# Tag Info

## Hot answers tagged term-structure

5

The original Vasicek paper is "An equilibrium model of the term structure". If you google for it, you'll find it and you can read in his own words his motivation for developing it. In particular, what now is called the Vasicek model basically comes from applying his results to an Ornstein-Uhlenbeck model for the spot process, which he claims was proposed by ...

5

It's because of the settlement days you passed when you initialized the flat volatility curve. You're creating the spot, forward and flat volatilities as: boost::shared_ptr<BlackVarianceSurface> volatilitySurface( new BlackVarianceSurface(todaysDate, calendar, maturityArray, strikeArray, ...

4

There are two different issues at play here. One is that, of course, you want only the future cash flows to enter the calculation. This is taken care when you set the evaluation date to 6 months from today. In C++, you would say Settings::instance().evaluationDate() = today + 6*Months; I don't remember the corresponding function in QuantLibXL, but you ...

3

I will refer to "Interest Rate Models - Theory and Practice: With Smile, Inflation and Credit" by Damiano Brigo and Fabio Mercurio. In chapter 3 (One-factor short-rate models) they have a very nice table which lists some of the properties of instantaneous short rate models. In both of your models you know the distribution of $r_t$. The huge difference ...

2

I would look at the following metrics when quantifying "liquidity" in listed options: bid/offer spread number contracts traded and from that follows notional traded (in the option not underlying) frequency of bid/offer adjustments relative to changes in the underlying delta. frequency of liquidity added/removed on the bid and offer side even when no ...

1

I think the rationale behind it is that if $r$ is the short rate, the the price of the bond is $P(t,T) = \mathbf{E}e^{- \int_t^T r_s ds }.$ As is well known by know is easy to calculate expectations of random variables of the form $e^Z$, where $Z$ is Gaussian. This model is the simplest example of a case in which the integral of the short rate as Gaussian ...

1

A PCA explains the variation in data. A slope PC is usually identified by the pattern of the signs of the loadings. If the loadings of short term contracts have the same sign which is different from the sign of the loading of longer term contracts then such a PC is identified as slope PC. It means that if this PC goes up or down it affects short term ...

1

Nelson Siegel seems to be pretty standard too

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