Content area
Full text
I n this article, we examine the research process and principles underlying successful models used in quantitative equity strategies. The research process is at the heart of the development of successful quantitative strategies. Key factors for their success are the availability of more and better data, advances in computational and econometric methods, and better understanding of how to enhance judgment in the research process. Our discussion does not provide rules to follow, but rather tenets that emerged from our collective experience of researching and developing quantitative models.
By identifying and examining the characteristics of quantitative strategies, we attempt to highlight some best practices in quantitative modeling and aspire to outline a broader paradigm for building successful models. These characteristics may not be strictly statistical or mathematical in nature, but rather they emphasize the integration of market dynamics, data, research design, modeling techniques, and economic and financial judgment.
InSuperforecasting , Tetlock and Gardner [2015] state that "foresight isn't a mysterious gift bestowed at birth. It is the product of particular ways of thinking, of gathering information, of updating beliefs." In this article, we share some insights on accomplishing this objective by providing a framework and some thoughts on building quantitative forecasting models. Our discussion centers on developing quantitative models regardless of asset class, but our examples draw heavily from equities. Although we focus on quantitative research methodologies, we think that some of these ideas are valuable for a fundamental research process.
WHAT ARE QUANTITATIVE MODELS?
In this article, we refer to quantitative modeling in a broader sense. A quantitative strategy is a systematic, data- and model-based approach to making investment decisions. We can further qualify quantitative strategies by their underlying core characteristics. By examining these core characteristics, we can attempt to identify some best practices in quantitative modeling to develop a paradigm that will lead to building successful models.
The most important characteristic of the quantitative modeling approach is the scientific approach. This approach provides a paradigm that guides and informs empirical work. Similar to other fields that take a scientific approach--including natural sciences, medicine, and social sciences--this approach in quantitative modeling attempts to describe, inquire, and interpret with precision. The characteristics of a scientific approach as it relates to quantitative equity strategy modeling include...