Nicolas Mirjolet - Multivariate Trend Following (S7E8)
May 27, 2024
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Nicolas Mirjolet, CEO of Quantica Capital, discusses the challenges of scaling a statistical arbitrage fund and the advantages of larger players in asset management. He explains Quantica's multivariate trend-following approach, emphasizing the trade-off between diversification and convexity in trend strategies.
Scaling a business in a capital-constrained space is easier for larger players due to benefits like broad alphas and cost-saving netting trades.
Quantica's multivariate trend following approach aims for stable returns with low cross-correlations by analyzing relative risk-adjusted returns among instruments.
Quantica's research focuses on expanding the investment universe, maintaining style consistency, and balancing liquidity and risk factors in portfolio construction.
Deep dives
Nicola Mirjaleg's Insights on Scaling Statistical Arbitrage Businesses
Nicola Mirjaleg shares his experience operating a statistical arbitrage fund and discusses what makes a strategy easier or harder to scale a business on. He emphasizes that in this capital-constrained space, smaller players face challenges due to high turnover, trade execution costs, and cross exposure. The larger players gain an edge due to the breadth of alphas they can deploy and structural advantages, such as netting trades to save on execution costs.
Quantica's Multivariate Approach to Trend Following
Quantica's flagship managed futures program employs a multivariate approach to trend following, led by Nicola Mirjaleg. This approach involves analyzing relative risk-adjusted returns between different instruments in the investment universe, focusing on price dynamics and capital flows. By generating a larger number of signals and maintaining lower cross-correlations between instruments, Quantica aims to achieve stable returns across varied market environments, offering a balanced performance profile.
Innovation and Future Research Directions at Quantica
Despite running a consistent flagship program for over 20 years, Quantica continues to innovate in three main areas: expanding the investment universe, refining signal generation and portfolio construction processes, and exploring implementation strategies. Nicola Mirjaleg highlights the ongoing research projects focused on maintaining style consistency while pursuing a target sharp ratio of one, demonstrating a commitment to evolving within the realm of intermediate to slow trend following.
Identifying Liquidity Criteria for Instrument Selection
Maintaining accuracy in liquidity models is crucial for strategic integration based on asset liquidity levels. Despite tracking over 400 potential instruments, only 103 are actively traded to ensure a cohesive liquidity profile. Enhancing liquidity aids trend following strategies by reducing cross-correlations and adding uncorrelated instruments. Balancing liquidity and risk factors in portfolio construction is vital, with a focus on modeling diverse relative trend measures.
Analyzing Performance Attribution and Risk Factors in Trend Following
Decomposing trend follower profit and loss into independent risk categories reveals insights into trend performance drivers. A principal component analysis uncovers uncorrelated statistical risk factors influencing trend profitability. The study highlights an inverse relationship between trend performance and the number of independent risk factors required for replication. Historical analysis demonstrates the impact of macroeconomic trends and idiosyncratic factors on trend following success, emphasizing the balance between macroeconomic drivers and differentiated trends.
In this episode, I speak with Nicolas Mirjolet, CEO and Co-Head of Research at Quantica Capital.
We begin with Nicolas’s experience operating a statistical arbitrage fund, where he provides his thoughts as to what makes a strategy easier or harder to scale a business on. Nicolas also provides some context for his somewhat counter-intuitive view that the larger players had a bigger edge in this capital constrained space.
We then transition to Quantica’s flagship managed futures program. Nicolas explains that while Quantica is a price-based trend follower, they apply a multivariate approach to their signal analysis. We discuss how the approach works and how it contrasts against a standard univariate approach. Specifically, Nicolas shares his thoughts on how the multivariate approach impacts the portfolio return profile and why you may want more or fewer variables in your signal universe than your tradable market universe.
We end the conversation with Quantica’s most recent quarterly research paper, which provides quantitative insight into the convexity versus robustness tradeoff trend managers make when they add more markets to their portfolio.
Please enjoy my conversation with Nicolas Mirjolet.
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