But in Poddar, the woman board of director is quite qualified. Impressive qualification rather.
Recently there has been a spate of bad news in the Credit Rating agency space. A link posted by Vivek suggests that these cos have let us down.
However, a little bit of Bayes type probabilistic thinking would have led to a surprising finding perhaps tempering the blame game a little bit - not completely though.
Even if the rating agency is very accurate in giving a good rating to companies that wonât default, there is a reasonably high chance that cos who defaulted had a good rating
The question is thus, given that a company has defaulted, what is the probability that it had an excellent rating?
Turns out that, that probability is 9%. That means that ~10% of all the defaults will probably have good credit ratings.
Data collected from CRISIL Default Study report 2018 contains the necessary data that we can plug into a Bayes type analysis.
Data source : https://www.crisil.com/content/dam/crisil/our-analysis/publications/default-study/CRISIL-Default-Study-2018.pdf
As per CRISIL, the overall default rate is 4.4%
They have given CDR (Cumulative Default Rate) data only uptil 3 years but on page 19 they mention the average time to default for AAA rated instruments as 177 months. But since there is no data beyond 3 years I will take 3 years.
The crux is this, âGoodâ ratings are those which are in the âAâ category ( AAA,AA and A) and Bad ratings are the ones in the B&C category ( BBB,BB,B and C).
To cut a long story short, based on the data above suggests 1.1% default within 3 years even for the rockstars ( that itself is disturbing)
Here is the probability distribution. I have assumed a 50:50 split between the bad rating and good ratings.
| Item | Default | No Default | Total |
|---|---|---|---|
| Bad Rating | 10.0% | 90.0% | 50.0% |
| Good Rating | 1.0% | 99.0% | 50.0% |
| Total | 5.5% | 94.5% | 100.00% |
Bayes theorem says that
P(Good Rating given that you have Defaulted) = P(Good Rating)* P(Default given that you have a Good Rating)/P(Default)
OR
0.5*0.01/0.055 = 9%
Even though credit ratings agencies are generally very good at assigning ratings given and 99% of AAA rated cos dont default , the probability that a co which has defaulted with good credit ratings is still ~10%
For Bayes, one could possibly go to ( a good source as well)
Best
Bheeshma
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Value Quest Moat Fund & Mirae Asset fund exits completely from Narayana Hrudalaya. Prof Bakshi bought it at near about 300 levels & exited at about 230 odd level. Main reason could be the recievable days while dealing with the Govt. which he recently reflected in his tweets.
VQ has cut a lot of other holdings too recently namely Tvs srichakra 100%, accelya 56% (& kitex 100% & poddar100â° in past) .
So VQ is either sitting on huge cash or deployed already somewhere else (only his current batch students would know)
Source : Latest shareholding data by BSE for Q1 2019
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Maybe Bajaar.me has not updated the public holdings. According to them 29.6 is NH, 29.4 CCL, 15.2 Wonderla, 13.2 Ambika, 8.9 Accelya, 3.6 WIM plast.
Complete exits : TVS srichakra
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yes they (bajaar.me) canât update the site so fast unless they have AI bots reading from the bse & updating instantly, which I doubt they have.
It is indeed Poddar. She is the COO of Poddar Housing and no other information except her name in the Corporate Information Page in 2018 Annual Report.
it could also be massive fund outflows because of poor performance of the fund
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WimPlast is a new addition.
[Note: The performance of the fund is not great if this data is to be believed - https://www.trustnet.com/factsheetpdf?url=https:%2F%2Fwww2.trustnet.com%2FFactsheets%2FFundFactsheetPDF.aspx%3FfundCode%3DKXF5I%26univ%3DB&Citicode=kxdz&Universe=B&Fundcode=KXF5I&Sectorcode=B:EIN]
could you please elaborate on which company this is?
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Alex this link is for q2 2017 shareholding 
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Any reason found why he exited relaxo? Just because it has become expensive?