Applications of Quantitative Analysis in Financial Markets

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 929

Special Issue Editor


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Guest Editor
College of Management and Economics, Tianjin University, Tianjin 300072, China
Interests: financial big data; financial engineering; asset pricing

Special Issue Information

Dear Colleagues,

We invite researchers, academics, and practitioners to submit original research articles to a Special Issue of Mathematics entitled “Applications of Quantitative Analysis in Financial Markets”. The application of quantitative analysis in financial markets has grown significantly in recent years. With the use of advanced technologies, financial investors are increasingly relying on quantitative analysis to make informed investment decisions, manage risks, and optimize their portfolios’ performance. Governments are also guiding the development of financial markets through quantitative analysis, such as encouraging green finance and corporate social responsibility. These have led to an increased demand for research and analysis in this area. Based on the above background, we propose the following topics to consider:

  • Portfolio optimization;
  • Statistical analysis of financial data;
  • Big data analytics in finance;
  • Risk management and asset pricing;
  • Environmental, social, and governance (ESG) factors in investment decision making;
  • Modeling and simulation for green finance.

Prof. Dr. Yongjie Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • quantitative analysis
  • financial markets
  • investment decision
  • big data
  • asset pricing
  • risk management
  • ESG
  • green finance
  • portfolio optimization

Published Papers (1 paper)

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Research

28 pages, 1373 KiB  
Article
Optimizing Cryptocurrency Returns: A Quantitative Study on Factor-Based Investing
by Phumudzo Lloyd Seabe, Claude Rodrigue Bambe Moutsinga and Edson Pindza
Mathematics 2024, 12(9), 1351; https://doi.org/10.3390/math12091351 - 29 Apr 2024
Viewed by 597
Abstract
This study explores cryptocurrency investment strategies by adapting the robust framework of factor investing, traditionally applied in equity markets, to the distinctive landscape of cryptocurrency assets. It conducts an in-depth examination of 31 prominent cryptocurrencies from December 2017 to December 2023, employing the [...] Read more.
This study explores cryptocurrency investment strategies by adapting the robust framework of factor investing, traditionally applied in equity markets, to the distinctive landscape of cryptocurrency assets. It conducts an in-depth examination of 31 prominent cryptocurrencies from December 2017 to December 2023, employing the Fama–MacBeth regression method and portfolio regressions to assess the predictive capabilities of market, size, value, and momentum factors, adjusted for the unique characteristics of the cryptocurrency market. These characteristics include high volatility and continuous trading, which differ markedly from those of traditional financial markets. To address the challenges posed by the perpetual operation of cryptocurrency trading, this study introduces an innovative rebalancing strategy that involves weekly adjustments to accommodate the market’s constant fluctuations. Additionally, to mitigate issues like autocorrelation and heteroskedasticity in financial time series data, this research applies the Newey–West standard error approach, enhancing the robustness of regression analyses. The empirical results highlight the significant predictive power of momentum and value factors in forecasting cryptocurrency returns, underscoring the importance of tailoring conventional investment frameworks to the cryptocurrency context. This study not only investigates the applicability of factor investing in the rapidly evolving cryptocurrency market, but also enriches the financial literature by demonstrating the effectiveness of combining Fama–MacBeth cross-sectional analysis with portfolio regressions, supported by Newey–West standard errors, in mastering the complexities of digital asset investments. Full article
(This article belongs to the Special Issue Applications of Quantitative Analysis in Financial Markets)
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