Skip to main content

Questions tagged [arima]

Refers to the AutoRegressive Integrated Moving Average model used in time series modeling both for data description and for forecasting. This model generalizes the ARMA model by including a term for differencing, which is useful for removing trends and handling some types of non-stationarity.

Filter by
Sorted by
Tagged with
0 votes
0 answers
11 views

Why does the forecast for some series degrade when using a VARMA model comparing to independent ARMA models?

I am working with multiple time series that I suspect are correlated, and I have assumed that using a VARMA model would at least not degrade the forecasts of each series, if not improve them. However, ...
Rocio's user avatar
  • 1
1 vote
0 answers
37 views

ARIMAX: only MA(1) model gives meaningful coefficients for exogenous variables

Is it possible that the coefficients for the exogenous variables in (regression with ARIMA errors) are only meaningful with MA(1) models? Here is my reasoning and a simulation. I would be grateful ...
Arthur's user avatar
  • 556
4 votes
1 answer
108 views

Choosing Between Intercept-Only and AR-NN Models: Justified to not use the model with the lowest RMSE/MAE?

I have created two autoregressive models for forecasting: a basic intercept-only model and an AR-NN (autoregressive neural network) model. Both models show similar performance based on recursive one-...
george1994's user avatar
0 votes
0 answers
14 views

Manual MLE of AR(1) yields a weird initial value $y_0$

I am playing with a manual implementation of the maximum likelihood estimator (MLE) of the parameters in an AR(1) model $$ y_t = c + \varphi_1 y_{t-1} + \varepsilon_t $$ with $\text{Var}(\varepsilon_t)...
Richard Hardy's user avatar
1 vote
0 answers
26 views

Understanding ARMA model fit

I fit an ARMA(1,1) model using statsmodels in python to a univariate data series and got seemingly very significant fit. Log likelihood: 200,000 AIC/BIC/HQIC: -400,000 AR.L1 : 0.1 (z 45) MA.L1: -0....
dayum's user avatar
  • 643
0 votes
0 answers
7 views

How to calibrate and simulate a copula-garch model in R using rmgarch package

So I have been trying to calibrate and simulate cryptocurrencies for VaR and ES analysis using the rmgarch package in R. I have been using the t-copula, my reason being that cryptocurrencies' ...
Xerium's user avatar
  • 1
1 vote
1 answer
99 views

How to adjust hyper-parameter values of SARIMAX as we move month on month

I am trying to build a SARIMAX forecasting model to forecast availability of technicians across all 50 US states over 12 weeks horizon. I have a seasonal data hence going in with SARIMAX. Sample data ...
Karthik S's user avatar
0 votes
0 answers
21 views

How do I write a mathematical equation for ARIMA (1,1,1) x (1,1,0) period 12 [duplicate]

I would appreciate it if someone could assist me in writing the mathematical equation for the seasonal ARIMA (1,1,1) x (1,1,0) period 12. I'm a little confused with how to go about this. I would ...
Numan's user avatar
  • 1
0 votes
0 answers
23 views

Residual autocorrelation in ARMA-GARCH model

I have used the auto.arima function on my data set, which is the Ethereum-USD exchange rate, and I end up with an ARMA(2,2) model based on the AIC. I have estimated ...
Htcharnock's user avatar
4 votes
2 answers
156 views

How is mean-reversion behavior captured within ARIMA models? What coefficients determine speed of mean-reversion?

