finance - 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.