Kettera Strategies' Heat Map Update - May 2021
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In the dynamic world of Hedge Funds and Managed Futures, May 2021 was a month of contrasting strategies, as highlighted by the CBOE Eurekahedge Relative Value Volatility Hedge Fund Index. This article delves into the profitable themes that emerged in discretionary macro programs and model-driven (systematic) macro programs during this period.
Discretionary macro programs, characterised by fundamental analysis and a focus on macro outlooks, profited from policy shifts, government bond markets, and currency markets. These strategies often capitalised on pro-growth policies or geopolitical events, taking advantage of trends over medium-to-long terms. Notably, common profitable themes involved long positions in precious metals, selected bond markets, and short positions in Bitcoin, with scaled-back positions in commodities.
On the other hand, model-driven or systematic macro programs, such as Managed Futures, thrived on market volatility and price momentum. These programs, which often include the BarclayHedge Currency Traders Index and BTOP FX Traders Index, profitably capitalised on increased volatility through trend following and short-term bursts of price movements, often capturing risk premia that shift with market uncertainty.
The systematic approach's main opportunity arises from shorter-term bursts of volatility and risk premia shifts induced by market uncertainty, leveraging quantitative models to validate trades and enhance discretionary decisions. In May 2021, the prevalent theme among systematic trend programs was that gains in FX and commodities outweighed setbacks in equities and fixed income.
The performance comparison between discretionary and model-driven macro programs was a topic of interest in May. Kettera Strategies, for instance, found that discretionary managers outperformed model-driven strategies during this period. This distinction underscores how discretionary managers emphasise macroeconomic fundamentals and policy insights for positioning, while models focus on exploiting volatility patterns and market regimes detected through quantitative methods.
In the energy sector, crude oil specialists faced a challenging month, with prices falling mid-month then rallying strongly. Iron ore spot prices rose 25% in the first half of May before giving it back, rewarding nimble managers. Grain markets, meanwhile, were volatile due to unexpected U.S. acreage and yield reports and contradictory demand rumours. Relative value traders using calendar spreads and inter-commodity ratio spreads generally performed better than outright directional strategies in these markets.
The way the USD weakened against most of the G10 currencies allowed for gains to be captured by most programs. Strong upwards moves in gold, silver, and copper benefited commodities directional strategies. Natural gas traders, however, faced a tight, range-bound market with a late-month price spike that quickly faded.
In conclusion, May 2021 was a month that underscored the value of both discretionary and systematic macro strategies. While discretionary managers anchored on macroeconomic narratives and policy drivers, model-driven strategies relied on systematic signals derived from volatility and momentum in macro instruments like bonds, currencies, and commodities. As we move forward, it will be interesting to see how these strategies evolve and adapt to the ever-changing market landscape.
Disclaimer: The views expressed in this article are those of the author and not necessarily those of AlphaWeek or its publisher, The Sortino Group.
Finance and technology played crucial roles in both discretionary and model-driven macro programs during May 2021. For instance, discretionary managers utilized fundamental analysis, macro outlooks, and policy insights to make well-informed decisions, supported by data and cloud computing systems. Similarly, model-driven strategies, such as Managed Futures, employed quantitative models to capitalize on volatility patterns and short-term bursts of market movements, further leveraging technology for trade validation and enhancing discretionary decisions.
