Fundamental Flow Factors Strategy
By Alan Gigi and Martin Geissmann | October 15, 2020
Fundamental flow factors strategy focuses on a companies' fundamental metrics. Factors computed from related companies’ fundamentals such as the return on equity (ROE), return on assets (ROA), or the earning yield are used to predict the performance of the target company’s stock performance.
Using the related companies recently reported fundamentals (and especially the change in fundamentals) is an appealing approach to forming portfolios.
For financial metrics, we wanted to invert the portfolio construction method used above. Instead of building the L/S portfolio with a long position from the highest quantile and a short position from the lowest quantile, we choose the opposite. The long exposure would be on stocks whose peers recently had a decrease in a metric and a short exposure on stocks whose peers recently had an increase. The logic is that if suppliers (or customers) of a company report increasing profit margins, ROE, ROA, or earning yields, this indicates that they siphon off a larger share of the total value created as opposed to just sending more funds to their suppliers. Stock performance can come from increasing revenues or increasing margins, and it is important to check both.
We find positive performances especially in strategies based on signals from the supplier ROE and earning yield (see table 1). This backs the hypothesis that if further up the supply chain increased profit margins are achieved, the company in focus is likely to be contributing to that increased profitability by overpaying. As a result, the company tends to perform worse than its peers.
Table 1: Sharpe ratio of fundamental flow strategies
The same L/S strategies formed on customers’ metrics still lead to positive returns, however with considerably lower SR. (See graph below)
We do not report the results on the portfolios constructed from the absolute financial metrics figures (as opposed to the changes), mainly due to them giving ambiguous results. It has to be assumed that the bare figures do not mean much as a static snapshot of a supply chain in temporary equilibrium. In other words, there is nothing inherently special about any given level of ROE, ROA, etc. for generating subsequent returns in the stock market. Rather, it is the changes in these metrics and their associated impact on the supply chain that matters. Markets can also be driven by surprises, i.e. deviations from the consensus’ expectations, but we lack meaningful historical data to perform such a backtest.