| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Economics and Finance | 287 | 17 | 19 | 8 |
The journal primarily focuses on research topics in Econometrics, Mathematical economics, Mathematical optimization, Portfolio and Applied mathematics. The journal holds forums on Econometrics that merges themes from other disciplines such as Financial economics, Asset (economics) and Credit risk. Topics in Mathematical economics explored in Mathematical Finance were investigated in conjunction with research in Martingale (probability theory), Arbitrage, Discrete time and continuous time, Black–Scholes model and Incomplete markets.
Martingale (probability theory) research presented is mostly focused on the subject of Local martingale. The work on Arbitrage addressed in it expands to the thematically related Fundamental theorem of asset pricing. Bellman equation, Stochastic control and Optimal stopping are all topics related to Mathematical optimization research discussed.
The journal explores issues in Portfolio which can be linked to other research areas like Microeconomics and Transaction cost. Stochastic volatility is a major topic of Volatility (finance) research presented in Mathematical Finance. The studies on Stochastic volatility discussed can also contribute to research in the domains of Implied volatility, Volatility swap and Volatility smile.
The journal articles primarily focus on research topics in Econometrics, Mathematical economics, Mathematical optimization, Valuation of options and Financial economics. The journal papers hold forums on Econometrics that merge themes from other disciplines such as Arbitrage and Credit risk. Issues in Mathematical economics were discussed in the journal articles, taking into consideration concepts from other disciplines like Martingale (probability theory), Incomplete markets, Valuation (finance) and Portfolio optimization.
Mathematical Finance investigates studies in Econometrics, Mathematical economics, Applied mathematics, Mathematical optimization and Volatility (finance). Issues in Econometrics were discussed, taking into consideration concepts from other disciplines like Value at risk, Derivative (finance), Financial market and Sharpe ratio, Portfolio. The journal facilitates discussions on Mathematical economics that incorporate concepts from other fields like Black–Scholes model, Mathematical finance, Binomial distribution and Duality (optimization).
While work presented in Mathematical Finance provided substantial information on Applied mathematics, it also covered topics in Markov process, Optimal stopping, Asymptotic expansion, Markov chain and Nonlinear system. Mathematical Finance covers research in Mathematical optimization, particularly Singular control, Stochastic control and Lagrange multiplier and how they are related with concepts in Group (mathematics). Volatility (finance) research presented in it encompasses a variety of subjects, including Market liquidity, Order (exchange), Microeconomics and Hedge (finance).
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 Mathematical Finance (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 Mathematical Finance (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, 1.92% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 49.02% were posted by at least one author from the top 10 institutions publishing in the journal. Another 17.65% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 9.80% of all publications and 23.53% 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.
If you find the world of Mathematical Finance exciting and want to explore career opportunities within this field, there are several pathways you could consider. One of these is becoming a Certified Public Accountant (CPA). Particularly in the state of Wisconsin, there are specific requirements and processes to follow in order to achieve this designation.
Once you've become a CPA, you can apply your Mathematical Finance knowledge to various job roles, such as running your own accounting business, working in government or corporate accounting, and even moving into finance consulting. The possibilities are vast.
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Paolo Barucca;Marco Bardoscia;Fabio Caccioli;Fabio Caccioli;Marco D'Errico
(2020)Kay Giesecke;Gustavo Schwenkler;Justin A. Sirignano
(2020)A. Max Reppen;Jean Charles Rochet;Jean Charles Rochet;Jean Charles Rochet;H. Mete Soner;H. Mete Soner
(2020)Paul Embrechts;Tiantian Mao;Qiuqi Wang;Ruodu Wang
(2021)Dilip B. Madan;Wim Schoutens
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