10 May 2021
April 2021 - Macro Systematic Strategy – Pervasiveness of dispersion inter and intra asset classes - Systematic Fund Manager's Comments
Pervasiveness of dispersion inter- and intra-asset classes
The path in global financial assets is dictated by of a multitude of short, mid and long-term factors. To name a few, central banks/fiscal policies, corporate earnings and investors’ flows inevitably create dispersion, offering at the same time opportunities for systematic strategies designed to capture inefficiencies over different time horizons.
The essence of systematic strategies is to benefit from dispersion in financial markets, but it would be too simplistic to leave it here. The biggest challenge lies in the pace of adaption to changing market conditions. Therefore, both trend and mean-reversion strategies bear high importance, but they do not necessarily work at the same time over an entire economic cycle.
Statistical hierarchy between assets
At RAM, our Macro Systematic strategy aims at capturing dispersion inter- and intra-asset classes. The process is based on trend and mean-reversion modelling of the interrelations between assets at two levels, macro (government bonds, equity indices, commodities and currencies) and micro (single name equities), rather than a modelling of assets on a standalone basis. The inherent rational behind this process is that the interaction between assets provide much powerful results from a robustness and Sharpe ratio perspective.
Importance of short-term strategies
In the last 20 years, quantitative modelling has emerged as a “technological” solution to address financial problems. The evolution of trading techniques, methods, tools and softwares is slowly but naturally following the progress of hard science. Hence, with more data, tools and models, financial and economic cycles have shortened. Nowadays, the pace at which a market is shifting between Bull and Bear regimes is almost 5 times faster than 25 years ago. In this research we will give an overview of different stylized facts regarding the increased impact and hence the importance of short-term strategies in contemporary financial markets.
The complementarity of trend strategies in Futures: the agricultural case.
With the COVID crisis commodities as an asset class experienced a strong momentum. Our strategy is based on a proprietary Genetic algorithm process that builds portfolios of short, mid, and long-term strategies implemented to take advantage of trend and reversal trading across and intra asset classes. In the commodity-agricultural sub-universe there is a very small numbers of reversal patterns found. Therefore, it leads our exposure to this sub-space to be dominated by the trend component mostly through longer-term (superior to 100 days lookback) as depicted by the gross exposure in the chart below.
Source: RAM AI, as of 30.04.2021
Digging deeper in the analysis of agricultural exposure reveals very interesting investment cases such as soybean oil. This Agri-commodity exhibits a very strong long-term patterns since March 2020. However, as depicted by the cumulated contribution breakdown (below chart), one can see that short-term trend strategies (less than 10 days) have been also creating alpha. This chart shows how important it is to not only diversify though trend and reversal but also through long term and short term.
Source: RAM AI, as of 30.04.2021
RAM Diversified Alpha Fund (UCITS) – strong YTD performance
Our Systematic Macro strategy in the UCITS version delivered a strong +8.31% return YTD (PI share class, as of 30.04.2021). This performance has been realized thanks to the commodities, bonds and single name equities exposure. It is worthwhile to note that our models have swiftly adapted to the trend reversal in government bonds, while this pocket trigged losses for strategies focusing only on mid to long-term.
Finally, we outline below the key characteristics of our Macro Systematic strategy, which we believe represent an interesting value proposition in a global portfolio allocation.
The Strategy acts as a real diversifier in a global portfolio allocation. It is not only uncorrelated to peers but to major asset classes too. The goal is to offer a positive expected return over medium to long term.
• Multi-dimension dispersion analysis
Alpha creation results from an unbiased analysis of multiple explanatory variables used to model the dispersion across and intra assets. Hundreds of millions of alphas are created artificially and then carefully selected through a heuristic optimisation process.
The model is calibrated multiple times per year to take into account evolving market conditions. On top of that, the frequency of signals spanning from short, medium and long term, enables the Strategy to capture market information in the most robust way.
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