# Recommended Time serie forecasting model for Fibonacci levels classification

I have a set of time series data which gives me fibonacci levels and the duration at which the value is at this level. Data structure to look like:

Date / Duration (minutes) / Level

201201 / 380 / 2
.....

210422 / 400 / 4


I'd like to create a NN model (LSTM maybe) that would forecast the next level, the probability it reaches it and this for several steps ahead (1 step = 400 minutes). Which time series forecasting model would you recommend ? Thanks in advance.

• Could you explain what a Fibonacci level is? I'm not sure what you are trying to achieve with your model. What is the desired output? Apr 28 at 19:34
• Fibonacci levels in stock price (for example) is defined between the minimum and the maximum price during a given period. The range (min, max) is chunck in levels. Below min and above max levels are called extension levels. So, let's say that I look at 1 year back. It gives me my level and I start classifying and I count the duration in minutes price stays in each level. I am now trying to have a time series prediction model which tells me the probability that in X minutes, it should be at the level Y with a given probability. Hope it's clear, if not I am happy to explain more. Apr 28 at 19:38
• So basically, instead for predicting the actual value of the stock price, you want to know in which range the price will fall in and for how long? Apr 28 at 19:44
• Exactly this with a given probability Apr 28 at 19:45