but as far as the literature I have read sofar (mostly from rating agencies), I have not read about any model using these CDS implied default probilities as input for their model. Does anybody know of any literature available about this topic?

<r>A question about the valuation of CDO's. As an input, one needs probabilities of default of the reference assets. As I understand it, S&P, Moody's and Fitch have their own assumptions for default probabilities, based on historical data. Would it also be possible (and would it make sense) to u...

<t>A question perhaps slightly offtopic: if I would try to reproduce a certain model, either based on this one or on another CDO paper, how could I test to see how it performs? For instance, is there any public available market information of certain deals, where I can compare my results for spreads...

-edit- Doublepost

<t>QuoteOriginally posted by: gjlipmanIf you divide by 10000 you will get the expected payout (under risk neutral approach). Then, you can discount that back three years at the risk free rate to get the present value.ok, that sound pretty straightforward :-)but what exactly do you mean by a risk neu...

<t>a somewhat related question... lets say that my payout depends on the performance of my share compared with the performance on another company. If my return is higher, I get the shareprice at the end times 1,5. If return over the three year period has been lower for my share, I get nothing.Using ...

What do you think is the best estimator for mu, the drift, for stockprices?Base it on historical data (average historical return), or take the beta of the stock and calculate the CAPM expected return? Or even an other method?

another question: when I let Excel calculate the correlations with the Data analysis toolpack, it gives other correlations then when I calculate them with Crystal Ball.Can anyone explain these differences?

when you specify your assumptions (you assign a probability distribution to a variable) there is a button 'correlation' there (or correl), there you can specify correlation, or let crystal ball calculate it.

<t>i have estimated volatility and drift from historical daily data.now i determine the end value of the stock with the formulaSt = So * e^((u-(d^2/2))t+d*sqrt(t)*E))with E a random drawing from a standardized normal distribution.Now does it mather if I calculate the end value of the stock after let...

ok searched it and the technique is mostly clear to me, should be able to replicate that.another question is what the general consensus is on predicting stock price movements. I think GMB is the most used model for this, but are there any other popular methods to simulate future returns?

<t>I am trying to simulate stock prices using GBM for a group of six stocks, each stock with its own assumption for expected return and volatility. Now I want the stockprices to be correlated, where correlation is based on historical correlation between stock returns. How can I model this? Is this d...

<r>The idea is based on an article by Hogan et al: Testing Market Efficiency Using Statistical Arbitrage with Applications to Momentum and Value Strategies (<URL url="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=386440"><LINK_TEXT text="http://papers.ssrn.com/sol3/papers.cfm? ... _id=386440">h...

<t>well I buy options on a certain stock A, and sell options on a stock B. I want the amount I sell to equal the amount I buy, to be equal in dollars that is. so let's say I buy option A for 4 dollars at time t, and its value rises to 10 at time t+1.I sell option B for 4 dollars at time t, and its v...

how should I determine the return on a dollar neutral investment strategy? that is, the amount invested in the long position is equal to the amount invested in the short position. therefore, the net investment is zero.should i take the sum of the returns of the individual positions?