A5103057866- Market Dynamics and Volatility
- Energy, Environment, Economic Growth
- Climate Change Policy and Economics
- Energy, Environment, and Transportation Policies
- Environmental Impact and Sustainability
- Energy Load and Power Forecasting
- Monetary Policy and Economic Impact
- Complex Systems and Time Series Analysis
- Grey System Theory Applications
- Financial Risk and Volatility Modeling
- Nuclear Materials and Properties
- Ion-surface interactions and analysis
- Fiscal Policy and Economic Growth
- Economic and Environmental Valuation
- Diamond and Carbon-based Materials Research
- Semiconductor materials and devices
- Integrated Circuits and Semiconductor Failure Analysis
- Global Energy Security and Policy
- Blockchain Technology Applications and Security
- Fiscal Policies and Political Economy
- Energy and Environment Impacts
- Stock Market Forecasting Methods
- Advanced Power Generation Technologies
- Radioactive element chemistry and processing
- Global Energy and Sustainability Research
IPAG Business School
2014-2024
Institut de Recherches en Technologies et Sciences pour le Vivant
2024
Université Paris 8
2011-2023
Centre National de la Recherche Scientifique
1971-2021
Université de Versailles Saint-Quentin-en-Yvelines
2017-2021
Université Paris-Saclay
2017-2021
Groupe d’Étude de la Matière Condensée
2017-2021
Analyse, Géométrie et Modélisation
2017
Université Paris Cité
2014
EconomiX
2011
Abstract This study uses complex network analysis to investigate global stock market co-movement during the black swan event of Coronavirus Disease 2019 (COVID-19) pandemic. We propose a novel method for calculating price index correlations based on open-high-low-close (OHLC) data. More intraday information can be utilized compared with widely used return-based method. Hypothesis testing was select edges incorporated in avoid rigid setting artificial threshold. The topologies constructed...
Abstract For improving forecasting accuracy and trading performance, this paper proposes a new multi‐objective least squares support vector machine with mixture kernels to forecast asset prices. First, kernel function is introduced into taking full use of global local functions, which adaptively determined following data‐driven procedure. Second, fitness proposed by incorporating level particle swarm optimization used synchronously search the optimal model selections kernels. Taking CO 2...
A theory of photovoltaic effects in nonhomogeneous semiconductors which takes into account the variations bandgap, effective masses, mobilities, majority carrier concentrations, and pair lifetime is presented. The observed on graded-composition Cd <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</inf> Hg xmlns:xlink="http://www.w3.org/1999/xlink">1-x</inf> Te single crystals are essentially due to gradient gap, but strongly reduced by diffusion...
Abstract This paper aims at the imbalanced characteristics and proposes a novel evolutionary cost‐sensitive support vector machine (CSSVM) by integrating learning, machine, genetic algorithm for carbon price trend prediction. First, prediction is converted into binary‐class problem CSSVM, in which higher misclassification cost imposed on minority samples. In comparison, more negligible most Second, (GA) used to optimize all parameters of CSSVM synchronously. Taking Beijing, Hubei, Guangdong...