This paper investigates the seasonality patterns within various asset classes. We find that a strategy that buys the assets with the largest same-calendar-month past average returns (up to ten years) and sells the assets with the smallest samecalendar- month past average returns, earns statistically and economically significant premia within commodity and equity index universes. Capitalising these premia directly appears practically difficult, due to the high strategy turnover and associated costs. We therefore suggest a way to actively incorporate seasonality signals into a trend-following strategy by switching off long and short positions, when the respective seasonality signals argue otherwise. The seasonality-adjusted trend-following strategy constitutes a significant improvement to the raw strategy across both commodities and equity indices. The increased turnover can impact the performance pickup, but the relatively low trading costs of liquid futures contracts as well as methodological amendments that optimise position smoothing can render the improvement genuine.

Keywords: Seasonality; Trend-following; Momentum; Managed Futures; CTA; Commodities (search for similar items in EconPapers)
JEL-codes: G11 G12 G13 G14 G15 (search for similar items in EconPapers)
Date: 2016
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