Dear R users,
I am working on the Value at Risk (VaR) for the Operational risk. For a given
loss data, we try to fit some statistical distributions using Kolmogorov-Smirnov
(KS) test and A-D test and then for fitted distribution using the estimated
parameters, the losses are simulated and the VaR is arrived at.
The typical problem faced by the banks is the paucity of Internal loss data and
thus banks depend on the external loss data obtained from external sources. This
external data is normally of higher magnitude than the internal loss data of the
bank. Thus using regression technique, this external data is scaled and then the
internal data and the scaled external data is combined. Then we try to fit some
statistical distribution to this combined data. However, at times it becomes
very difficult to fit any distribution to this particular combined data as the
data becomes Bimodal.
The paper by G. Dionne and Hela Dahen " What about underevaluating
Operational Value at Risk in the Banking sector?" suggests that we fit two
distributions
(1) to the internal data (called body part) with Upper cap or upper bound to the
loss data and
(2) to the external data with Lower bound (called Tail part).
Thus, now I am dealing with two truncated distributions (i) having a lower loss
bound (say 5000$ i.e. bank records only those losses exceeding 5,000$) and
having an Upper bound of say 500,000$; and (ii) having lower loss bound of say
500,000$ and no upper limit.
My question is
(1) Is there any R package which helps to estimate the parameters of
"various" Truncated distributions?
(2) How to fit the truncated distributions to loss data in the sense how do we
use KS and AD tests?
Extremely sorry for writing such a long mail.
Regards
Julia
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Only a man of Worth sees Worth in other men
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