Suppose we have an AR(1) model: $X_{t} =\phi X_{t-1} + \epsilon_{t}$. If $|\phi|<1$, then $X_{t}$ process follows a mean-reverting behavior. Now, instead of simple AR(1) model, let's consider the ...
Sane's user avatar
  • 465
1 vote
0 answers
33 views

Forecasting ARIMA(0,0,1) model by hand - trouble with MA elements

I am having issues forecasting a stationary ARIMA(0,0,1) time-series. I currently have 500 observations of the process, and want to predict the coming three periods. Using Stata software, I am able to ...
Ohoma's user avatar
  • 11
0 votes
1 answer
31 views

ARIMAX-GARCH flattens when using daily return, but not level

Whenever I do my ARIMAX-GARCH model for forecasting n-ahead with sentiment from news as my exogenous variable, the predictions seems normal when forecasting using level price of the stock, but it ...
BarneGeniet's user avatar
0 votes
0 answers
20 views

Importance of stationarity for ARIMA/ARIMAX/SARIMAX for predictive purposes

I am doing a forecasting project right now and I could use some understanding of why stationarity is importance when forecasting in general. Especially for the SARIMAX model. I know the problem of ...
Mathias Nissen's user avatar
0 votes
0 answers
32 views

ARIMA model underestimates

What steps should we take if my ARIMAX model consistently underestimates? Furthermore, should this underestimation be a significant concern in my analysis? Edit: I am doing an ARIMAX forecast where I ...
BarneGeniet's user avatar
0 votes
0 answers
12 views

How can we apply sensitivity analysis in comparing two ARIMA models, both measuring intervention effect?

I have a dataset of reporting rates collected over an 8-month period obtained from the baseline (4 months) and during intervention (4 months). The goal is to determine if the intervention has a ...
George Mwenye-Phiri's user avatar
1 vote
0 answers
34 views

Variance of ARMA$\left(2,2\right)$ model

Find $Var(∇Y_t)$ if $Y_t = 5 + 2Y_{t-1} - 1.7Y_{t-2} + 0.7Y_{t-3} + e_t - 0.5e_{t-1} + 0.25e_{t-2}$. I've reduced this down to $∇Y_t = 5 + ∇Y_{t-1} - 0.7∇Y_{t-2} + e_t - 0.5e_{t-1} + 0.25e_{t-2}$. ...
Random user33's user avatar
0 votes
1 answer
23 views

Why the differenced at lag 12 time series of a SARIMA(0,0,0)(0,1,1)_12 model follow the MA(1) pattern with step 12?

I am trying to understand why the ACF of the seasonally differenced series reveals the AR of MA structure of the original series. For example: The following lines creates a SARIMA(0,0,0)(0,1,1)_12 ...
Epameinondas's user avatar
0 votes
0 answers
24 views

What is the ARMAX model specification of the following economic setting?

I am currently doing a project estimating electricity prices in France, however, my modelling skills are lacking. I have hourly data on spot prices, which are determined per separate hour, one day ...
Zillah's user avatar
  • 31
1 vote
0 answers
35 views

Autocorrelation and ARMA model

Consider the market model for security $i$ $$ R_{i,t}=α_i+β_i R_{m,t}+e_i $$ I'm estimating the parameters of this model (alpha and beta) using OLS. However, the Breusch-Godfrey test indicates the ...
Mattia's user avatar
  • 151
0 votes
0 answers
11 views

Modeling non-negative time series with square root decay?

Q: How should I model a non-negative time series $y_t$ which exhibits square-root decay? More specifically, a time series $y_t$ whose square-root differences $\sqrt{y_t}-\sqrt{y_{t-1}}$ are linear and ...
lowndrul's user avatar
  • 2,147
0 votes
0 answers
26 views

Forecasting Square Waves

I am involved in a social experiment with other college students. The experiment involves simulating current price of the market at which a given asset can be bought or sold for immediate delivery. We,...
NOT-A-CS-GUY's user avatar
0 votes
0 answers
19 views

Different results when fitting ARIMA model for levels vs ARMA model for first differences in R

In the following code I show that I get different forecasts when fitting an ARIMA(2,1,0) for cumulative sums of a generated AR(2) model vs. fitting an ARMA(2,0) for the AR(2) itself. Can anyone point ...
Mr Frog's user avatar
  • 339
3 votes
1 answer
44 views

How to determine (the lag order of) MA from these plots?

