Capturing the January to Halloween Premia—on the Cheap

Seasonal patterns in equity and commodity markets are ripe for exploitation—and, according to new research, can be cost-effective, given the right strategy.

Nick Baltas, executive director of UBS Investment Bank’s quantitative research division, argued that investors could capture “significant” premiums by incorporating seasonality signals into their portfolios—but these premiums can come at a high price.

“From the famous January effect to the Halloween effect and the lunar cycle, academic studies have documented a multitude of seasonal patterns within equity markets and equity strategy returns,” Baltas wrote. “What is very common across all these patterns is that it is typically rather expensive to exploit them.”

To avoid the associated high turnover costs, Baltas suggested that investors capitalize on seasonal patterns indirectly through trend-following.

A typical trend-following strategy, according to the quant, involves long positions on assets that have moved up over the past year and short positions on those that were downward moving over the same period. Baltas’s proposed “seasonality-adjusted” strategy would incorporate seasonal patterns through “switching off long and short positions, when the respective seasonality signals argue otherwise.”

For example, if an asset has one of the lowest same-calendar-month average past returns, investors should not hold a long position. Likewise, they should avoid short positions for assets with the highest same-calendar-month average past returns.

For his analysis, Baltas backtested trend-following strategies for commodities and equities from January 1992 to February 2015. The study revealed seasonality-adjusted trend-following strategies outperformed, achieving Sharpe ratios of 0.81 for commodities and 0.71 for equity indexes. These figures surpassed ratios of 0.71 and 0.66 for regular trend-following commodity and equity strategies, respectively.

While the strategy still has turnover costs, Baltas noted that these expenses are “relatively conservative,” given the liquidity and low trading costs of futures contracts. Furthermore, he said the implementation highlighted in the study applied none of the cost-optimization or position-smoothing techniques that investors would use to reduce costs in practice.

One example of a cost optimization technique would be halving positions rather than switching them off entirely. Under this moderation, Baltas found, “turnover of the enhanced strategies falls significantly with the performance pickup remaining strong.”

The full report, “Multi-Asset Seasonality and Trend-Following Strategies,” will be published in a forthcoming issue of Banking, Markets, & Investors.