Example of Journal of Forecasting format
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Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format
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Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format Example of Journal of Forecasting format
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open access Open Access

Journal of Forecasting — Template for authors

Publisher: Wiley
Categories Rank Trend in last 3 yrs
Statistics, Probability and Uncertainty #39 of 152 up up by 25 ranks
Strategy and Management #167 of 440 up up by 30 ranks
Modeling and Simulation #122 of 290 up up by 41 ranks
Management Science and Operations Research #73 of 166 up up by 15 ranks
Computer Science Applications #305 of 693 up up by 57 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 237 Published Papers | 712 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 27/06/2020
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Related Journals

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Taylor and Francis

Quality:  
High
CiteRatio: 8.2
SJR: 1.331
SNIP: 1.866
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Elsevier

Quality:  
High
CiteRatio: 4.9
SJR: 1.02
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Taylor and Francis

Quality:  
High
CiteRatio: 5.9
SJR: 0.972
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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

1.57

92% from 2018

Impact factor for Journal of Forecasting from 2016 - 2019
Year Value
2019 1.57
2018 0.816
2017 0.934
2016 0.747
graph view Graph view
table view Table view

3.0

36% from 2019

CiteRatio for Journal of Forecasting from 2016 - 2020
Year Value
2020 3.0
2019 2.2
2018 1.5
2017 1.4
2016 1.8
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 92% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 36% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.543

17% from 2019

SJR for Journal of Forecasting from 2016 - 2020
Year Value
2020 0.543
2019 0.654
2018 0.407
2017 0.792
2016 0.633
graph view Graph view
table view Table view

1.112

5% from 2019

SNIP for Journal of Forecasting from 2016 - 2020
Year Value
2020 1.112
2019 1.174
2018 0.699
2017 0.849
2016 0.924
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 17% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 5% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Forecasting

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Wiley

Journal of Forecasting

The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic...... Read More

Statistics, Probability and Uncertainty

Strategy and Management

Modelling and Simulation

Management Science and Operations Research

Computer Science Applications

Decision Sciences

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Last updated on
27 Jun 2020
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ISSN
0277-6693
i
Impact Factor
High - 1.482
i
Open Access
Yes
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Sherpa RoMEO Archiving Policy
Yellow faq
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
apa
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Citation Type
Author Year
(Blonder et al., 1982)
i
Bibliography Example
Blonder, G. E., Tinkham, M., and Klapwijk, T. M. (1982). Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and super- current conversion. Phys. Rev. B, 25(7):4515–4532.

Top papers written in this journal

Journal Article DOI: 10.1002/FOR.3980010202
The accuracy of extrapolation (time series) methods: Results of a forecasting competition
01 Apr 1982 - Journal of Forecasting

Abstract:

ln the last few decades matiy methods have become available for forecasting. As always, when alternatives exist, choices need to be made so that an appropriate forecasting method can be selected and used for the specific situation being considered. This paper reports the results of a forecasting competition that provides info... ln the last few decades matiy methods have become available for forecasting. As always, when alternatives exist, choices need to be made so that an appropriate forecasting method can be selected and used for the specific situation being considered. This paper reports the results of a forecasting competition that provides information to facilitate such choice. Seven experts in each of the 24 methods forecasted up to 1001 series for six up to eighteen time horizons. The results of the competition are presented in this paper whose purpose is to provide empirical evidence about differences found to exist among the various extrapolative (time series) methods used in the competition. read more read less

Topics:

Probabilistic forecasting (62%)62% related to the paper, Empirical research (52%)52% related to the paper, Competition (economics) (52%)52% related to the paper
1,403 Citations
Journal Article DOI: 10.1002/FOR.3980040103
Exponential smoothing: The state of the art
Everette S. Gardner1
01 Jan 1985 - Journal of Forecasting

Abstract:

This paper is a critical review of exponential smoothing since the original work by Brown and Holt in the 1950s. Exponential smoothing is based on a pragmatic approach to forecasting which is shared in this review. The aim is to develop state-of-the-art guidelines for application of the exponential smoothing methodology. The ... This paper is a critical review of exponential smoothing since the original work by Brown and Holt in the 1950s. Exponential smoothing is based on a pragmatic approach to forecasting which is shared in this review. The aim is to develop state-of-the-art guidelines for application of the exponential smoothing methodology. The first part of the paper discusses the class of relatively simple models which rely on the Holt-Winters procedure for seasonal adjustment of the data. Next, we review general exponential smoothing (GES), which uses Fourier functions of time to model seasonality. The research is reviewed according to the following questions. What are the useful properties of these models? What parameters should be used? How should the models be initialized? After the review of model-building, we turn to problems in the maintenance of forecasting systems based on exponential smoothing. Topics in the maintenance area include the use of quality control models to detect bias in the forecast errors, adaptive parameters to improve the response to structural changes in the time series, and two-stage forecasting, whereby we use a model of the errors or some other model of the data to improve our initial forecasts. Some of the major conclusions: the parameter ranges and starting values typically used in practice are arbitrary and may detract from accuracy. The empirical evidence favours Holt's model for trends over that of Brown. A linear trend should be damped at long horizons. The empirical evidence favours the Holt-Winters approach to seasonal data over GES. It is difficult to justify GES in standard form–the equivalent ARIMA model is simpler and more efficient. The cumulative sum of the errors appears to be the most practical forecast monitoring device. There is no evidence that adaptive parameters improve forecast accuracy. In fact, the reverse may be true. read more read less