I am using time series to analyze the price of a commodity. Characterizing is the fact that the price of the good is determined per hour, one day prior to the day of delivery. For now, I have ...
Zillah's user avatar
  • 31
3 votes
1 answer
31 views

Why do we make a time series stationary if the ARIMA, AR and other models are clearly working with the dependence of lags?

When we run a AR model, we are using a linear combination of its lags to predict the current value. So this means that the lags are related to each other (at least t-1, t-2, ..., t-n are related to t0)...
Andrew Joplh's user avatar
0 votes
0 answers
15 views

Interpretation of ARIMAX residuals

Plotted a seasonal ARIMAX model where I took one difference and one seasonal difference, am unsure of how do I interpret the residuals output below. The resultant model is ARIMA(2,1,2)(2,1,0)[12] ...
scoosch's user avatar
  • 11
1 vote
0 answers
14 views

ARIMA with multiple series [closed]

i would like to conduct forecast time series ARIMA model about the disease outbreak on eviews using temp and rainfall as exogenous variable. I am able to forecast all of them alone but not with the ...
Hijab's user avatar
  • 11
1 vote
1 answer
41 views

Time series model specification

I want to run a regression analysis in R to explain the variation of my DV g_law_tot which is the growth rate of total budget from t-1 to t. I have yearly data from 1994 to 2023. I have some political,...
user14514023's user avatar
2 votes
1 answer
28 views

Confusing SARIMAX Parameter Estimates from Simulated ARMA Data

I've been working on simulating ARMA (Autoregressive Moving Average) time series data in Python and fitting ARIMA models using the SARIMAX class from the ...
Quant In Spe's user avatar
0 votes
1 answer
36 views

Estimate of the intercept is off in a simulated AR(1) model

I've been working with a SARIMAX model for forecasting and found myself struggling to accurately interpret its long-term forecasts. To better understand the underlying mechanics and perhaps pinpoint ...
Quant In Spe's user avatar
0 votes
0 answers
6 views

Running ARIMA-SEATS with different weekdays

Is it possible to run the Census Bureau's ARIMA X-13 SEATS with, say Sunday-Thursday as working days, or Sunday-Friday, for that matter? I'm running in R with the 'seasonal' package, if that matters.
BlackNinja's user avatar
0 votes
0 answers
67 views

ACF and PACF plots to estimate SARIMA orders

I have some data (sales of a particular item at a particular grocery store) which exhibits both trend and seasonality. I fit these trend and seasonality components by doing a linear regression of the ...
Steven Gubkin's user avatar
2 votes
1 answer
207 views

Modeling timeseries with strong seasonality

I have monthly national home price index data, from CoreLogic. Data is seasonally adjusted. But still has strong seasonal effect. Here is the plot for monthly changes. ...
deb's user avatar
  • 265
1 vote
0 answers
27 views

Fit ARMA(p, q) model in the Python statsmodels library using maximum likelihood [closed]

I am trying to fit a ARMA(p,q) model using the exact methods where the exact maximum likelihood or conditional sum of squares likelihood is maximized. This was available in the statsmodels library in ...
SPaul's user avatar
  • 11
2 votes
2 answers
105 views

Incorporating ARIMA errors in a linear regression model

I am working with economic data and trying to create a linear regression model for forecasting purposes. The dependent variable data is in terms of percentage change and I've differenced the ...
Amy K's user avatar
  • 151
2 votes
1 answer
156 views

Regarding explosive AR processes and stationarity

I often see this: If we have an $\text{AR}(1)$ process,$x_t=\phi x_{t-1}+w_t, $ $x_t$ is: stationary if $|\phi|<1$ an unit root (nonstationary) if $|\phi|=1$ explosive (and nonstationary) if $|\phi|...
da7666's user avatar
  • 91
3 votes
1 answer
41 views

Forecasting excess mortality with ARIMA model

I am using the forecast package by Prof Hyndman, and have had success fitting ARIMA models to excess mortality (from the COVID-19 pandemic) data. I am currently trying to produce plots for cumulative ...
Jina A.'s user avatar
  • 31
0 votes
0 answers
30 views

Checking if RW() = ARIMA(0,1,0) with drift

I am trying to confirm the following statement that in R fable package: ...
user1700890's user avatar
0 votes
0 answers
41 views

How to choose the order of differencing?

