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Relative vs Traditional Trend Following

Relative vs Traditional Trend Following

This summary is written by Rich based on a conversation in our CTA series between Bruno Gmür, Founder and CIO at Quantica Capital, and the podcast hosts, Niels and Alan.

About Quantica Capital

Bruno shared that Quantica Capital is a Zurich-based boutique investment management firm with a small team managing $800 million in their flagship product, the Quantica Managed Futures Program (QMF), which has an 18-year track record. 

The QMF program is a style consistent medium-term trend following strategy focused on liquid markets, trading only futures markets. The client base is highly diversified, with different investment vehicles available including UCITS, Cayman format, and managed accounts. 

Bruno discussed the investment philosophy behind Quantica's managed futures program, which focuses on medium-term trend following and liquid markets. He explained that his academic background in mathematics and experience in quantitative models led him to detect and implement trend following inefficiencies on a risk-adjusted basis between different markets or market segments. Their approach incorporates both time series momentum and cross-sectional momentum.

Quantica's differentiating factor lies in its focus on relative trends rather than on individual market trends, which expands their universe of potential markets to consider. By normalizing 100 markets to 100 risk factors, they can generate 10,000 spreads, allowing for a more robust and stable approach. This method considers the covariance structure of the market during signal generation, rather than only during the portfolio construction process, as is the case in time series momentum.

The persistence of these relative trends can be attributed to large investors implementing tactical moves and creating money flows between markets, which can be detected and followed by Quantica's approach.

While traditional trend following strategies (also known as time series momentum) analyze the trends of individual markets separately, Quantica's approach is based on comparing the trends between different markets or market segments on a risk-adjusted basis.

In their analysis, they normalize the markets to risk factors, which allows them to generate a large number of spreads (combinations of different markets). By examining these spreads, they are able to identify trends in the relative performance of different markets. This approach gives them a more robust and stable way of detecting trends and capturing market inefficiencies.

The focus on relative trends enables Quantica to better identify and follow money flows between markets, as large investors implement tactical moves and shift allocations between different market segments. As a result, their strategy can potentially capture more stable risk premia and be more resilient in different market environments compared to traditional trend following strategies.

Bruno explained that Quantica's approach of focusing on relative trends results in high correlation with other trend-following models, but the main difference lies in the sizing of positions. The correlation is determined by the direction of a signal, but the performance depends on position sizing.

The relative trend approach may not yield a significant difference in performance compared to traditional trend-following models. However, over the long term, taking into account the covariance structure and expanding the universe of market comparisons can improve the Sharpe ratio by about 0.2. While this may not seem like a significant improvement, it can be meaningful over a longer time horizon.

It's important to note that this improvement in Sharpe ratio does not guarantee consistent outperformance, and it might take a long time for the benefits of this approach to become evident.

The Role of the Sharpe Ratio

Bruno discussed the role of Sharpe ratio in evaluating the performance of trend-following programs. He believes that maximizing the Sharpe ratio is their mandate, as their investors want long-term performance. He differentiated between volatility as a measure of risk and the use of Sharpe ratio to gauge a program's success.

Niels wondered if having a lower Sharpe ratio and a more extreme trend-following profile could lead to higher long-term returns and be more beneficial as a portfolio tool. Bruno disagreed, stating that as a CTA, they invest exclusively in futures and use a daily rebalancing mechanism. This allows them to scale up exposures, maintaining the same Sharpe ratio while increasing returns and volatility. Bruno asserted that this can be achieved through the daily rebalancing mechanism, which is not possible with longer rebalancing periods due to the effect of compounding.

Challenges of Covariance Estimation and Effect of Volatility Shocks

Alan asked Bruno about the challenges in estimating covariance matrices, particularly during times of market stress, and how their system deals with market shocks. 

Bruno acknowledged that estimating covariance matrices and expected returns is difficult due to the inherent noise in financial markets. He explained that trend-following returns can be improved over the long term by taking the covariance structure into account. In the recent market shock, Bruno's approach had similar positions to traditional CTAs, so it neither outperformed nor underperformed.