Topics:

Exponential smoothing (64%)64% related to the paper, Smoothing (60%)60% related to the paper, Seasonal adjustment (53%)53% related to the paper, Autoregressive integrated moving average (51%)51% related to the paper
1,235 Citations
Journal Article DOI: 10.1002/FOR.928
Combination forecasts of output growth in a seven-country data set
James H. Stock1, Mark W. Watson1
01 Sep 2004 - Journal of Forecasting

Abstract:

This paper uses forecast combination methods to forecast output growth in a seven-country quarterly economic data set covering 1959‐1999, with up to 73 predictors per country. Although the forecasts based on individual predictors are unstable over time and across countries, and on average perform worse than an autoregressive ... This paper uses forecast combination methods to forecast output growth in a seven-country quarterly economic data set covering 1959‐1999, with up to 73 predictors per country. Although the forecasts based on individual predictors are unstable over time and across countries, and on average perform worse than an autoregressive benchmark, the combination forecasts often improve upon autoregressive forecasts. Despite the unstable performance of the constituent forecasts, the most successful combination forecasts, like the mean, are the least sensitive to the recent performance of the individual forecasts. While consistent with other evidence on the success of simple combination forecasts, this finding is difficult to explain using the theory of combination forecasting in a stationary environment. Copyright © 2004 John Wiley & Sons, Ltd. read more read less

Topics:

Consensus forecast (68%)68% related to the paper, Forecast verification (56%)56% related to the paper, Forecast skill (53%)53% related to the paper
View PDF
1,100 Citations
Journal Article DOI: 10.1002/FOR.3980030207
Improved methods of combining forecasts
Clive W. J. Granger1, Ramu Ramanathan1
01 Apr 1984 - Journal of Forecasting

Abstract:

It is well known that a linear combination of forecasts can outperform individual forecasts. The common practice, however, is to obtain a weighted average of forecasts, with the weights adding up to unity. This paper considers three alternative approaches to obtaining linear combinations. It is shown that the best method is t... It is well known that a linear combination of forecasts can outperform individual forecasts. The common practice, however, is to obtain a weighted average of forecasts, with the weights adding up to unity. This paper considers three alternative approaches to obtaining linear combinations. It is shown that the best method is to add a constant term and not to constrain the weights to add to unity. These methods are tested with data on forecasts of quarterly hog prices, both within and out of sample. It is demonstrated that the optimum method proposed here is superior to the common practice of letting the weights add up to one. read more read less

Topics:

Consensus forecast (58%)58% related to the paper, Linear combination (54%)54% related to the paper
1,088 Citations
Journal Article DOI: 10.1002/FOR.3980070102
Outliers, Level Shifts, and Variance Changes in Time Series
Ruey S. Tsay1
01 Jan 1988 - Journal of Forecasting

Abstract:

Outliers, level shifts, and variance changes are commonplace in applied time series analysis. However, their existence is often ignored and their impact is overlooked, for the lack of simple and useful methods to detect and handle those extraordinary events. The problem of detecting outliers, level shifts, and variance change... Outliers, level shifts, and variance changes are commonplace in applied time series analysis. However, their existence is often ignored and their impact is overlooked, for the lack of simple and useful methods to detect and handle those extraordinary events. The problem of detecting outliers, level shifts, and variance changes in a univariate time series is considered. The methods employed are extremely simple yet useful. Only the least squares techniques and residual variance ratios are used. The effectiveness of these simple methods is demonstrated by analysing three real data sets. read more read less

Topics:

Variance (accounting) (52%)52% related to the paper, Univariate (51%)51% related to the paper
680 Citations
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Journal of Forecasting format uses apa citation style.

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Frequently asked questions

1. Can I write Journal of Forecasting in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Journal of Forecasting guidelines and auto format it.

2. Do you follow the Journal of Forecasting guidelines?

Yes, the template is compliant with the Journal of Forecasting guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Journal of Forecasting?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Forecasting citation style.

4. Can I use the Journal of Forecasting templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Journal of Forecasting.

5. Can I use a manuscript in Journal of Forecasting that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Journal of Forecasting that you can download at the end.

6. How long does it usually take you to format my papers in Journal of Forecasting?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Journal of Forecasting.

7. Where can I find the template for the Journal of Forecasting?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Journal of Forecasting's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Journal of Forecasting's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Journal of Forecasting an online tool or is there a desktop version?

SciSpace's Journal of Forecasting is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Journal of Forecasting?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Journal of Forecasting?”

11. What is the output that I would get after using Journal of Forecasting?

After writing your paper autoformatting in Journal of Forecasting, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Journal of Forecasting's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Forecasting?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Forecasting. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Forecasting?

The 5 most common citation types in order of usage for Journal of Forecasting are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Journal of Forecasting?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Journal of Forecasting's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Journal of Forecasting in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Forecasting Endnote style according to Elsevier guidelines.

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