I have a time series that looks like this I was asked to display the autocorrelation function and perform ADF test and based on that suggest a d for further analysis. I get plots like this and can ...
moon's user avatar
  • 1
0 votes
2 answers
35 views

Approach to Handling Stationarity in Multi-dimensional Time Series Forecasting with AutoARIMA

I am working on a time series forecasting project for a meal delivery service that operates in multiple cities. The company has several fulfillment centers across these cities for dispatching meal ...
user172500's user avatar
0 votes
1 answer
39 views

VARMAX does not improve over ARIMA

i'm trying to forecast inflation using the macroeconomic variables i understand to be determinants of inflation (e.g. inflation expectations, exchange rates e.t.c) however, what ive noticed is that ...
themanfromnowhere's user avatar
2 votes
2 answers
187 views

Modelling Time to Events

I am trying to see if there is a class of statistical regression models which can specifically be used to model the "time to event" (e.g. time at which a certain threshold is expected to be ...
Uk rain troll's user avatar
0 votes
0 answers
24 views

Does this state space model make sense?

I'm working on a problem, Consider that a times series $\{y_t\}$ is generated from an $\text{ARIMA}(1,1,1)$ model, so that $$y_t-y_{t-1}=\alpha(y_{t-1}-y_{t-2})+\epsilon_t+\gamma\epsilon_{t-1},$$ ...
mjc's user avatar
  • 589
1 vote
1 answer
48 views

What modeling approach should i use AR, MA, ARMA?

those are my ACF and PACF plots for my time series after two differentiating. I watched a couple of tutorials but I cannot figure out what method I am supposed to use. Also, an interpretation of the ...
antekkalafior's user avatar
1 vote
0 answers
25 views

Does cointegration test of exogenous variable with Y variable make sense when doing ARIMAX/SARIMAX?

The cointegration test between two time series variable is generally relevant from my understanding when you are performing a regression model. In terms of ARIMA model the approach is straightforward ...
Sayooj Balakrishnan's user avatar
1 vote
1 answer
40 views

auto.arima results in R has no intercept

After fitting an ARIMA model with a covariate using the auto.arima function in R, I get the following results What could be the reason as to why my results do not ...
Wagathu's user avatar
  • 189
2 votes
1 answer
40 views

What is the natural progression from discrete AR models into continuous time?

Lets say we want to predict a single target variable and we have 10 regressors/features. Assume we would like to predict 30 days ahead (daily predictions up to 30 days ahead) and our data is a daily ...
MilTom's user avatar
  • 369
4 votes
1 answer
203 views

Different result between ARIMA and auto.arima

I have conducted an analysis on a time series dataset, and the issue is that the 'manual' ARIMA (SARIMA) performed in Gretl gives me a model (3,0,1)(1,1,1) with all *** and AIC=1595.332. However, when ...
Leonard Banković's user avatar
0 votes
0 answers
49 views

Why does there seem to be a drift in the Arima simulation of a time series with seasonality?

I'm trying to make sense of the basics of time series, and I ran into a block of code by Rob Hyndman. ...
JAP's user avatar
  • 101
1 vote
0 answers
111 views

How to remove seasonality from time series?

I want to model time series in Python for air quality prediction. My dataset has two columns: date_time and aqi, and contains hourly measurements of AQI. Data is seasonal but not perfectly seasonal ...
Pro1's user avatar
  • 11
1 vote
1 answer
109 views

How do I write the equation of an ARIMA (1,1,2)?

I obtained the following output from the function auto.arima(): Is this the correct way to write the equation? Or should it be like this?
Helen's user avatar
  • 11

1
2 3 4 5
59