Mapping My Mind: Value Factor
What have I learned so far?
June 2019. Reading Time: 10 Minutes. Author: Nicolas Rabener.
SUMMARY
- There is consistency in the performance of the Value factor across markets and asset classes
- Allows to create a coherent framework of how to think about Value
- Suggests a global driver of factor performance
INTRODUCTION
Our research aims to educate investors by bridging the gap between academic literature and practical investing. In contrast to our usual research notes, this one is more personal as I will document some of the key insights I have learned about the Value factor in recent years. The objective is to outline my current framework and update this as my education continues.
Naturally there are many academics and investors who have done far more work on the Value factor for far longer. In fact, most of our efforts are based on the research of others, which we analyze and then either challenge or aim to enhance by providing a new perspective. It is tough to innovate in quantitative research and I am not certain that we as a firm have found something truly unique yet, but we keep on searching.
However, there are also many conflicting views, which is one of the reasons why investing is so challenging. I believe it helps to occasionally step back and aggregate what I have learned into a coherent, data-driven framework.
This research note summarizes some of the basic characteristics of the Value factor performance.
HOW SHOULD VALUE BE MEASURED?
The Value factor is defined as buying cheap and selling expensive stocks. Academic researchers like Fama and French tend to use price-to-book multiples as valuation metric while practitioners prefer price-to-earnings, price-to-cashflow, or EV-to-EBITDA. Price-to-book is perhaps less accurate for valuing a company due to accounting reasons like stale book values, but investors should note that billions have been allocated to investment products using the metric given its important status in academic research.
In order to compare the different valuation metrics, we create beta-neutral long-short Value factor portfolios in the US stock market. The analysis highlights that the returns of the portfolios were heterogeneous since 2000, although they share common trends. For example, all portfolios generated strong performance after the Tech bubble imploded in 2000 and were more or less fl
