Investment Approaches

PMP participants are divided into three groups, each focusing on a distinct investment framework, explored theoretically and implemented practically.

Academic research describes a wide range of investment strategies with attractive risk/return characteristics. However, such strategies often neglect real-world frictions that make them difficult to implement in practice.

The academic approach uses a two-step process to develop attractive investment strategies. The first is to seek to reproduce the findings from the academic literature. To the extent that the claimed effects are indeed present in the data, students then develop implementable versions of the strategies, investigate their performance, and identify the likely sources of their returns. Strategies found to be sufficiently attractive are then combined into an overall portfolio.

Primary Supervisors: Prof. Thorsten Hens and Dr. Alexandre Ziegler

In the fundamental approach, investment decisions are made by applying a structured framework built on three pillars (macroeconomic analysis, company fundamentals, and market sentiment) to consistently outperform the benchmark. The group operates across multiple asset classes and within the constraints typical of institutional investors, such as pension funds.

Primary Supervisor: Ivan Kraljevic, UBS

In the quantitative approach, investment decisions are made using data-driven algorithms. These algorithms are trained by using statistical and machine learning methods on empirical market data. An important aspect of quantitative methods is to guarantee the consistent implementation of risk controls and assess factor exposures a posteriori to understand the drivers of returns.

Primary Supervisor: Adrien Hardy, QRT

Investment strategies are implemented within a target set of asset allocation weights. All groups are also required to set up an adequate risk management process as well as develop a suitable documentation and controlling process within the predetermined framework.