<r>Hi,I have lately read an article about some hedge fund establishing a factoring fund.<URL url="http://www.cbsnews.com/news/another-investment-to-avoid-like-the-plague/The"><LINK_TEXT text="http://www.cbsnews.com/news/another-inv ... plague/The">http://www.cbsnews.com/news/another-investment-to-av...

<t>I tried, as an exercise, to reconcile the DCF(FCFF), DCF(FCFE) and Market Value of Debt.Not only that I failed, it raised additional questions as to NPV concept.The example is follows.Assumptions:Investment (Capital) = 500Debt = 250 (50%), perpetuity bond, market interest rate 9% meaning that the...

If I understand correctly, "yes" refers to unlevering - I should use volatility of asset rather than that of an equity.Please correct, if I got you wrong.Thanks for the answer.

<t>I have noticed that in several books on Corporate Finance, such as Brealey and Meyers, or Berk and DeMarzo, they use the volatility of equity as an input to Black and Scholes.Furthermore, in case the company is not traded, they suggest to use volatility of equity of the comparable traded company....

<t>Then I really fail to understand what is the relevance of this sentence in the Matlab help forum quote:"A PCA applied on what is known as the second moment matrix, i.e., data'*data, will have the mean of the data built into the eigenvectors.".I apply PCA to an original data - interest rates, equi...

<t>Thanks.I've read this thing from Matlab (that is exactly what I got in Matlab help search) and the pdf you attached. I might be completely off but that is exactly what I don't understand.To be more precise, I am not sure I understand the following part of the attached (pasted) explanation:"A PCA ...

<t>No.The eigenvectors are already normalized in both cases.My question is regarding the centering the original data matrix.1. In my matrix the data vectors are columns and rows are points in time.From each data vector (a column) I subtract the mean of the column thus creating the new column vectors...

Hey all,Why is it important to center data, i.e. subtract the mean from each data vector prior to computing the principal components matrix?More important question: when it is imperative to center data and when it is not?Thanks,G

<t>CLT is simple to use. CLT is used to produce results quickly when you don't know the distribution of the population (which is usually the case).The precision of the results calculated with CLT depends on how close your samples follow the assumptions of the theorem. Namely, to what extent your sam...

Thank you, guys.It feels wrong on many levels: from discrimination of other shareholders, not acting in a good faith and up to a somewhat broadened definition of "insider trading".G

<t>Let?s assume you are a businessman that plans an entry into a regulated market that was recently opened for a competition.You raise a lot of money, you get license, regulatory approval.You know that till now this market was de-facto a cartel.You plan to lower the prices significantly.One day befo...

Thanks.

<t>Thanks a lot, Tad. But somehow I have more questions than before.GARP notes mention the expected value of the loan at the time of default. Naive question number 1:What is the definition of the expected value of the loan? Is it a loan value discounted with expected return (not the contractual one)...

<t>Hi,I am trying to evaluate credit risk of a bond portfolio and the first step is to calculate expected loss:EL = Exposure * PD * LGDI have a few questions:A bank purchases a bond at a discount. What is the exposure: is it the face value or the paid price?Is it different for bonds purchased at the...

<t>Thanks,Yeah, I am aware of the last 60 days average, etc...The issue was that I got enormous EC comparing to regulatory charge on market risk.I mean that rough factor of 3*sqrt(10) in regulatory charge could not even close compensate for the 99.98% confidence level and sqrt(250) in EC calculation...