I*******i
发帖数: 1703 | 1 Currently I am working on a project where I use HW interest rate model to
forecast future short rate r(t,t )and long rate r(t,T).
when i backtest my prediction against realized rate, say the long rate r(t,
t+1year) that is calculated according to HW, there is a consistent positive
bias of my prediction ( meaning prediction > realized )
Anyone here has related experience working with HW interest rate model? Is
there a theoritical explaination on this phenominon?
I am using a fixed mean reversion | i****e
发帖数: 78 | 2 没用过HW模型,不过常识来讲,还没有模型能预测市场的将来.
HW模型也只是个模型而以.
,
positive
【在 I*******i 的大作中提到】
: Currently I am working on a project where I use HW interest rate model to
: forecast future short rate r(t,t )and long rate r(t,T).
: when i backtest my prediction against realized rate, say the long rate r(t,
: t+1year) that is calculated according to HW, there is a consistent positive
: bias of my prediction ( meaning prediction > realized )
: Anyone here has related experience working with HW interest rate model? Is
: there a theoritical explaination on this phenominon?
: I am using a fixed mean reversion
| a*****k
发帖数: 704 | 3 楼住的问题我不是很明白
我想一般我们用HW来pricing options.
首先应该是fit the yield curve.
forecast是怎么弄？
【在 i****e 的大作中提到】
: 没用过HW模型,不过常识来讲,还没有模型能预测市场的将来.
: HW模型也只是个模型而以.
:
: ,
: positive
| f*******y
发帖数: 988 | 4 extrapolation呗
【在 a*****k 的大作中提到】
: 楼住的问题我不是很明白
: 我想一般我们用HW来pricing options.
: 首先应该是fit the yield curve.
: forecast是怎么弄？
| n****8
发帖数: 23 | 5 If you have both positive or negative bias, it is normal since no model can
predict the rate perfectly. But persistance positive biase means something
wrong.
HW is affine term structure models. If you use 1 factor HW, it doesn't
capture non parallel shift of the term structure. Hence the TS you forecase
could only show paralell movement, which result in persistance positive or
nagative bias.
If you use 2 factor models, it can allow non parallel shift. But there are
many format of 2 factor models | I*******i
发帖数: 1703 | 6 Thank You Very Much!!
We r using 1 factor hw model..could u explain more abt this part?
"HW is affine term structure models. If you use 1 factor HW, it doesn't
forecase
and what r the possible sources of persistent positive or negative bias in
this case?
can
appear
there |
|
