Questions tagged [forecasting]
Prediction of the future events. It is a special case of [prediction], in the context of [time-series].
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Can I use VAR model on I(1) series with cointegration?
I have four I(1) series, and the Johansen test(ca.jo()) shows there is one cointegration. My purpose is to forecast, so I want to compare the forecasting results of VAR and VECM model. Is this ...
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16 views
Simulating AR/MA Process and forecasting it [on hold]
I'm trying to simulate an AR and a MA process separately.
I found the ACF and PACF as well.
If now I want to forecast for one time period ahead, can I do that with a simulated time series in R, if ...
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12 views
Multilevel modeling: many groups, mostly one sample each
I have a modeling problem in which customers can have multiple accounts on a website. Roughly speaking, 50% of customers have one account, 25% have two accounts, 12.5% have three accounts, etc. There ...
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11 views
How to build forecast model [on hold]
I have some data about budget overrun and fee erosion. I have determined that greater the budget overrun, greater the fee erosion. Conversly, lesser the budget overrun, lesser the fee erosion.
I ...
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1answer
13 views
Upwardly biased forecast results due to period of high demand: how to deal with this?
I'm currently working on a call-center forecasting project with some data limitations. Currently it is still a learning-project, and I started with simple OLS regressions.
For the months 2016-12 to ...
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15 views
Different set of predictors significant for different sample sizes - how to interpret results?
So I am trying a GARCH framework with external regressor(s) to predict returns. The external regressor, $y$, intuitively has useful lags that could predict the response.
I'm slowly accumulating data ...
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14 views
Converting log transformed and differenced time series back into original in R
I have built a Garch model in R based on taking a log transformation and a one order difference on the original time series. I would like to know how develop a forecast based on the Garch model for ...
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1answer
9 views
How to calculate mean directional accuracy in R [on hold]
I have been searching for a method to calculate the mean directional accuracy in R. Basically I have a few forecasting arima models, and I would like to choose the best model. Besides looking at the ...
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2answers
223 views
How to predict the next number in a series while having additional series of data that might affect it?
Let's say we want to predict the price of Big Mac for the year 2020. We have 2 indexes that we think might make an influence to Big Mac price determination.
...
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18 views
How to add the effect of structual change points (level shift, local time trends, changes in seasonal pulses ) in ARIMA IN PYTHON?
I am working on a time series forecasting problem which is described in details here. As I came to know that I was not considering structural changes and seasonal dummies and was building a simple ...
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16 views
Time series forecasting using Neural Network in matlab [on hold]
Please help me to create neural network to forecast inflation in Matlab for my research.
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17 views
Automating data preparation and model fit steps for multiple products
My question is in continuation to the these questions:
Question 1
Question 2
Question 3
Question 4
I am also attempting to automate the forecasting of financial parameters of multiple products in the ...
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7 views
How to do out of sample forecast by SVM in r? [on hold]
I am doing uni variate forecasting by using SVM in r. I did my in sample forecast precisely but when i do forecast for some next time period it gives the same values. here are codes.
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1answer
63 views
Model for forecasting daily page views of a web page in R
I have to forecast daily page views of a web portal. We have the daily page views of the data for the last 2 years. We have to forecast for next 90 days. I am using a multi-seasonal (with season ...
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1answer
127 views
Time series forecast - ARIMA/ARIMAX with daily data [closed]
I am working on a project to analyse and forecast time series for sales and revenue of a client. There are various models that i want to test for accuracy purposes - namely Holt Linear Method, Holt ...
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1answer
12 views
What does it say about your underlying system when the granular level is not predictable, but aggregations are?
This might be too "discussion-y" rather than black-or-white-answer for here, but thought I'd try. If there's a better direction someone can point me, that's fine.
Example: One McDonald's store daily ...
