(no subject)
oppenhiemer
2 weeks left before the december lvl I results are announced!!
_______

(no subject)
oppenhiemer
Few more formulas that are similar in values, but slightly different in explanations.
They kind'a go together as an equity analyses and portfolio measures. 

1.2 SF Ratio (safety first)



so.. it calculates.... a difference between Expected Return and Lowest Risk Level /per standard deviation. In a situation when return cant fall below certain per cent point and we need to know the risk of this 'worst case scenario'.
the higher the ratio =the better, since any portfolio manager might want to be as far as possible from a vital 'risk threshold'

1.3 SHARPE Ratio 

Sharpe



same thing only subtracts Risk Free Rate (instead of Lowest Risk Level) and measures an 'excess return /per unit of risk'



(no subject)
oppenhiemer
off. cfa forum people say we need to bring our own pencils!! 
*should not forget! + they all say that test questions and wording is very similar to schweser. that is a good sign.

(no subject)
oppenhiemer

we should start our list of most widely used formulas. 

1.1 CAPM Model




it looks insane, but it truly shouldn't be viewed that way. the main idea here is....  that this basic relationship between the Risk -Free rate/ Beta /and Return on the Market always holds equated to Expected Return on Equity.  Any questions that mention "Beta" or Stock or "Market free Rate" will need this formula. 

they also can be tricky and name... (E(Rm)-Rf) =  as a "market risk premium"- but that should not confuse us. it basically simplifies the parenthesis to a single digit. 


(no subject)
oppenhiemer
damn. questions are tricky.  the answer can come up to ... say.. 4.9989898 and the range of the answers will be ..5, 3 to 5 or above 5.  making the second bracket to be incorrect, due to a rounding error.  + can be a lengthy explanation of a portfolio .. with various securities, with tax-questions, mentioning in one word that it is a pension plan (which is non- taxable regardless of the things it holds and how many pages they devoted to the question!).

therefore. eventually - the implied probability of a wrong answers-  stays the same across the board. тьху! 

(no subject)
oppenhiemer
more on luck.

it is a silly component, but anyone who ever took a difficult exam can never deny it exists and its influential. it can make a difference between getting a boarder line questions right or the questions that you even know - wrong. the chicago guy said everyone should 'wear their lucky underwear' )))))))) the problem is i don't have any. in fact - i don't have any 'lucky charms' that are somehow supposed to conquer luck. the web is full of 'lucky underwear and a first date" topics... which kin'd proves that at least the phenomenon is present. and i bet anthropologists can write lengthy articles on human mind perceptions and adaptation to various kinds of crazy stuff. o well... we'll just have to go with it. luck or no luck. 

(no subject)
oppenhiemer
"mark 'B' and move on" works!! the probability of guessing while keeping the parameters of guessing constant seems to improve the guess rates )))) 

Portfolio Management
oppenhiemer
since it utilizes many of the same principles of q-methods, here it is. 




the full version -- >   http://fotki.yandex.ru/users/passperfect-cfa/album/269463/  

the interesting assumption also exists, that on the test, if they ask us to rank portfolios in terms of "which is better? A or B?" (on the picture) - we always always select a portfolio "ABOVE' the Security Market Line, regardless of risks or returns. in this example  -we would go with a portfolio A. buy above the line!!

(no subject)
oppenhiemer
in q -methods also we need to keep track of all basic relations. like for example, if we know for a fact that some values can't be higher than the others- it will eliminate any need for calculations. 

NOIR  (french fro black) - we should put on our cheat sheet )))))))))) ranks any statistical data by precision. 
nominal < ordinal <interval<ratio  

also in interest rates the important moment was mentioned that
basically just 2 main ways of calculating interests.

(simple and compounded) 

simple uses 360 and 360/t formulas / compounded always 365 and 365/t 
simple is used in bills/notes/bonds / compounded always in equities and currencies

(no subject)
oppenhiemer
in q-methods the hardest seems to be all that z-table/ t-table/ f-table  statistical probabilities crap. 

but what was interesting...

is this notion that setting up a "null hypotheses" (can be any crazy idea, doesn't need to connect to reality in any way), so..."proving it' is never the case. it is a crazy idea anyway. all the questions on the test will be can we or can we not statistically reject it.and that's basically needs to come from a  memorization of when z-test and when t-tests (a student version) are used.

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