Systematic and Unsystematic Determinants of Sectoral Risk Default Interconnectedness [0.03%]
系统性与非系统性部门风险违约关联决定因素分析
Haithem Awijen,Younes Ben Zaied,Ahmed Imran Hunjra
Haithem Awijen
Assessing the financial stability of the banking industry, particularly in credit risk management, has become extremely crucial in times of uncertainty. Given that, this paper aims to investigate the determinants of the interconnectedness o...
Application of Supervised Machine Learning Techniques to Forecast the COVID-19 U.S. Recession and Stock Market Crash [0.03%]
基于监督机器学习技术预测新冠疫情造成的美国经济衰退和股市崩盘
Rama K Malladi
Rama K Malladi
Machine learning (ML), a transformational technology, has been successfully applied to forecasting events down the road. This paper demonstrates that supervised ML techniques can be used in recession and stock market crash (more than 20% dr...
An Intelligent Algorithm to Predict GDP Rate and Find a Relationship Between COVID-19 Outbreak and Economic Downturn [0.03%]
一种智能算法预测GDP并寻找新冠肺炎疫情与经济衰退之间关系的方法
Amir Masoud Rahmani,Seyedeh Yasaman Hosseini Mirmahaleh
Amir Masoud Rahmani
With the spread of COVID-19, economic damages are challenging for governments and people's livelihood besides its dangerous and negative impact on humanity's health, which can be led to death. Various health guidelines have been proposed to...
On ESG Portfolio Construction: A Multi-Objective Optimization Approach [0.03%]
基于多目标优化的ESG策略 portfolio构建方法研究
Panos Xidonas,Eric Essner
Panos Xidonas
Ahead of the new asset management era that calls for sustainable investments, the limitations of the traditional bi-objective mean-variance framework need to be resolved, to accommodate responsible investment objectives. In this paper, we p...
Profitability of Ichimoku-Based Trading Rule in Vietnam Stock Market in the Context of the COVID-19 Outbreak [0.03%]
新冠肺炎疫情期间基于 ichimoku 交易法则在越南股票市场的盈利性分析
Ha Che-Ngoc,Nga Do-Thi,Thao Nguyen-Trang
Ha Che-Ngoc
Ichimoku Kinkohyo or Ichimoku Cloud Chart is one of the most popular technical indicators used by traders all over the world. However, its profitability is heavily influenced by the market environment, to which it is applied. Furthermore, t...
Volatility Interdependence Between Cryptocurrencies, Equity, and Bond Markets [0.03%]
数字货币、股票和债券市场之间的波动性相互依存关系
Etienne Harb,Charbel Bassil,Talie Kassamany et al.
Etienne Harb et al.
This paper investigates (i) the return-volatility spillover between Bitcoin, Ethereum, Ripple, and Litecoin, (ii) the interdependence between cryptocurrencies' volatility and the US equity and bond markets' volatility, and (iii) the impact ...
Do Multi-Market Institutions and Renewable Energy Matter for Sustainable Development: A Panel Data Investigation [0.03%]
多市场机构和可再生能源对可持续发展的影响：基于面板数据的实证研究
Najid Ahmad,Fredj Jawadi,Muhammad Azam
Najid Ahmad
This paper measures the impact of multi-market institutions, renewable energy consumption, and infrastructure on sustainable development in 76 selected countries over the period 2000-2015. To this end, we applied a dynamic Ordinary Least Sq...
A Novel Prediction Model: ELM-ABC for Annual GDP in the Case of SCO Countries [0.03%]
一种新型预测模型：基于SCO国家案例的ELM-ABC年度GDP预测模型
Xiaohan Xu,Roy Anthony Rogers,Mario Arturo Ruiz Estrada
Xiaohan Xu
With the development of economic and technologies, the trend of annual Gross Domestic Product (GDP) and carbon dioxide (CO2) emission changes with time passes. The relationship between economic growth and carbon dioxide emissions is conside...
Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh Evidence Through XGBoost Modeling [0.03%]
汽油价格和不确定性指数能预测原油价格吗？通过XGBoost模型得出的新证据
Kais Tissaoui,Taha Zaghdoudi,Abdelaziz Hakimi et al.
Kais Tissaoui et al.
This study examines the forecasting power of the gas price and uncertainty indices for crude oil prices. The complex characteristics of crude oil price such as a non-linear structure, time-varying, and non-stationarity motivate us to use a ...
Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth [0.03%]
比较机器学习方法预测美国GDP增长的样本外表现
Ba Chu,Shafiullah Qureshi
Ba Chu
We run a 'horse race' among popular forecasting methods, including machine learning (ML) and deep learning (DL) methods, that are employed to forecast U.S. GDP growth. Given the unstable nature of GDP growth data, we implement a recursive f...