Special Issue "Mathematical Analysis in Economics and Management"
Deadline for manuscript submissions: 31 August 2020.
Interests: financial econometrics; investment management; decision science; risk analysis
In recent years, mathematical analysis models of economics and management have attracted a great deal of attention and been studied by many researchers from a broad range of mathematical viewpoints, including the mathematical analysis model in economics and management, like the econometric model, quantitative model, business intelligence, big data, data mining approach, machine learning, integration of decision science analysis, and statistical model.
The purpose of this Special Issue is to establish a collection of papers that develop novel insights on mathematical analysis methods for criteria decision support frameworks and/or to apply artificial-intelligence-based approaches, the econometric method, quantitative model, etc. to improve the current state-of-the-art in the economics and management field. Of special interest are papers that deal with economics, financial technology, business intelligence, and management.
Prof. Yi-Hsien Wang
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 papers will be 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 monthly 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 1200 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.
- Financial technology
- Mobile payment
- Equity crowdfunding
- Big data
- Machine learning
- Statistical model
- Decision science analysis
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Commodities Markets to Oil Funds – A Garch-Midas Model
Authors: Arthur Jin Lin 1 and Hai-Yen Chang 2,*
Affiliation: 1.Graduate Institute of International Business, National Taipei University, New Taipei City 237, Taiwan; [email protected] 2.Department of Banking and Finance, Chinese Culture University, Taipei City 111, Taiwan; [email protected]
Abstract: The oil funds have experienced high volatility over the last decade. This study applied the GARCH-MIDAS model on the data from January 2008 to April 2020 to investigates volatility transmission from the equity (Standard and Poor’s 500 Index), spot freight (Baltic Dry Index), commodities (Standard and Poor’s Goldman Sachs Commodity Index), currency (U.S. Dollar Index), and crude oil (West Texas Intermediate) markets to United States Oil Fund (USO) and BlackRock World Energy Fund A2 (BGF). By dividing the sample into two (before and after the 2018 U.S.-China trade war), we find the volatility transmission increasing after the turbulent period. The empirical evidence indicates a significant volatility transmission only from the equity market to oil funds before the U.S.-China trade war. Volatility transmission increased in directions from the equity, spot freight, commodities, and crude oil markets to oil funds after the U.S.-China trade war, extending to the COVID-19 pandemic. The results suggest that investors can use the equity market to predict oil fund movement during the tranquil and turmoil periods. Investors can use the equity, spot freight, commodities, and crude oil markets to forecast the volatility of oil funds during the turmoil periods, protecting themselves against high volatility of oil funds.