time series analysis

Hi All - I have built a very simple model. I have developed a regression model in MS EXCEL to predict if the FTSE 100 is fairly, under, or overvalued. Forecasting EPS: Dependent variable - Trailing 12 months EPS (£) Independent Variables - Brent Crude Price ($), Bloomberg Industrials Metal...

I am trying to run a Mann-Kendall over a group of files, to perform the MK on each one. This is precip data, for each area, over decades. I read the data into R, then create df "datalist". I bind all the files into one, and then split them by the name in the first column ("V1"). This all works...

Does any body know how to convert a mixed DataFrame containing both Unix and datetime to datetime only feature(with Python) Data frame head is given in the below attachment P.S Please help. I can not find solutions from the net.

I'm trying to identify a trend in some monthly precipitation time series data (2000-2020). The data are non-normal so I'm running a Mann Kendall test and a Sen's slope test to find the significance and magnitude of the trend. I've found that the data show a significant positive trend (tau = 0.4...

Hey everyone, I am currently doing a coursework for uni and I need some help. I don't have a background in stats and this is not a statistics course so I am confused. I have a dataset of daily air quality, which have numerous gaps - some small (one day missing), some big (over a month of...

Hey everyone, i'm struggling with modelling some times series to get residuals with white noise characteristics. I use SPSS for ARIMA modelling and exponential smoothing and Gretl for stationary testing with the Augmented-Dickey-Fuller and the KPSS-Test. My workflow: At first I use Gretl to...

Hey everyone, i have a question about the results I get when I do a cross correlation of two white noise time series with SPSS 21.0. Why do I get two different results depending on how much variables I insert in the window for the cross correlation? For example: If I insert the variables...

Hello, I have already corrected the stationary of my elements with diff, but to analyze the VaR (), CVaR (). It is necessary to create a portfolio, I have seen many packages that have left me confused. How is the procedure to create a crypto portfolio? that is I must assign all the columns of...

Hello there! I am struggling at the analysis part of my thesis. I want to compare countries according to their growth rates over time. So in other words, do they increase or decrease over time more than the others or less… I saw that time series panel data regression with dummy coding for the...

As part of my University research project, I have decided to study the impact of Immigration on house prices but find that the immigration Variable that should be statistically significant according to literature appears to be insignificant. I don't know whether this was down to the method I...

Hi everyone, currently I'm working on a project where I want to test effects of external indicators on internal sales data. So I already collected a lot of data and now want to compare two time series. But there are some things I'm not sure about: Is it recommendable to decompose each time...

I need to find the solution to this question, could someone help? Consider the stochastic process {Xt;t ∈ Z}. Let fX(λ) = |1 +1/3 eiλ|2 be the spectral density function and RX (t) be the autocovariance function of {Xt; t ∈ Z}. What is the value of RX(1).

Hi all, i have a very simple question, because i am not good at statistics but i need that :) I have two signals, one is lets say 'x' another is 'time', so its a time serie. I need to find the upper and lower values of my signals according to confidence interval and then show them on a graph...

Hi, assume that we have time series with autocorrelated values described by the regression model Y_i ~ X_i. As far as I understand, in AR-regression models, this correlation is considered by assuming that residuals are autocorrelated. Instead, I could introduce additional predictors...

Hello there, I would like to know what would be the best method to measure the relationship between variables like life expectancy and income over time (years)? In my case I have a time series with around 30 years. I would like to examine if there is a dependence between variables like life...

There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...

There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...

Describe what role Exploratory Data Analysis (EDA) has in the application of time series modeling. Include: (a) Why is testing for a normal distribution important? (b) Why is testing for skew and kurtosis important? (c) What role does hypothesis testing play? (d) What distribution is used for...

Hello everyone, I am new to this forum and I would need some help on a time series regression model with financial variables. I am regressing Y=S&P500 Health Care index c X=bookmaker odds for the victory of Hillary Clinton x=S&P500 x=USD/EUR everything is in dlog, and I use the lag of...

Checking a variable for I(1) process, when should i use a ADF vs DF test?