Example of Applied Mathematical Finance format
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Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format
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Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format Example of Applied Mathematical Finance format
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This content is only for preview purposes. The original open access content can be found here.
open access Open Access

Applied Mathematical Finance — Template for authors

Publisher: Taylor and Francis
Categories Rank Trend in last 3 yrs
Finance #173 of 288 down down by 79 ranks
Applied Mathematics #352 of 548 down down by 104 ranks
journal-quality-icon Journal quality:
Medium
calendar-icon Last 4 years overview: 73 Published Papers | 97 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 15/07/2020
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Related Journals

open access Open Access
recommended Recommended

Wiley

Quality:  
High
CiteRatio: 4.2
SJR: 1.98
SNIP: 2.249
open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 4.5
SJR: 1.336
SNIP: 2.022
open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 2.8
SJR: 0.771
SNIP: 1.33
open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 1.4
SJR: 0.214
SNIP: 0.992

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

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

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.

1.3

63% from 2019

CiteRatio for Applied Mathematical Finance from 2016 - 2020
Year Value
2020 1.3
2019 0.8
2018 1.1
2017 1.4
2016 1.4
graph view Graph view
table view Table view

0.829

104% from 2019

SJR for Applied Mathematical Finance from 2016 - 2020
Year Value
2020 0.829
2019 0.406
2018 0.455
2017 0.615
2016 0.622
graph view Graph view
table view Table view

0.89

38% from 2019

SNIP for Applied Mathematical Finance from 2016 - 2020
Year Value
2020 0.89
2019 0.644
2018 0.735
2017 0.842
2016 0.905
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 63% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 104% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 38% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Applied Mathematical Finance

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Taylor and Francis

Applied Mathematical Finance

Approved by publishing and review experts on SciSpace, this template is built as per for Applied Mathematical Finance formatting guidelines as mentioned in Taylor and Francis author instructions. The current version was created on 15 Jul 2020 and has been used by 858 authors to write and format their manuscripts to this journal.

Finance

Applied Mathematics

Economics, Econometrics and Finance

i
Last updated on
15 Jul 2020
i
ISSN
1350-486X
i
Impact Factor
High - 1.068
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
Taylor and Francis Custom Citation
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Citation Type
Author Year
(Blonder et al., 1982)
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Bibliography Example
Blonder, G. E., Tinkham, M., and Klapwijk, T. M. 1982. Transition from metallic to tunneling regimes in super-conducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys Rev B. 25(7):4515–4532.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1080/13504869500000005
Pricing and hedging derivative securities in markets with uncertain volatilities
Marco Avellaneda1, A. Levy2, Antonio Paras1

Abstract:

We present a model for pricing and hedging derivative securities and option portfolios in an environment where the volatility is not known precisely, but is assumed instead to lie between two extreme values σminand σmax. These bounds could be inferred from extreme values of the implied volatilities of liquid options, or from ... We present a model for pricing and hedging derivative securities and option portfolios in an environment where the volatility is not known precisely, but is assumed instead to lie between two extreme values σminand σmax. These bounds could be inferred from extreme values of the implied volatilities of liquid options, or from high-low peaks in historical stock- or option-implied volatilities. They can be viewed as defining a confidence interval for future volatility values. We show that the extremal non-arbitrageable prices for the derivative asset which arise as the volatility paths vary in such a band can be described by a non-linear PDE, which we call the Black-Scholes-Barenblatt equation. In this equation, the ‘pricing’ volatility is selected dynamically from the two extreme values, σmin, σmax, according to the convexity of the value-function. A simple algorithm for solving the equation by finite-differencing or a trinomial tree is presented. We show that this model captures the importance of diversifi... read more read less

Topics:

Volatility smile (65%)65% related to the paper, Implied volatility (64%)64% related to the paper, Stochastic volatility (63%)63% related to the paper, Forward volatility (63%)63% related to the paper, Volatility swap (61%)61% related to the paper
View PDF
728 Citations
Journal Article DOI: 10.1080/135048602100056
Optimal execution with nonlinear impact functions and trading-enhanced risk
Robert Almgren1

Abstract:

Optimal trading strategies are determined for liquidation of a large single-asset portfolio to minimize a combination of volatility risk and market impact costs. The market impact cost per share is taken to be a power law function of the trading rate, with an arbitrary positive exponent. This includes, for example, the square... Optimal trading strategies are determined for liquidation of a large single-asset portfolio to minimize a combination of volatility risk and market impact costs. The market impact cost per share is taken to be a power law function of the trading rate, with an arbitrary positive exponent. This includes, for example, the square root law that has been proposed based on market microstructure theory. In analogy to the linear model, a ‘characteristic time’ for optimal trading is defined, which now depends on the initial portfolio size and decreases as execution proceeds. A model is also considered in which uncertainty of the realized price is increased by demanding rapid execution; it is shown that optimal trajectories are described by a ‘critical portfolio size’ above which this effect is dominant and below which it may be neglected. read more read less

