Support Board
Date/Time: Mon, 10 Mar 2025 01:55:43 +0000
log-periodic power law model
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[2013-06-18 20:02:18] |
yoytu - Posts: 59 |
I wonder how hard it is for SC devs to implement this LPPL model like a studie on SC ? The LPPL model correlates the price with the time in the following formula:
log(p(t))=A+Btm+Ctmcos(ω⋅log(t)−ϕ) In this formula, t is the time (measured backwards in days from tc), A is the logarithm of the price at tc, ω is the angular log-frequency, B and m measure super-exponential acceleration (B>0 and 0<m<1), C is the magnitude of the log-periodic oscillations and ϕ is the phase shift. (see: first article) The main difficulty in fitting this model is its high non-linearity. One strategy would be to try a sufficient space of combinations for the non-linear parameters (m, ω and ϕ), after which use a linear-fitting method to find the A, B, C parameters (e.g. using R). link:https://tasmania.ethz.ch/challenges/entrepreneurial-risks-eth-zurich/projects/new-social-bubble-bitcoins#chapter-3 |
[2013-06-18 23:04:56] |
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This is not something we have time for, but you can certainly implement this yourself. Here is the documentation: http://www.sierrachart.com/index.php?l=doc/doc_CreatingDLLs.html Sierra Chart Support - Engineering Level Your definitive source for support. Other responses are from users. Try to keep your questions brief and to the point. Be aware of support policy: https://www.sierrachart.com/index.php?l=PostingInformation.php#GeneralInformation For the most reliable, advanced, and zero cost futures order routing, *change* to the Teton service: Sierra Chart Teton Futures Order Routing |
[2022-03-14 05:38:36] |
User751739 - Posts: 29 |
@yoytu did you ever build this out? I'm currently looking in not this as well.
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