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22 views
Intra-Day Time Series Forecasting w/ non-continuous data
I have 8 sample frames taken at the end of each quarter starting in 2017Q2 and ending in 2019Q1 for a stock ticker. Each sample frame consists of 2 trading days worth of stock data (open, high, low, ...
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1answer
10 views
Contemporary term for setting of forecasting constants
Two time-series forecast principles are used: a seasonal moving average and a seasonal single exponential smoothing forecast.
To attain quality results, the associated constants (the season size, the ...
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1answer
35 views
Forecasting Methodology
Suppose I have only 1 variable (data on export, monthly, non-seasonally adjusted) from Jan 1960 till Mar 2019. My task is to obtain forecasts of this series for the coming year (i.e. Apr 2019 - Mar ...
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14 views
How do I specify a moving average model in R-INLA?
I have a dynamic regression model specified as follows:
$f_{c,t+1} \sim N(\eta_{c,t+1} + \phi\epsilon_t,\sigma^2_{f})$
$\epsilon_t=f_{c,t}-\eta_{c,t}$
$\eta_{c,t}=\beta_0+\beta_1x_{1,c,t}$
How ...
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2answers
40 views
Calculating probability of a female US president [closed]
What solid evidence could we use to assess the chances of a woman being elected in the next US presidential election 2020?
The last 45 US presidents were male. That's a hit rate of 100%. Intuitively ...
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46 views
Formulae for density function replacing probabilistic function
I am working with markov chains and in specific I am working with (Langrock, Roland MacDonald, Iain L. Zucchini, W (2016)). They define a forecast distribution given as:
$$ Pr(X_{T+h}=x|X^{(T)}=x^{(...
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11 views
Decide inventory to carry based on forecast model to max. profit
This is statistical modeling / forecasting optimization question. I have a forecast model which predicts units value for a year. Now if I carry more inventory than prediction, I lose all the extra ...
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1answer
22 views
Calculating forecast intervals for user adjusted forecasts?
My demand forecasting solution generates point forecasts and forecast intervals for millions of time series (# of products × # stores for a large retailer) using statistical models.
Business users (...
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1answer
28 views
Forecasting a time series without trend and seasonality?
Can I use ARIMA methods to forecast a time series without any trend or seasonality?
If no, are there any other methods that I can use to do such forecasting?
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33 views
Random Forest for time series - how to deal with mixed frequencies?
I want to use random forest to forecast a quarterly sampled variable $Y_t$ using a large set of monthly sampled regressors $X_t$. The point is that I have very few observations (I'm working with ...
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1answer
84 views
ARMAX for Bitcoin prediction via sentiment
I am looking for correlation between social sentiment of BTC and the financial value of BTC. My approach is to use a time-series model to predict the bitcoin value at t+1 based on multiple input ...
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21 views
Prediction of financial time series
I have several questions. I will split the text up in one high-level description of the goal of my exercise, a detailed description of my potential solution and finally my actual questions. Please ...
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14 views
Long fitting times for SARIMAX. Fine tuning required for hourly data with weekly seasinality
I have developed a SARIMAX model for hourly data of two months aprox 1700 records and predecting a week data around 170 records.
As the seasonality observed is for a week so m=168.
Initially used GRID ...
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32 views
Using temperature as feature in Neural Network
I'm currently putting together a Neural Network for doing Sales Forecasting for hundreds of products. The domain experts know that the sales spike when the temperature drops and so I started to use ...
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0answers
22 views
What does this mean? Can you explain it to me in laymans term? [duplicate]
How to interpret this? What does the ARIMA(0,0,0)(0,1,0)[12] means in laymans term?
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9 views
Distance from expected error versus distance from expectation
Model 1: percentage from expectation
We have a time series forecasting model that makes predictions every 15 minutes. As a first stab, we classified all those points that were 50% larger than our ...
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40 views
The Efficient Market Hypothesis and forecastability?
According to Wikipedia:
The efficient-market hypothesis (EMH) is a theory in financial economics that states that asset prices fully reflect all available information. A direct implication is that ...
