A Study of the International Stock Market Behavior During COVID-19 Pandemic Using a Driven Iterated Function System [0.03%]
驱动迭代函数系统在COVID-19疫情期间的国际股票市场行为研究
Aman Gupta,Cyril Shaju,Pratibha et al.
Aman Gupta et al.
We propose a novel approach to visualize and compare financial markets across the globe using chaos game representation (CGR) of iterated function systems (IFS). We modified a fractal method, widely used in life sciences, and applied it to ...
Hedging the Risks of MENA Stock Markets with Gold: Evidence from the Spectral Approach [0.03%]
黄金对冲中东及北非股市风险的证据——基于频谱分析方法的研究
Awatef Ourir,Elie Bouri,Essahbi Essaadi
Awatef Ourir
In this paper, we contribute to the old debate on the dynamic correlation between gold and stock markets by considering a spectral approach within the framework of portfolio hedging. Specifically, we consider eight MENA stock markets (Tunis...
Fredj Jawadi,Hachmi Ben Ameur,Stephanie Bigou et al.
Fredj Jawadi et al.
This study investigates the relationship between the financial market and the real business cycle in the US from February 1987 to March 2016. Using different monthly time-series as proxies for the financial and macroeconomic cycles, we firs...
Tail Risk Early Warning System for Capital Markets Based on Machine Learning Algorithms [0.03%]
基于机器学习算法的资本市场尾部风险预警体系研究
Zongxin Zhang,Ying Chen
Zongxin Zhang
Scientific and effective tail risk measurement and early warning are key points and difficulties in the identification and control of major risks in capital markets. In this paper, we use the autoregressive conditional Fréchet model (AcF) ...
Ivana Lolić,Petar Sorić,Marija Logarušić
Ivana Lolić
We utilize a battery of ensemble learning techniques [ensemble linear regression (LM), random forest], as well as two gradient boosting techniques [Gradient Boosting Decision Tree and Extreme Gradient Boosting (XGBoost)] to scrutinize the p...
Need to Meet Investment Goals? Track Synthetic Indexes with the SDDP Method [0.03%]
需要实现投资目标吗？用SDDP方法追踪合成指数
Lorenzo Reus,Rodolfo Prado
Lorenzo Reus
This work presents a novel application of the Stochastic Dual Dynamic Problem (SDDP) to large-scale asset allocation. We construct a model that delivers allocation policies based on how the portfolio performs with respect to user-defined (s...
Inaccurate Value at Risk Estimations: Bad Modeling or Inappropriate Data? [0.03%]
风险值估算不准确：不良建模还是不当数据？
Evangelos Vasileiou
Evangelos Vasileiou
Forecasting accurate Value-at-Risk (VaR) estimations is a crucial task in applied financial risk management. Even though there have been significant advances in the field of financial econometrics, many crises have been documented throughou...
A Mellin Transform Approach to the Pricing of Options with Default Risk [0.03%]
Mellin变换在具有违约风险的期权定价中的应用
Sun-Yong Choi,Sotheara Veng,Jeong-Hoon Kim et al.
Sun-Yong Choi et al.
The stochastic elasticity of variance model introduced by Kim et al. (Appl Stoch Models Bus Ind 30(6):753-765, 2014) is a useful model for forecasting extraordinary volatility behavior which would take place in a financial crisis and high v...
Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors [0.03%]
基于树的集成模型和动态因子的美国GDP实时预测
Barış Soybilgen,Ege Yazgan
Barış Soybilgen
In this study, we nowcast quarter-over-quarter US GDP growth rates between 2000Q2 and 2018Q4 using tree-based ensemble machine learning models, namely, bagged decision trees, random forests, and stochastic gradient tree boosting. To solve t...
Marek J Druzdzel,Jayant R Kalagnanam
Marek J Druzdzel
We describe a performance budget planning model developed for a research university, comprised of a set of 88 key variables and 38 non-linear structural equations that describe interactions among them. These equations, based on the knowledg...