Sinéad Farmer
HEDGE FUND DATA 15/12/2021

Seasonality of hedge fund returns

Sinéad Farmer Investor Relations Coordinator

Seasonality in hedge fund returns – when in the year do hedge funds perform best?

Using the Aurum Hedge Fund Data Engine[1] to analyse the seasonality of hedge fund returns over the last 10 years seems to clearly indicate that hedge fund performance in the last month of a given calendar quarter is often, a bit grim… with the exception of December.

10 YEAR HEDGE FUND INDUSTRY ASSET WEIGHTED NET RETURN AGGREGATED BY MONTH

On an aggregated basis, December has been responsible for more dollar returns than the combined performance generated in the months of March, June, August, September and October over the past 10 years. April and July are other months in which hedge funds regularly perform strongly. However, when we look at hedge fund performance across all of the spring/summer months, we see this is a more variable performance season.

Why is there seasonality in hedge fund returns?

It is possible that there is some response to the well-known Santa equity rally at play here, which will be impacting those hedge fund strategies with higher beta.

However, when we look deeper into the data we can see that December returns actually typically have a high component of alpha. The chart below helps us to effectively see in aggregate across the last 10 years when the industry is most successful from a seasonality perspective in creating alpha.

HF UNIVERSE DOLLARS EXTRACTED OVER THE LAST TEN YEARS BROKEN DOWN INTO ALPHA/BETA MONTHLY SPLITS

This chart breaks down the returns of each of the component funds of the Hedge Fund Composite into beta and alpha components. It excludes those attributable to risk free (“Rf”) components.  Alpha = actual return – Rf** – beta * (market return – Rf). These are then aggregated to show the dollar returns of the Hedge Fund Composite attributed to alpha/beta (excluding Rf).

For note, beta can be negative in certain cases, creating negative dollar attributions. These are offset by corresponding positive alpha contributions.

The chart shows 50% of the alpha generated by the industry over the last ten years is generated in the December – February period!

Does strategy matter?

The seasonality of alpha generation observed varies dependent upon the master strategy involved. Take, for example, macro. When stripping out beta dollars we find that 71% of the alpha dollars generated by macro managers over the last ten years occurred in the two months of December and January!

MACRO DOLLARS EXTRACTED OVER THE LAST TEN YEARS BROKEN DOWN INTO ALPHA/BETA MONTHLY SPLITS

Quant is the master strategy with the weakest observable correlation to S&P Global BMI (US Dollar). So although this alpha/beta seasonality trend is illustrated even more starkly when we look at quant, given its low beta we should take this with a pinch of salt. If we just look at the months of December and January, 117% of positive alpha dollars in the past ten years were generated in these months (this number is more than 100% as there are several months of negative alpha dollar generation in this strategy group). July, however, is the exceptional alpha generation month for quant strategies, accounting for 95% of positive alpha dollars generated.

QUANT DOLLARS EXTRACTED OVER THE LAST TEN YEARS BROKEN DOWN INTO ALPHA/BETA MONTLY SPLITS

Multi-strategy funds have exhibited far less seasonal beta generation over the period, with alpha typically generated more consistently throughout the year. And also with this strategy grouping there is a considerably lower level of beta generation than many other master strategies, our data suggest that on a net basis, $4 of alpha are generated for every $1 of beta. Equity strategies in large multi-strategy funds tend to be multi-PM equity market neutral platforms. These are hugely diversified, and have negligible beta or style factor exposure. It is not surprising that multi-strategy returns exhibit little equity market beta-linked seasonality.

MULTI-STRATEGY DOLLARS EXTRACTED OVER THE LAST TEN YEARS BROKEN DOWN INTO ALPHA/BETA MONTHLY SPLITS

But why is performance poor at other quarter ends during this 10-year period?

What is it that causes negative or low levels of alpha creation at non-year-end quarter ends?

One possible reason could be redemption pressures hedge funds experience at quarter end. Another could be that these months are the ‘off-season’ for corporate earnings reporting. Less company-specific news at quarter-ends (March, June, September, and December), mean that stocks can ‘drift’ or move for more macro/non-stock specific reasons, which can be challenging for fundamental equity investing. This article identifies the trends in hedge fund returns, but establishing the reasons for them will require a much more in-depth analysis.

March and September are months that over the 10 year period are often associated with equity market drawdowns. Hedge fund strategies that have higher beta components to equities are impacted by these drawdowns, creating negative beta in those months.

HEDGE FUND INDUSTRY AND GLOBAL EQUITY INDEX 10 YEAR RETURNS

Will December 2021 buck the trend?

With the impact of the Omicron variant on markets and speculation around what impact it may have on global economies, we are currently seeing plenty of market turmoil.  Will this have an impact on the seasonal trends?  We have yet to see how this will play out and there is a possibility that the ‘Santa’ rally will be lower or even negative this year.  It is also possible this will impact on alpha generation in the hedge fund industry, although the dislocations and volatility could provide opportunities for some managers and strategies. We will have to wait and see if this year it turns out to be a ‘season to be jolly’.

However, this analysis backs up once again Aurum’s preference for hedge fund strategies with low or no structural beta, that aren’t reliant on market environments for positive performance.

Aurum believe that investors should not be paying hedge fund fees for beta-driven returns.  A well-constructed portfolio of hedge funds should be capable of delivering alpha-driven uncorrelated returns across market cycles.  Selecting the right strategies and the right managers is the key for investors seeking alpha.

So, we wish you a festive season full of good cheer and alpha-rich hedge fund returns!

[1]Aurum’s proprietary Hedge Fund Data Engine database containing data on just under 4,000 hedge funds representing in excess of $2.9 trillion of assets as at December 2020. Information in the database is derived from multiple sources including Aurum’s own research, regulatory filings, public registers and other database providers.
Data from the Aurum Hedge Fund Data Engine is provided on the following basis: (1) Aurum Hedge Fund Data Engine data is provided for informational purposes only; (2) information and data included in the Aurum Hedge Fund Data Engine are obtained from various third party sources including Aurum’s own research, regulatory filings, public registers and other data providers and are provided on an “as is” basis; (3) Aurum does not perform any audit or verify the information provided by third parties; (4) Aurum is not responsible for and does not warrant the correctness, accuracy, or reliability of the data in the Aurum Hedge Fund Data Engine; (5) any constituents and data points in the Aurum Hedge Fund Data Engine may be removed at any time; (6) the completeness of the data may vary in the Aurum Hedge Fund Data Engine; (7) Aurum does not warrant that the data in the Aurum Hedge Fund Data Engine will be free from any errors, omissions or inaccuracies; (8) the information in the Aurum Hedge Fund Data Engine does not constitute an offer or a recommendation to buy or sell any security or financial product or vehicle whatsoever or any type of tax or investment advice or recommendation; (9) past performance is no indication of future results; and (10) Aurum reserves the right to change its Aurum Hedge Fund Data Engine methodology at any time and may elect to suppress or change underlying data should it be considered optimal for representation and/or accuracy.