The evolution of quantitative strategies has led to the need for hundreds of alpha forecasts with varying timeframes and signal strengths, highlighting the importance of constantly introducing new alpha signals and enhancing existing ones while managing risk and portfolio construction.
Managing a multi-strategy program requires normalizing and comparing alpha forecasts from different models, combining them into a global portfolio while respecting risk limits and constraints, and maintaining the integrity of individual signals during trade execution.
Deep dives
Introduction and Background
In this podcast episode, Corey Hofstein interviews Osif Nor, the portfolio manager at Aspect Capital, about his experience developing systematic macro strategies and managing a multi-strategy program. Nor discusses the challenges and evolution of quantitative strategies over the past 25 years, including the need for hundreds of alpha forecasts with varying timeframes and signal strengths. The conversation highlights the importance of constantly introducing new alpha signals and enhancing existing ones, but also emphasizes the need for risk management and portfolio construction. Additionally, Nor touches on the benefits of collaboration, data availability, and the use of technology in systematically investing.
Combining Alpha Signals and Portfolio Construction
Nor explains the process of combining alpha signals in the multi-strategy program. The team normalizes and compares the alpha forecasts from each model, treating them as long-short portfolios with standardized risk targets. These portfolios are then combined into a global portfolio, which is optimized to account for risk limits and constraints. Nor emphasizes the importance of managing conviction and risk when dealing with multiple alpha signals. He mentions the challenges of unifying alpha forecasts across different time horizons, but reiterates the significance of maintaining the integrity of the individual signals while executing trades based on their respective forecasts.
Managing Uncertainty and Marginal Benefit
The discussion delves into the balance between conviction and risk management. Nor notes that when all signals strongly converge on a trade, caution is required to mitigate concentration risk and potential asymmetric losses. He highlights the importance of risk management in such situations and leans towards prioritizing risk control over maximizing conviction when faced with highly correlated signals. Additionally, he emphasizes the significance of enhancing existing alpha sources with high-confidence improvements rather than relying on untested or low-accuracy signals.
Operational Challenges and Future Trends
Nor acknowledges the operational challenges of implementing short-term alpha signals, emphasizing the importance of having an efficient execution research team and robust infrastructure. He mentions the significance of accurate and timely data, data processing capabilities, and minimizing execution delays and estimation errors. He expresses excitement about the evolution of the space, particularly the availability of diverse and rich datasets, including alternative data sources, advanced modeling techniques like chat GPT, and the ability to forecast at high frequencies. Overall, Nor anticipates that these advancements will make the systematic investing landscape more exciting and offer greater potential for consistently outperforming benchmarks.
In this episode I speak with Asif Noor, Portfolio Manager at Aspect Capital where he oversees the firm’s Multi-Strategy Program.
Asif has spent the last 25 years of his career developing systematic macro strategies, giving him a depth and breadth of experience to understand what it takes to remain competitive in the space.
While a handful of low frequency signals may have been sufficient a few decades ago, today Aspect’s Multi-Strategy Program incorporates hundreds of alpha forecasts ranging from intraday to several months. But this evolution also brings new challenges, which we discuss at length in this episode. For example, how are new alphas introduced and old alphas sunset? How do you unify alphas of different magnitudes and convictions? Or, how do you manage risk across so many signals?
This conversation is chalk full of the practical, real world experiences of running a multi-strategy program.
Please enjoy my conversation with Asif Noor.
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