opuntia83 said:Can anyone help me to found the the likehood fonction for Log-periodic-power-law ?
The maximum likelihood function for LPPL (Log Periodic Power Law) is a mathematical function used to estimate the parameters of a financial bubble. It is based on the theory that financial bubbles follow a log-periodic power law distribution, which means that the bubble grows at an accelerating rate before ultimately crashing.
The maximum likelihood function for LPPL works by finding the set of parameters that maximizes the probability of observing the data given a specific model. This is done by iteratively adjusting the parameters until the likelihood function reaches its maximum value. The resulting parameter values are then used to make predictions about the future behavior of the financial bubble.
The key assumptions of the maximum likelihood function for LPPL include the assumption that the financial bubble follows a log-periodic power law distribution, that the bubble will eventually burst, and that the data used to estimate the parameters is accurate and representative of the underlying process.
One of the main advantages of using the maximum likelihood function for LPPL is that it provides a quantitative method for identifying and predicting financial bubbles. It also allows for the estimation of the timing and severity of the bubble's collapse, which can be useful for investors and policymakers.
Some limitations of the maximum likelihood function for LPPL include its sensitivity to the initial parameter values, the need for accurate and reliable data, and the assumption that the financial bubble will eventually burst. Additionally, the model may not be able to capture all the complexities and nuances of real-world financial bubbles.