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Algorithmic Finance - IOS Press | 2024 Impact Factor:0.2 | Cite Score:0.5 | Q4

Algorithmic Finance Journal With Cite Score

Cite Score and Journal Rank of Algorithmic Finance

  • About: Algorithmic Finance is a peer-reviewed journal that focuses on the intersection of finance and algorithmic methods. The journal explores how computational techniques, algorithms, and quantitative models are applied to financial markets, trading strategies, risk management, and investment analysis.
  • Objective: The primary objective of the Algorithmic Finance journal is to publish research that advances the use of algorithms and computational methods in finance. The journal aims to provide a platform for the dissemination of innovative approaches, theoretical developments, and practical applications related to algorithmic trading, financial modeling, quantitative finance, and related areas. It seeks to address both the theoretical underpinnings and practical implementations of algorithmic methods in the financial industry.
  • Interdisciplinary Approach: The journal adopts an interdisciplinary approach by integrating research from finance, computer science, mathematics, and statistics. This approach encourages the exploration of new methodologies that combine insights from these diverse fields to tackle complex financial problems. By fostering collaboration between experts in finance and computational sciences, the journal aims to advance the development and application of sophisticated algorithms and models in the financial domain.
  • Impact and Significance: The Algorithmic Finance journal is significant for its contribution to the advancement of quantitative finance and algorithmic trading. The journals publications provide valuable insights into the development and application of computational techniques in financial markets, helping to improve trading strategies, risk management, and financial decision-making. By featuring cutting-edge research, the journal supports the growth of knowledge and practice in the field of algorithmic finance.

  • Editor-in-Chief:  Philip Maymin

  • Scope: Algorithmic Finance is a peer-reviewed journal that focuses on the application of algorithmic techniques and methods in the field of finance. The journal provides a platform for research on quantitative models, computational methods, and algorithmic strategies that address financial problems and challenges.
    1. Algorithmic Trading: Research on the development and application of algorithms for trading financial instruments, including high-frequency trading, market making, and execution strategies.
  • Quantitative Finance Models: Studies on quantitative models used in finance, such as pricing models for derivatives, risk management models, and asset pricing models.
  • Computational Finance: Articles on the use of computational techniques and simulations to solve complex financial problems and analyze financial data.
  • Machine Learning in Finance: Research on the application of machine learning algorithms and techniques for financial forecasting, pattern recognition, and decision-making.
  • Financial Engineering: Studies on the design and implementation of innovative financial products and strategies using algorithmic and computational approaches.
  • Portfolio Management: Research on algorithmic approaches to portfolio optimization, asset allocation, and risk management.
  • Algorithmic Risk Management: Articles on the use of algorithms for assessing and managing financial risks, including credit risk, market risk, and operational risk.
  • High-Frequency Data Analysis: Studies on the analysis of high-frequency financial data and the development of algorithms for processing and interpreting such data.
  • Statistical Methods in Finance: Research on statistical techniques and methods used for financial analysis, model fitting, and hypothesis testing.
  • Financial Econometrics: Articles on econometric models and methods applied to financial data, including time series analysis and volatility modeling.
  • Case Studies and Applications: Research showcasing practical applications, case studies, and real-world examples of algorithmic finance techniques and strategies.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  2157-6203

    Electronic ISSN:  2158-5571

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 2024:  0.3

  • Subject Area and Category:  Computer Science, Computer Science Applications, Computer Vision and Pattern Recognition, Economics, Econometrics and Finance, Finance, Mathematics, Computational Mathematics

  • Publication Frequency:  

  • H Index:  13

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  

    Q4:  Computational Mathematics

  • Cite Score:  0.5

  • SNIP:  0.050

  • Journal Rank(SJR):  0.107