Topics:

Trading strategy (61%)61% related to the paper, Algorithmic trading (61%)61% related to the paper, Market microstructure (61%)61% related to the paper, Pairs trade (61%)61% related to the paper, Market impact cost (58%)58% related to the paper
522 Citations
open accessOpen access Journal Article DOI: 10.1080/13504860500117503
Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality
Álvaro Cartea1, Marcelo G. Figueroa1

Abstract:

This paper presents a mean‐reverting jump diffusion model for the electricity spot price and derives the corresponding forward price in closed‐form. Based on historical spot data and forward data from England and Wales the model is calibrated and months, quarters, and seasons–ahead forward surfaces are presented. This paper presents a mean‐reverting jump diffusion model for the electricity spot price and derives the corresponding forward price in closed‐form. Based on historical spot data and forward data from England and Wales the model is calibrated and months, quarters, and seasons–ahead forward surfaces are presented. read more read less

Topics:

Forward price (69%)69% related to the paper, Jump diffusion (58%)58% related to the paper, Mean reversion (58%)58% related to the paper, Forward curve (55%)55% related to the paper
View PDF
401 Citations
Journal Article DOI: 10.1080/13504869500000007
Uncertain volatility and the risk-free synthesis of derivatives
Terry Lyons1

Abstract:

To price contingent claims in a multidimensional frictionless security market it is sufficient that the volatility of the security process is a known function of price and time. In this note we introduce optimal and risk-free strategies for intermediaries in such markets to meet their obligations when the volatility is unknow... To price contingent claims in a multidimensional frictionless security market it is sufficient that the volatility of the security process is a known function of price and time. In this note we introduce optimal and risk-free strategies for intermediaries in such markets to meet their obligations when the volatility is unknown, and is only assumed to lie in some convex region depending on the prices of the underlying securities and time. Our approach is underpinned by the theory of totally non-linear parabolic partial differential equations (Krylov and Safanov, 1979; Wang, 1992) and the non-stochastic approach to Ito's formation first introduced by Follmer (1981a,b). In these more general conditions of unknown volatility, the optimal risk-free trading strategy will, necessarily, produce an unpredictable surplus over the minimum assets required at any time to meet the liabilities. This surplus, which could be released to the intermediary or to the client, is not required to meet the contingent claim. One s... read more read less

Topics:

Volatility smile (63%)63% related to the paper, Stochastic volatility (63%)63% related to the paper, Implied volatility (62%)62% related to the paper, Volatility risk premium (60%)60% related to the paper, Volatility (finance) (56%)56% related to the paper
383 Citations
Journal Article DOI: 10.1080/13504860210132897
On modelling and pricing weather derivatives

Abstract:

The main objective of the work described is to find a pricing model for weather derivatives with payouts depending on temperature. Historical data are used to suggest a stochastic process that describes the evolution of the temperature. Since temperature is a non-tradable quantity, unique prices of contracts in an incomplete ... The main objective of the work described is to find a pricing model for weather derivatives with payouts depending on temperature. Historical data are used to suggest a stochastic process that describes the evolution of the temperature. Since temperature is a non-tradable quantity, unique prices of contracts in an incomplete market are obtained using the market price of risk. Numerical examples of prices of some contracts are presented, using an approximation formula as well as Monte Carlo simulations. read more read less

Topics:

Weather derivative (59%)59% related to the paper
View PDF
380 Citations
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Frequently asked questions

1. Can I write Applied Mathematical Finance in LaTeX?

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

2. Do you follow the Applied Mathematical Finance guidelines?

Yes, the template is compliant with the Applied Mathematical Finance 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 Applied Mathematical Finance?

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 Applied Mathematical Finance citation style.

4. Can I use the Applied Mathematical Finance 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 Applied Mathematical Finance.

5. Can I use a manuscript in Applied Mathematical Finance 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 Applied Mathematical Finance that you can download at the end.

6. How long does it usually take you to format my papers in Applied Mathematical Finance?

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

7. Where can I find the template for the Applied Mathematical Finance?

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 Applied Mathematical Finance'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 Applied Mathematical Finance'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. Applied Mathematical Finance an online tool or is there a desktop version?

SciSpace's Applied Mathematical Finance 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.

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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 Applied Mathematical Finance?”

11. What is the output that I would get after using Applied Mathematical Finance?

After writing your paper autoformatting in Applied Mathematical Finance, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Applied Mathematical Finance'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 Applied Mathematical Finance?

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 Applied Mathematical Finance. 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 Applied Mathematical Finance?

The 5 most common citation types in order of usage for Applied Mathematical Finance 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 Applied Mathematical Finance?

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16. Can I download Applied Mathematical Finance 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 Applied Mathematical Finance Endnote style according to Elsevier guidelines.

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