Multi-Asset Seasonality and Trend-Following Strategies

Bankers, Markets & Investors (Forthcoming)

24 Pages Posted: 3 Jan 2016

See all articles by Nick Baltas

Nick Baltas

Imperial College Business School; Goldman Sachs International

Date Written: January 3, 2016

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 same-calendar-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

JEL Classification: G11, G12, G13, G14, G15

Suggested Citation

Baltas, Nick, Multi-Asset Seasonality and Trend-Following Strategies (January 3, 2016). Bankers, Markets & Investors (Forthcoming). Available at SSRN: https://ssrn.com/abstract=2710334

Nick Baltas (Contact Author)

Imperial College Business School ( email )

South Kensington Campus
Exhibition Road
London, SW7 2AZ
United Kingdom

Goldman Sachs International

Peterborough Court
133 Fleet Street
London, EC4A 2BB
United Kingdom

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