| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Economics and Finance | 65 | 61 | 122 | 23 |
The foci of the journal are Econometrics, Statistics, Series (mathematics), Autoregressive model and Volatility (finance). It addresses concerns in Econometrics which are intertwined with other disciplines, such as Autoregressive integrated moving average, Time series and Bayesian probability. The study on Statistics presented is investigated in conjunction with research in Forecast error.
The Series (mathematics) study featured in Journal of Forecasting draws connections with the study of Applied mathematics. Volatility (finance) studies tackled cover an aspect of the field of Financial economics.
The journal articles are organized to address concerns in the fields of Econometrics, Statistics, Series (mathematics), Consensus forecast and Financial economics. The most cited publications hold forums on Econometrics that merge themes from other disciplines such as Artificial neural network and Autoregressive integrated moving average, Time series. The most cited papers address concerns in Statistics which are intertwined with other disciplines, such as Variance (accounting) and Value at risk.
The journal covers a variety of subjects, including Econometrics, Volatility (finance), Predictability, Autoregressive model and Realized variance. The Econometrics study presented in Journal of Forecasting encompasses related topics like Robustness (economics) and also examines its connection to subjects such as Jump. Autoregressive conditional heteroskedasticity, Leverage effect and Futures market studies in the realm of Volatility (finance) interact with fields like Natural gas.
Journal of Forecasting facilitates discussions on Autoregressive model that incorporate concepts from other fields like Bayesian vector autoregression, Bayesian probability and Time series. While work presented in Journal of Forecasting provided substantial information on Realized variance, it also covered topics in Implied volatility, Monetary economics, Applied mathematics and Stock market. While Index (economics) is the focus of it, it also provided insights into the studies of Order (exchange) and Series (mathematics).
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Forecasting (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Forecasting (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 4.13% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.86% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.48% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.52% of all publications and 74.14% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
One significant missing section from this article is how the forecasting techniques discussed are applicable in various industries, specifically accounting. Applying forecasting models in accounting is not brought up in this document and could certainly add depth based on Google Search Quality Guidelines. Forecasting is integral to the field of accounting as accountants often rely on statistical models to predict future economic trends and outcomes. Using the insights gained from forecasting models, businesses can establish effective financial strategies and risk management practices. In particular, accountants utilize forecasting to predict future revenue and expenses, aiding organizations in budget planning. Moreover, forecasts can play a vital role in investment decisions and in identifying potential growth opportunities or risks. Econometrics, a key topic in the Journal of Forecasting, is especially relevant in accounting for its application in financial forecasting. For instance, Autoregressive Integrated Moving Average (ARIMA) models, commonly used in econometric analyses, are invaluable tools for predicting future financial variables such as sales and stock prices. Similarly, the use of time series analysis aids in modeling and forecasting variables that evolve over a period of time, such as revenues and costs. If you are an aspiring accountant, and you'd like to incorporate understanding of these advanced forecasting techniques into your professional toolkit, formal education can be a good starting point. Becoming a Certified Public Accountant (CPA) requires a strong foundation in various areas of accounting and related disciplines, such as econometrics. There are several reputable institutions offering relevant programs, notably in the state of Wyoming. Learn more about how to be a CPA in Wyoming. Having a section that connects forecasting to real-world applications not only provides readers context for the relevance of the article’s subject, but also helps improve the article’s quality by demonstrating its practical use, which follows Google's Search Quality Guidelines.
David Gabauer
(2020)Unknown
(2022)Bangzhu Zhu;Bangzhu Zhu;Shunxin Ye;Ping Wang;Julien Chevallier
(2021)Chao Liang;Yu Wei;Yaojie Zhang
(2020)Chao Liang;Feng Ma;Lu Wang;Qing Zeng
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