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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: Estimating a Log Periodic Power Law model with some constraints |

Date |
Mon, 22 Mar 2010 14:55:15 -0000 |

We quite often see questions like this and some of the time their motivation is very unclear. Quite often it seems that people are confusing constraints with their expectations or hypotheses about parameter values. Whether that's true here, Stata does not really offer much direct support for constraints defined by inequalities. Why not fit directly? If the constraints are satisfied, there is no problem. If not, then the model appears a poor choice for the data -- or, according to taste, the data are a poor choice for the model. This may sound a flippant response, but I think this strategy not only is simpler but also offers more scope for learning something new. Nick n.j.cox@durham.ac.uk Mehmet I Canayaz I am trying to estimate a Log Periodic Power Law model (a simple version can be found here:http://econophysics.econ.univpm.it/econpapers/abstract/Bree.pdf ) on some financial data and I am having some difficulties. The model reads: P(t) = A + B * (t_c - t) ^ z + C * (t_c - t)^z * cos ( w * ln(t_c - t) - r) with the following constraints: B<0, 0<z<1. My first idea was running a nonlinear least squares model on (price) P(t) and (time) t with the many coefficients such as A, B, t_c, C etc. to be estimated.[t_c is of extreme importance since it shows the time of a future burst in a financial bubble]. The problem is: I don't really know how to assert the mentioned constraints on nonlinear least squares in Stata. Stata doesn't allow me to create a constraint and call it like: nl y x, cons(1) If you have a better estimation method for this formula or have an idea on how to fulfill the constraints I would appreciate your help. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: RE: Estimating a Log Periodic Power Law model with some constraints***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

**References**:**st: Estimating a Log Periodic Power Law model with some constraints***From:*Mehmet I Canayaz <mehmet@nyu.edu>

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