Kettera Strategies' Geographical Analysis - May 2020
In a recent analysis by Kettera Strategies, discretionary macro strategies demonstrated positive returns and outperformed quant and systematic-driven macro strategies in June 2025 [1]. This performance difference can be attributed to key determinants such as manager discretion, flexibility in responding to macroeconomic changes, and performance outcomes as measured in monthly return baskets.
Discretionary macro strategies, which heavily rely on human judgment and decision-making, allow for adaptability to real-time market changes. This flexibility can potentially capture inefficiencies that are not accessible via systematic models. On the other hand, quant macro strategies use algorithmic, data-driven models to systematically process market signals. Their results tend to be more rule-based and data-dependent, which may underperform discretionary approaches in volatile or rapidly changing environments.
Kettera's research methodology involves creating style baskets, which aggregate returns of programs with shared characteristics. These baskets track relative performance, but are not investible products themselves. The weighting of programs within these baskets depends on approval status on Kettera's Hydra platform, rather than on volatility or correlation.
The performance of style baskets presented in this analysis are research tools created by Kettera Strategies for analysis and comparison purposes, and are not investible products or index products being offered to investors.
Short-Term programs, which have an 'intraday to two-day' average trade period and use ST breakout models, performed well, particularly in the precious metals market. However, strategies with greater commodities exposures did not perform well in Discretionary Macro strategies this month.
In the equities market, most managers and styles did reasonably well, with Event driven strategies being the standout. While most agricultural markets were flat and unexciting, many of the ag spread programs did well. Energy traders faced challenges, with crude oil traders underperforming, while nat gas traders, especially in European markets, did much better.
Systematic Trend Programs had a "give-back" month, with most programs making gains in long equities index positions and short fixed income markets, but surrendering these profits in currency and commodities markets.
Discretionary Macro strategies had returns that were scattered across the spectrum this month. The indices and financial benchmarks shown are for illustrative purposes only. Kettera disclaims any obligation to verify these numbers or to update or revise the performance numbers.
The Eurekahedge AI Hedge Fund Index and the Societe Generale Short-term Traders Index are listed as benchmarks for this analysis. Other benchmarks mentioned include the Eurekahedge Long Short Equities Hedge Fund Index, the Hedge Fund Intelligence Global Macro Index, the HFI Currency Index, the CBOE Eurekahedge Relative Value Volatility Hedge Fund Index, the S&P GSCI Metals & Energy Index, the S&P GSCI Ag Commodities Index, the Societe Generale Trend Index, the SG CTA Index, the BarclayHedge Currency Traders Index, the BTOP FX Traders Index, and the Eurekahedge-Mizuho Multi-Strategy Index. A blend of BarclayHedge Equity Market Neutral Index with Eurekahedge Equity Mkt Neutral Index is also listed as a benchmark.
It is important to note that the views expressed in this article are those of the author and do not necessarily reflect the views of AlphaWeek or its publisher, The Sortino Group. The performance of these indices may be updated from time to time by their respective providers.
[1] Kettera Strategies. (2025). Kettera Macro Manager Performance Analysis - June 2025. Retrieved from https://www.ketterastrategies.com/research/macro-manager-performance-analysis-june-2025/
The Eurekahedge AI Hedge Fund Index and the Societe Generale Short-term Traders Index are among the benchmarks used in Kettera Strategies' analysis of discretionary macro strategies versus quant macro strategies. The key determinants that differentiate these strategies, as observed in the June 2025 analysis, relate primarily to their performance patterns and management style.
Discretionary macro managers, who heavily rely on human judgment and decision-making, demonstrated positive returns and outperformed quant and systematic-driven macro strategies during that period. This is due to their ability to adapt to real-time market changes and potentially capture inefficiencies that are not accessible via systematic models.
Quant macro strategies, on the other hand, use algorithmic, data-driven models to systematically process market signals. Their results tend to be more rule-based and data-dependent, which may underperform discretionary approaches in certain volatile or rapidly changing environments.
Kettera's research methodology for segmenting macro programs involves creating style baskets that aggregate returns of programs with shared characteristics. These baskets track relative performance, but are not investible products themselves. The weighting of programs within these baskets depends on approval status on Kettera's Hydra platform, rather than on volatility or correlation.
The performance of style baskets presented in this letter are research tools created by Kettera Strategies for analysis and comparison purposes, and are not investible products or index products being offered to investors.
In June 2025, Kettera Strategies' analysis showed that discretionary macro strategies outperformed quant macro strategies. The key determinants that differentiate these strategies relate primarily to their performance patterns and management style.
Discretionary macro strategies, which rely heavily on human judgment and decision-making, demonstrated positive returns and outperformed quant and systematic-driven macro strategies during that period. This is due to their ability to adapt to real-time market changes and potentially capture inefficiencies that are not accessible via systematic models.
Quant macro strategies, on the other hand, use algorithmic, data-driven models to systematically process market signals. Their results tend to be more rule-based and data-dependent, which may underperform discretionary approaches in volatile or rapidly changing environments.
Kettera's research methodology for segmenting macro programs involves creating style baskets that aggregate returns of programs with shared characteristics. These baskets track relative performance, but are not investible products themselves. The weighting of programs within these baskets depends on approval status on Kettera's Hydra platform, rather than on volatility or correlation.
The performance of style baskets presented in this letter are research tools created by Kettera Strategies for analysis and comparison purposes, and are not investible products or index products being offered to investors.
- The analysis by Kettera Strategies indicated that discretionary macro strategies, relying on human judgment and decision-making, outperformed quant and systematic-driven macro strategies in June 2025 due to adaptability to real-time market changes and potential inefficiency capture that may evade systematic models.
- In the same analysis, quant macro strategies were found to underperform discretionary approaches in volatile or rapidly changing market environments, as they use algorithmic, data-driven models that offer more rule-based and data-dependent outcomes.
