Hedge Fund Data

Monthly hedge fund performance review – May 2022
20/06/2022
1 min read
HEDGE FUNDS | ||
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Hedge fund composite | ![]() | Hedge fund strategies monitored by Aurum’s Hedge Fund Data Engine delivered largely negative returns in May. The average hedge fund net return in May across all strategies was -1.01%. Performance dispersion was slightly wider than in April. |
Long biased | ![]() | Long biased funds monitored by Aurum’s Hedge Fund Data Engine returned an average of -1.17% in May. Most sub-strategies had negative returns. The worst performing sub-strategy, as in the previous three months, was long biased fixed income. Long biased commodities was the best performing sub-strategy, up 2.41%. |
Quant | ![]() | Quant funds monitored by Aurum’s Hedge Fund Data Engine returned -0.35% on average in May. Despite giving back some gains in May, it remains the strongest performing strategy year to date. The best performing sub-strategy was risk premia with an average net return of 1.18%. |
Equity long/short | ![]() | Equity long/short funds monitored by Aurum’s Hedge Fund Data Engine returned an average of -1.91% in May, in a bifurcated month for global equities. Most sub-strategies were negative for the month. For a second month, the worst performing sub-strategy was sector-focused funds. |
Macro | ![]() | Macro funds monitored by Aurum’s Hedge Fund Data Engine continued their recent run of positive performance in May, generating an average net return of 0.89%. Sub-strategy returns were generally positive. The exception, once again, was macro emerging markets, which returned -0.37%, continuing the sub-strategy’s weak performance seen year to date. |
Multi-strategy | ![]() | Multi-strategy funds monitored by Aurum’s Hedge Fund Data Engine returned an average of -0.84% in May. All size groupings of funds delivered negative performance. Mid/large funds (AUM of $2bn-5bn) delivered the worst performance, -1.29%. |
MARKETS | ||
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Major events | Markets remained volatile in May, but there were some signs of recovery in the second part of the month. Inflation readings, and central bank responses to them, were a key driver of market sentiment. Regions of China subject to COVID-19 lockdowns in China started to reopen. Digital assets, notably stablecoins Terra and Luna, sold off significantly. | |
Equities | ![]() | May was a month of two halves. Market disruption from April persisted into the first half of the month, but when data releases showed that inflation in developed markets showed signs of levelling off, equity markets responded positively. European, Japanese and UK equity indices outperformed US counterparts, but most major equity indices were positive for the month. |
Government bonds | ![]() | The recent run of negative performance in bond markets continued into May. Shorter dated US Treasury yields fell, but 30-year Treasury yields increased. Record high Eurozone inflation readings resulted in a spike in yields for European sovereign bonds on the last day of the month. |
Corporate bonds | ![]() | Corporate bonds performance was mixed in May. Investment grade credit was the strongest performer. Lower quality bonds generally lost money, although made a partial recovery towards month end. Emerging market credit was slightly positive by month end, but remains weakest year to date. |
Currencies | The US dollar continued to strengthen in the first half of May; supported by its safe haven status and the prospect of more aggressive interest rate hikes from the Fed. Despite the Bank of England’s 0.25% rate hike, the worsening economic situation in the UK restricted Sterling’s gains. The Russian ruble continued its recovery. |
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Commodities | ![]() | Commodity performance was mixed in May. Energy prices continued to increase. Concerns about supply were exacerbated by the EU’s ban on Russian oil products. Precious metals declined as demand for US Treasuries picked up, and base metals also declined as COVID-19 lockdowns in China impacted demand. |
The Hedge Fund Data Engine is a proprietary database maintained by Aurum Research Limited (“ARL”). For information on index methodology, weighting and composition please refer to https://www.aurum.com/aurum-strategy-engine/. For definitions on how the Strategies and Sub-Strategies are defined please refer to https://www.aurum.com/hedge-fund-strategy-definitions/