Monthly Archives: May 2013

Bond Risk: Calculating Value at Risk (VaR) for Bonds. Here are two common challenges that come up when we apply risk management concepts to individual bonds and bond portfolios: a) How do you measure risk of a newly issued bond that has no history of trading prices b) How do you integrate the risk of a bond issued [...]

About Finance Training Course.com – our story Sometimes when you have been working on an idea for a decade and a half it is easy to assume that everyone loves it as much as you do. Or is aware of the back story. This morning two prospective customers asked me about who we really are and why [...]

Yahoo-Tumblr acquisition – How did the math work out?I think there are multiple methods at work here: a) Traffic Integration - What is Tumblr’s Traffic worth to Yahoo? What can Yahoo sell to these customers or sell these customers for? Over the next 5 years  how much revenue would this traffic add to Yahoo’s bottom line?  Read the [...]

Value at Risk – Calculating Portfolio VaR for multiple securities with & without VCV Matrix .In an earlier VCV Matrix post we had presented the theoretical proof of how the portfolio VaR obtained using the short cut weighted average return method produces the same result as would have been obtained if a detailed Variance Covariance [...]

Nate Silver – Signal vs Noise. Book review Overconfidence regarding our prediction skills often leads to worse predictions in situations where there is a high level of uncertainty surrounding an event. In the book by Nate Silver “The signal and the noise – why so many predictions fail but some don’t”, uncertainty is represented by the [...]

Table H Recently a visitor to FinanceTrainingCourse.com, who had seen our basic introductory course on developing commutation functions, requested us to recreate the commutation tables used by the IRS in the US, Table H. Table H contains commutations factors, at various interest rates, that are used in the valuation of annuities, life estates, and remainders.The tables contain [...]

A key element in the construction of the Black Derman Toy interest rate model is the setting up and running of EXCEL’s Solver function. The Solver functionality links various parts of the model together, the inputs- initial zero curve rates and their volatilities, the calculation cells – price lattices and short rate tree, and the [...]

The Black Derman Toy (BDT) model is a one-factor, no-arbitrage interest rate model. One-factor in that the entire term structure of interest rates can be inferred with reference to the process underlying the short rates derived. No-arbitrage in that th...