A5012991424- Forecasting Techniques and Applications
- Stock Market Forecasting Methods
- Time Series Analysis and Forecasting
- Advanced Computational Techniques and Applications
- Statistical Methods and Inference
- Financial Risk and Volatility Modeling
- Energy Load and Power Forecasting
- Bayesian Methods and Mixture Models
- Statistical Distribution Estimation and Applications
- Evaluation and Optimization Models
- Service-Oriented Architecture and Web Services
- Corporate Finance and Governance
- Web Applications and Data Management
- Financial Distress and Bankruptcy Prediction
- Statistical Methods and Bayesian Inference
- Credit Risk and Financial Regulations
- Neural Networks and Applications
- Air Quality Monitoring and Forecasting
- Advanced Statistical Methods and Models
- Market Dynamics and Volatility
- Atmospheric and Environmental Gas Dynamics
- Supply Chain and Inventory Management
- Auditing, Earnings Management, Governance
- Cooperative Studies and Economics
- Occupational Health and Safety Research
Central University of Finance and Economics
2013-2024
Sun Yat-sen University
2024
Peking University
2024
The First People's Hospital of Xiaoshan District, Hangzhou
2024
Weinan Normal University
2023
University of Southampton
2022
Alibaba Group (China)
2022
Qingdao University
2022
Florida International University
2021
Huazhong University of Science and Technology
2021
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds future is both exciting challenging, with individuals organisations seeking to minimise risks maximise utilities. large number forecasting applications calls for a diverse set methods tackle real-life challenges. This article provides non-systematic review theory practice forecasting. We provide an overview wide range theoretical, state-of-the-art models, methods, principles,...
ABSTRACT In this paper we develop a measure of competition based on management's disclosures in their 10‐K filing and find that firms’ rates diminishing marginal returns new existing investment vary significantly with our measure. We show these firm‐level are related to industry‐level measures disclosure (e.g., Herfindahl index), but capture something distinctly new. particular, the has both across‐industry variation within‐industry variation, each is firm's future returns. As such, useful...
Abstract Background: Given the recent updates in cancer burden estimates by GLOBOCAN 2022, this study was undertaken to provide pertinent perspectives within context of Human Development Index (HDI) and major world economies. Methods: Datasets sourced from encompassed cases deaths across all types alongside projections up 2050. Cancer incidences top 10 cancers China four distinct HDI-classified regions were compared using descriptive analyses. Age-standardized incidence rates (ASIRs)...
Understanding teachers’ conceptions surrounding integrated STEM education is vital to the successful implementation of curricula in K-12 classrooms. Of particular interest understanding how teachers conceptualize role disciplines within their teaching. Further, despite knowing that content-agnostic characteristics are important, little known about real-world problems, 21st century skills, and promotion careers instruction. This study used an exploratory case design investigate 19 science...
This paper examines the nature of virtual teams and their place in networked economy. It presents a framework for categorising argues that fundamental changes have taken business environment which force people organisations to operate 'two spaces' simultaneously: physical space electronic space. highlights some issues trust identity exist that, due certain barriers, only small proportion these reach satisfactory level performance. Using evidence from two recent sets studies, it barriers...
Abstract The explosion of time series data in recent years has brought a flourish new analysis methods, for forecasting, clustering, classification and other tasks. evaluation these methods requires either collecting or simulating diverse set benchmarking to enable reliable comparisons against alternative approaches. We propose GeneRAting TIme Series with controllable characteristics, named GRATIS, the use mixture autoregressive (MAR) models. simulate sets using MAR models investigate...
Quantile regression is a method of fundamental importance. How to efficiently conduct quantile for large dataset on distributed system great We show that the popularly used one-shot estimation statistically inefficient if data are not randomly across different workers. To fix problem, novel one-step developed with following nice properties. First, algorithm communication efficient. That cost demanded practically acceptable. Second, resulting estimator its asymptotic covariance same as global...
Abstract We examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. document that abnormal relative postings firm, is, unusual changes in volume from versus investors, capture locals' advantage. This measure positively predicts firms' short‐term returns as well those peer firms same city. Sentiment analysis shows posting activities primarily reflect good news, potentially due to social transmission bias short‐sales...