Levermann Score

Susan Levermann (Wiki) developed this strategy working as a Fund Manager at DWS managing the  DWS Provesta fund with 1.7 billion USD value,  across german and european stocks. In 2008 she was awarded “Best Fund Manager” 1- and 3 years running and later published the successful strategy in her book

”Der Entspannte Weg zum Reichtum, ISBN10 3423346752, dtv 2011″

which would translate to

“The relaxed path to wealth”.

The book was awarded with the german book award in finance in 2011 (Finanzbuchpreis).

In an interview [2] she has postulated that

“A successful trader is not the one reading the stockprices in the morning brushing his teeth, nervously staring at the screens 24h and yelling at his mobile phone. It is by far more important to learn how to control your emotions and be disciplined…”

While other traders at DWS were frantically searching through the news and figuring out the state of the market, she was running her calculations on her database of around 3000 names and had time for a lot of coffee breaks [2].

Since Levermann’s strategy yields Buy as well as Sell recommendations –

this 13-score system can be regarded as a quantitative arbitrage strategy.

Since it became popular many traders have started using it. For example, the biggest fund (sorted by AUM) on the german investment platform (Wikifolio) is using this strategy across german names only. There are other online services which offer Levermann notifications either as paid subscriptions or only for certain limited regions.

In contrast we offer the Levermann strategy for all regions globally for free!.

Here is a quick summary of the 13 points, which look similar in parts to the Piotroski F-Score, but Susan’s list is definitely more extensive since it includes performance comparisons.

Metric\Score +1 0 -1
1 RoE LJ >20% [10%,20%] <10%
2 EBIT-Marge LJ >12% [6%,12%] <6%
3 Eigenkapitalquote LJ >25% [15%,25%] <15%
4 KGV 5 Jahre <12 [12,16] >16
5 KGV aktuell <12 [12,16] >16
6 Analystenmeinungen Verkaufen (2.5 bis 3.0) Halten (1.51 bis 2.49) Kaufen (1.0 bis 1.5)
7 Reaktion auf Quartalszahlen positiv zwischen -1% und +1% negativ
8 Gewinnrevisionen steigend zwischen -5% und +5% fallend
9 Kurs heute gg. Kurs vor 6 Monaten steigend zwischen -5% und +5% fallend
10 Kurs heute gg. Kurs vor 1 Jahr steigend zwischen -5% und +5% fallend
11 Kursmomentum steigend Zeile 9: 1Pkt Zeile 10: 0 od -1Pkt ansonsten Zeile 9: -1Pkt, Zeile 10: 0 od. 1Pkt
12 Dreimonatsreversal Perf. In jedem Monat < DAX ansonsten Perf. In jedem Monat > DAX
13 Gewinnwachstum EPS AJ < EPS NJ zwischen -5% und +5% EPS AJ > EPS NJ
* LJ = Letztes Geschäftsjahr, AJ = aktuelles Geschäftsjahr; NJ = nächstes Geschäftsjahr, EPS = Gewinn je Aktie


The scoring is calculated based on the table above and then summed up over every stock. If a stock doesnt have a score for a particular value we value this score with the worst-case-scenario in order to be conservative, meaning -1 for that particular score. This makes sense for the Buys. For the Sells this doesn’t make sense and we ignore those names where we don’t have a full set of 13 scores, in order to be conservative.

We then filter for the Top10 by Score and Market Capitalisation (MarketCap) and separate BigCaps from MidCaps (incl. SmallCaps). There are therefore 4×4 =16 signals per week with a list of max 10 names each for buy & sell. So a total of max 160 names per week to buy or sell.

The scoring then determines whether you get a Buy or Sell signal for the stock and one differentiates between BigCaps and MidCaps.
For BigCaps a stock is bought if the Levermann Score is >= 4 and sold if it is <=2.
For MidCaps a stock is bought if the Levermann Score is >=7 and sold if it is <=4.

BigCap is defined as MarketCap > 10bn$, MidCap <10bn$.

The Levermann Buys we sort by the Levermann Score and the Levermann Sells we sort by MarketCap descending.

You can browse all signals of the Levermann category here.

[1] ARD Börse vor Acht: “Das Levermann Prinzip 100” 2017-06-02
[2] Neue Zürcher Zeitung : “Erfolg hat, wer Langeweile aushält” 2010-05-09

We use Cookies to improve our Site. Your are agreeing to this by continuing to use our Site.