Code covered by the BSD License  

Highlights from
Weighted generalized Hurst exponent

Be the first to rate this file! 17 Downloads (last 30 days) File Size: 2.37 KB File ID: #36487

Weighted generalized Hurst exponent

by

 

01 May 2012 (Updated )

Computes the generalized Hurst exponent with exponential weights

| Watch this File

File Information
Description

This code calculates the weighted generalized Hurst exponent H(q) from
the scaling of the renormalized q-moments of the distribution

      <|x(t+r)-x(t)|^q>_w/<x(t)^q>_w ~ r^[qH(q)]

                  
Here <f>_w are weighted averages of f(t) over 0<= t < T
with weights
      w(t) = w0 exp(-(T-t)/delta)
and
      w0 = (1-exp(-1/delta))/(1-exp(-T/delta))

H = genhurstw(S)
S is 1xT data series (T>50 recommended)
calculates unweighted H(q=1)

H = genhurstw(S,q)
calculates unweighted H(q) specifying the exponent q
which can be a vector (default value q=1)

H = genhurstw(S,q,delta)
calculates weighted H(q) specifying the characteristic time delta
 
H = genhurstw(S,q,delta,maxT)
calculates weighted H(q) specifying the characteristic time delta
and the size of the scaling window maxT

[H,sH]=genhurstw(S,...)
estimates the standard deviation sH(q)

examples:
  generalized Hurst exponent for a random gaussian process
  H=genhurstw(cumsum(randn(10000,1)))
or
  H=genhurstw(cumsum(randn(10000,1)),[1,2]) to calculate H(1) and H(2)
or
  H=genhurstw(cumsum(randn(10000,1)),[1,2],100) to calculate weighted
  H(1) and H(2) with chractreistic time delta = 100

for the generalized Hurst exponent method please refer to:
  T. Di Matteo et al. Physica A 324 (2003) 183-188
  T. Di Matteo et al. Journal of Banking & Finance 29 (2005) 827-851
  T. Di Matteo Quantitative Finance, 7 (2007) 21-36
for the weighted Hurst exponent method please refer to:
  R. Morales et al. Physica A, 391 (2012) 3180-3189.

MATLAB release MATLAB 7.13 (R2011b)
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Updates
31 Jan 2013

minor changes

Contact us