# trying to find the probability of a certain price in the oil market being touched within a time frame

#### pythonicon

##### New Member
I have built a model that predicts closing prices of the oil market. My goal is to make a model that can help find the probability of reaching a certain price within a certain time frame but I am lost. For example, if oil is at 60.00 a barrel, I would like to know how to find the probability of it reaching 63.00 within 14 days. I am not sure which probability model to use for this. I have thought about using a logistic regression model; however, that does not seem to work because of the binary choices that I have for the dependent variable. I thought about drawing trendlines on oil prices and calculating the probability of a reversal once a support/resistance line is touched by a candlestick. I would just identify the candlestick reversal pattern, among other momentum oscillators, and give it a 1 or 0 based if it reversed. The problem with my current time series model is it only gives the probability on a certain date of reaching a price when I need the probability of it occurring within a time frame. I thought about the exponential probability distribution but that doesn't seem practical.
Any help to identify what type of model or prob/stat method would help me with this.

#### hlsmith

##### Less is more. Stay pure. Stay poor.
Some type of bayesian time series or Monte Carlo simulation would allow you to see how often forecasts reach that threshold, which could be used to calculate a probability via the frequency of the occurrence.

Logistic isn't traditionally used in time series, which is what you are describing.

#### pythonicon

##### New Member

Yes, I am aware that logistic is a regression concept and not a time series concept. I was going to use the logistic regression model to calculate the probability of a reversal at support/resistance lines since I was having trouble trying to find the probability of the price reaching a certain time frame within a certain time frame.

I will certainly look into a bayesian time series model; thank you

#### gw1

##### Member
How accurate is the model that predicts closing prices on the oil market? How does it hold up with unknown unknowns e.g. war breakouts, pandemics, subprime mortgage collapses?