US recessions, the Value Factor (HML) and current status

The Fama-French value factor HML exhibits a fairly reliable 4 year cycle.  Growth and Value out-performance oscillates with a 4 year period (see my previous post on this).

Liew and Vassilou (1999), show that annual change in HML is related to future GDP change (see my blog post here).  Therefore tracking HML allows us to glean insight into upcoming economic conditions.

Where are we in the current cycle?


The black line is the 12 month moving average of HML.  St. Louis Fed recessions are in red.  HML lows clearly occur in years divisible by 4, although can lead or lag by a few months.  Lows correspond to high growth, which often (but not always) leads to recession.  One hypothesis is that the recession corrects the growth excesses in overheated parts of the economy.

HML is currently at or near the cycle low (circled).  Therefore conditions are in place for a potential recession.   Also of note is how rapidly value outperforms growth on recession exits.

Fortunately there are better recession forecasting tools than HML because the majority of market periods of extended weakness are coincident with recession.  The chart below shows the 12 month average of the Market Factor in black.

This highlights why using the sign of the 12 month return as an investment filter is so effective.  Once the return turns negative, the downturn is generally sustained.


However, the 12 month return may not provide an optimum re-entry signal.  Various oversold measures such as percentage of stocks below an N day moving average could be compared to typical recession levels to scale into value funds at low prices.

As the 12 month rolling return becomes increasingly negative, forward average annual returns rapidly rise:



Seasonality debunked (partially)

I’ve previously written about a bi-annual seasonality pattern in US equity markets:

The quarterly average market (Mkt-RF) returns from 1950 to present are shown below (data from Ken French’s library).  Quarters 1-4 are even years and 5-8 are odd years.


The table shows that mean returns of quarters 4-6 are greater than zero with high significance (t-stat > 2.3).

Except for Q8 which is marginal, all other quarterly means (including negative values) are not statistically different from zero (t-stat  < 2).  Therefore it is not possible to profit from this effect by excluding negative periods, hence the ‘partial’ debunking.

Caveats to these test results are that the dataset is small (32 points) and financial data is not normally distributed.


  1. Seasonality is a statistically significant effect:
    1. Quarters 4-6 have mean returns above zero.
    2. Other quarterly means are not statistically different from zero.
  2. A robust calendar strategy to avoid negative periods cannot be designed.

Cumulative market gains are zero across ‘even years’

Mkt-RF returns in ‘even years’ sum to zero over the last 50+ years (data from Ken French’s library).  This could be a spurious result although the stats suggest otherwise.


Is this result statistically significant?

Applying Student’s t-test gives a statistic of 2.3, i.e. mean returns of even versus odd years are different at the 5% significance level.