# Interpreting Fama-French factors for the German stock market

I calculated the Fama-French five factors myself for the German market. Most of my results align well with prior research, except one thing: When i do the calculations for the sub-period from 2011 to 2018, i get a negative mean for the HML factor albeit with a statistically non-significant t-statistic (<0.5). Before that and for the entire period (1990-2018) i get a positive mean and a statistically significant t-statistic (>2).

Can that be or am I doing something wrong? How should i interpret a negative HML factor return and what could be the reason for this change? All HML factors I have seen in international studies had a positive mean.

EDIT:

On my factor calculations: I use Thomson Reuters Datastream and followed Schmidt's et al. (2015) recommendation to clean my data from Datastream, but I didn't use their breakpoints. I used the breakpoints suggested by Fama/French (2016): Small is lower 10% of June market cap, big is upper 90% of June market cap. Then, the 30th and 70th percentile of the big group as breakpoints for other variables (HML, RMW, CMA). My book-to-market ratio for June of year $$t$$ is common equity (WC03501) + deferral taxes (WC03263) of fiscal year end $$t-1$$ divided by the december market value (MV) of $$t-1$$. Is there anything wrong with it?

Each June i sort them into big (top 90% aggregated market cap) and small (lower 10%). Independently, i calculate the 30th and 70th percentile breakpoints for the book-to-market ratio based on the big group and sort my companies into three groups: L(ow), M(edium), H(igh). The intersection of these two sorts generate six portfolios: SL, BL, SM, BM, SH, BH. I hold these portfolios from July of year $$t$$ until June of year $$t+1$$. Then, i re-sort my portfolios etc.

I calculate the monthly value-weighted returns. HML-return for month $$t$$ is: $$HML_r = \frac{r_{SH} + r_{BH}}{2} - \frac{r_{SL} + r_{BL}}{2}$$

EDIT:

On what stocks I exclude: As I said, I use Schmidt's et al (2015) paper to clean my data, both their static screens and their dynamic screen. I exclude companies with a lower market capitalization than 5 million euros though and i exclude all financial companies (SIC code between 6000 and 6999). Furthermore, to be included in my June sort of year $$t$$, i demand from the company to have all the return and the market value data from July of year $$t$$ until June of year $$t+1$$. I know that not all researchers do it like this, but some do (like Hanauer et al (2011)) and i think it's better to have more balanced portfolios like that.

• Besides US-evidence, the SMB-return in Germany is negative (i.e. large companies generate higher returns), but the other factor-returns and therefore HML-return should be positive in the german stock market (see table three here, similarly results in other studies hold up to the year 2018). Could you please describe in detail your steps on calculating the HML-return and provide details on what data set you have and what stocks you are excluding prior to any calculations? – skoestlmeier Nov 18 '18 at 10:50
• I edited my post. I am aware of this table. the weird thing is if I calculate the mean and t-statistics for the period 1996 until 2018 my HML factor is positive and highly significant with comparable values. also for 1996 until 2011. but not from 2011 until 2018. is smth wrong? – AahuM Nov 18 '18 at 11:00
• I meant 1990* until 2018 – AahuM Nov 18 '18 at 11:09
• I added a new edit for further clarification. – AahuM Nov 18 '18 at 11:13
• What are you regressing against? I mean, what is the stream of returns that you use as your portfolio? – Forgottenscience Nov 19 '18 at 13:23