mseGBM: Mean square error between empirical PDF and time-dependent...
In shill1729/findistr: Common distributions used in finance
mseGBM R Documentation
Mean square error between empirical PDF and time-dependent Gaussian
Description
The mean-square-error between the empirical PDF of daily log returns against a time-dependent
GBM model. Used for numerical calibration to the empirical density.
Usage
mseGBM(theta, epdf, h, idynamics)
Arguments
theta
parameter to optimize
epdf
object returned from density(), the empirical probability density function.
h
time-scale
idynamics
the integrated mean and volatility functions, as a list
Details
Here the coefficients in the SDE dS_t=\mu(t) S_t dt +\sigma(t) S_t dB_t are assumed
to be functions of time.
Value
numeric
shill1729/findistr documentation built on May 20, 2024, 9:43 a.m.
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| mseGBM | R Documentation |
Mean square error between empirical PDF and time-dependent Gaussian
Description
The mean-square-error between the empirical PDF of daily log returns against a time-dependent GBM model. Used for numerical calibration to the empirical density.
Usage
mseGBM(theta, epdf, h, idynamics)
Arguments
theta |
parameter to optimize |
epdf |
object returned from |
h |
time-scale |
idynamics |
the integrated mean and volatility functions, as a list |
Details
Here the coefficients in the SDE dS_t=\mu(t) S_t dt +\sigma(t) S_t dB_t are assumed
to be functions of time.
Value
numeric
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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