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14 views
Forecasting many points (horizson forecast) VS rolling one by one
I used a Feed Forward (or Convolution or RNN) for forecasting and I want to forecast many steps.
I have to options:
To forecast many points simultaneously.
Each time to forecast just one point and ...
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1answer
33 views
ARIMA model forecast does't seem right
I am doing a SARIMA forecasting for my monthly data in STATA, and below is my forecast. I use a SARIMA (1,1,1)(0,1,1,12) model, but the forecast seem to only capture the previous month pattern, which ...
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1answer
24 views
Manually calculate SARIMAX forecast
I'm trying to manually replicate the forecast that I obtained using statsmodels.api sarimax (python). Its actually just an AR(1) model with one exogenous variable, in the form of SARIMAX(1,0,0)(0,0,0)...
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1answer
24 views
Is statistical significance of a regressor important in forecasting different scenarios?
I have a good regression with ARMA errors (with exogenous variables), and it gives me reasonable forecasts. But now I need to construct different scenarios to forecast. My question is: Should I worry ...
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1answer
180 views
Can I use averages to improve the forecast of a multiple regression?
I have a cross-sectional multiple regression that I have estimated and now I would like to apply it to make a simple forecast of the dependent variable.
Take the data generating process
$$y_i =\...
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22 views
Time shifting in time series forecasting
I am working on an ANN model for univariate time series forecasting. The step size is 1, so I try to forecast value of t+1, using value of t. Unfortunately, my forecasts have time shift problem. The ...
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26 views
Method of analyze returns for nonstationary time-series
guys.
Let's have 2 types of time series: TrendStationary (or TS-stationary) and DifferenceStationary (or DS-stationary) time series.
So, what's the best strategy of analyzing and forecasting time ...
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7 views
Interpreting accuracy values in ARIMA
How to interpet each measuring accuracy and how will i know if its accurate measure in the model
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1answer
62 views
Some questions about quarterly and monthly timeseries
I need some help in my forecasting analysis.
In my company, for the most part, if we take a look at monthly sales time series we will find a lot of noise, a large standard deviation and variance, ...
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14 views
Time-series forecasting of weakly correlated, univariate series
Given an event that happens with a probability of $\lambda_1$, and another event happens with a probability of $\lambda_2$, what is the probability that they both occur?
I have a dataset of ...
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25 views
non-stationary time series for VAR model forecasting
I'm working with a VAR model to do forecast involving two non-stationary time series (quarterly frequency). The literature indicates to verify if there is cointegration and, otherwise, to use the ...
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1answer
42 views
How does facebook prophet handels missing data?
Prophet's paper (forecasting at scale by SJ Taylor - 2017) says the following on missing data:
"Unlike ARIMA models, the measurments do not need to be regularly spaced, and we do not need to ...
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2answers
58 views
Does SARIMA(3,1,18)(8,1,3) exist?
When I entered the above model in minitab to forecast, it said, 18 is not acceptable, and that value should be less than or equal to 5. I wonder whether it's a limitation of minitab, or this model is ...
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1answer
82 views
Interpretation of spectral entropy of a timeseries
The tsfeatures package for R has an entropy() function. The vignette for the package describes it as:
The spectral entropy is ...
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1answer
45 views
Forecasting in R - really short time-series
Complete noob on forecasting and time-series here.
I'm doing my PhD and my group did previous research on the prevalence of the disease we're studying. We only have prevalence data of 5 years and ...
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11 views
Forecasting data for 5 years [duplicate]
Following is a part of my data-set. What are the tests I can use for it? Can I use any forecasting method? If yes, what are those methods?
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1answer
27 views
I need help with choosing a mid-long term forecastic method for this demand
I am trying to forecast the demand of a product for the next 36 months, based on its sales history. The demand plot is shown below.
I honestly don't know what to do with it. I tried linear and non-...