Bruno also highlighted that risk management and portfolio construction play a significant role in position sizing, with more than 50% of portfolio changes after the shock driven by volatility. He noted that their methodology for estimating medium-term volatility and covariance matrices hasn't changed over the last 20 years and remains robust. Bruno concluded that a robust methodology is key for managing volatility, as it is impossible to predict shocks in the market.

Bruno and Niels further discussed the importance of estimating correlation and Bruno explained that their approach is model-driven, and if they knew the market parameters, expected returns, and covariance structure exactly, they would generate the best strategy. However, the challenge lies in estimating the covariance matrix, which is difficult due to the noise and shocks in the market. 

Bruno also highlighted the importance of having a robust methodology for estimating volatility and covariance that is stable and can manage medium-term volatility. They discussed the possibility of using different timeframes for estimating correlation and emphasize the need for a stable and robust approach to measuring risk.

Implementing Good Research

Niels and Bruno discussed the challenges of turning good research into a good live implementation. 

Bruno explained that their approach to research is to ensure that their models are very robust and have a low number of free parameters, which helps to reduce the dimension of the markets they trade in. They also believe that everything they do should make sense from a theoretical perspective or be explained by some market behaviour. 

They focus on diversification, adding many different sources of returns to inflate the Sharpe ratio, and the implementation of their systematic models with a threshold of overall implementation costs of less than 0.5% per year.

When it comes to adding new signals, they are very careful not to overfit, which is why their research is more focused on implementation, risk management, portfolio construction, and signal generation. 

They believe that they have learned a lot over the last 20 years to understand better where their approach comes from, how they can improve it, and how big any incremental improvement can be. 

They have a much better understanding of the market structure, the importance of diversification, and what they can do with implementation. Overall, their understanding of what they are doing has exponentially increased over the last 10-15 years.

Role of Trend Following in a Larger Portfolio and Risk Management

The topic of applying trend following in a multi-asset portfolio was raised, and Bruno discussed the importance of understanding the client's objectives when including trend following. 

He mentioned that if the objective is risk mitigation, then some restrictions may be placed on the trend approach, but overall, the long-term effect on the portfolio would be similar. Bruno also commented on the notion of investors wanting crisis alpha or tail risk protection and stated that while they want that, they are not necessarily willing to pay a premium for it. 

He believes that over the long term, targeting crisis alpha is not something investors should aim for, as it can negatively impact their long-term performance. He added that he has not seen any happy tail risk protection investors or managers in the past 20 years, but he might be wrong.

Bruno emphasized that the characteristics of trend following vary over different time frames, with the full benefits being seen on a quarterly basis, making it regime independent or smart diversification. He expressed concerns about the term "crisis alpha" and proposed replacing it with "negative crisis beta" for trend following strategies. 

Bruno also discussed the use of replicators in trend following, saying that while they are transparent and may have cost advantages, they have disadvantages such as suboptimal risk management and diversification. He believes that a diversified research product has a better value proposition than just a replicator.

Return Expectations of Trend Following

Bruno's long-term outlook for trend following has not changed over the last 18-20 years. His view is that the approach should lead to a long-term Sharpe ratio of approximately 1 on a gross basis before fees but after implementation. However, he acknowledged that this can only be achieved by adding some incremental improvements and expanding the universe, adding more diversification, and improving on risk management techniques. 

Trend following is a painful strategy, and most of the time, investors may be underwater, which makes managing it difficult. However, the successful trend following CTAs stay around for 15, 20, 30, 40 years, showing resilience in the industry. 

Misconceptions of Trend Following

Bruno disagreed with the statement that trend following is dead, which he has heard every few years for the past two decades. He believes that despite the challenges, last year's performance is a good example of how trend following can still work. Bruno emphasized the importance of taking a long-term view and sticking with trend following through difficult periods. 

Outlook for 2023

Bruno is excited about the fact that their firm has a fully systematic strategy and that they operate within the futures space, which provides risk-adjusted liquidity, an advantage in times of uncertainty. 

He also disagreed with the statement that trend following is dead and sees a long-term Sharpe ratio of 1 on a gross basis as achievable.

This is based on an episode of Top Traders Unplugged, a bi-weekly podcast with the most interesting and experienced investors, economists, traders and thought leaders in the world. Sign up to our Newsletter or Subscribe on your preferred podcast platform so that you don’t miss out on future episodes.