Yuping Song
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View article: Metal commodity futures price forecasting based on a hybrid secondary decomposition error-corrected model
Metal commodity futures price forecasting based on a hybrid secondary decomposition error-corrected model Open
Although the existing hybrid model based on decomposition can improve the prediction performance for financial data, it ignores the effective information of the error between the real value and the predicted value. In order to explore the …
View article: Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection
Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection Open
Cryptocurrency transaction fraud detection faces the dual challenges of increasingly complex transaction patterns and severe class imbalance. Traditional methods rely on manual feature engineering and struggle to capture temporal and struc…
View article: A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector
A Study of the Factors Contributing to the Impact of Climate Risks on Corporate Performance in China’s Energy Sector Open
As the climate crisis intensifies, corporate operations face unprecedented challenges from increasing climate risks, necessitating rigorous investigation into their resultant economic ramifications. This study employs text analysis and mac…
View article: Self-Weighted Quantile Estimation for Drift Coefficients of Ornstein–Uhlenbeck Processes with Jumps and Its Application to Statistical Arbitrage
Self-Weighted Quantile Estimation for Drift Coefficients of Ornstein–Uhlenbeck Processes with Jumps and Its Application to Statistical Arbitrage Open
The estimation of drift parameters in the Ornstein–Uhlenbeck (O-U) process with jumps primarily employs methods such as maximum likelihood estimation, least squares estimation, and least absolute deviation estimation. These methods general…
View article: Transformer-Based Downside Risk Forecasting: A Data-Driven Approach with Realized Downward Semi-Variance
Transformer-Based Downside Risk Forecasting: A Data-Driven Approach with Realized Downward Semi-Variance Open
Realized downward semi-variance (RDS) has been realized as a key indicator to measure the downside risk of asset prices, and the accurate prediction of RDS can effectively guide traders’ investment behavior and avoid the impact of market f…
View article: Nature Gas Futures Price Forecasting Based on NR-LSTM Hybrid Model
Nature Gas Futures Price Forecasting Based on NR-LSTM Hybrid Model Open
Nowadays, climate change and geopolitics have led to policy uncertainty, which in turn affects energy prices. Accurate prediction of energy futures prices can effectively avoid uncertainty risks. This paper constructs a non-parametric regr…
View article: Rolling Decomposition Prediction of Gold Price Based on Nonparametric and Deep Learning Models
Rolling Decomposition Prediction of Gold Price Based on Nonparametric and Deep Learning Models Open
Gold futures, as an essential hedge asset, have received much attention. In this paper, the VMD-reconstruction-integration framework combining rolling windows is proposed to predict gold futures prices. The Fine to Coarse (FTC) method is u…
View article: Gold Futures Volatility Forecasting Based on HAR-QR and Machine Learning Model
Gold Futures Volatility Forecasting Based on HAR-QR and Machine Learning Model Open
Compared with traditional least squares regression, quantile regression can handle outliers and error tails in practical analysis problems, and can better describe the complex distribution dependencies between dependent and independent var…
View article: WITHDRAWN: The Role of Social Support on Consumers' Purchase Intention in the Context of Live Streaming E-commerce: The Evidence from China
WITHDRAWN: The Role of Social Support on Consumers' Purchase Intention in the Context of Live Streaming E-commerce: The Evidence from China Open
The full text of this preprint has been withdrawn, as it was submitted in error. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
View article: Deep Learning-Based Performance Optimization of English Machine Translation
Deep Learning-Based Performance Optimization of English Machine Translation Open
This article proposes a performance optimization method for English machine translation based on deep learning and introduces the Bahdanau attention mechanism. Using a parallel corpus of approximately 30,923 sentences for training and test…
View article: WITHDRAWN: The Role of Social Support on Consumers' Purchase Intention in the Context of Live Streaming E-commerce: The Evidence from China
WITHDRAWN: The Role of Social Support on Consumers' Purchase Intention in the Context of Live Streaming E-commerce: The Evidence from China Open
Live streaming e-commerce to promote products and sales has become a trend for online sellers. Although some studies have focused on consumers' behavioral intentions, few studies have investigated the social support provided by streamers i…
View article: Impact of COVID-19 on jump occurrence in capital markets
Impact of COVID-19 on jump occurrence in capital markets Open
In this paper, we investigate the relationship between the indicators for COVID-19 monitoring and the dynamic of jumps across six major financial markets including China, France, Italy, Germany, the UK, and the US. First, this paper finds …
View article: On Stock Volatility Forecasting under Mixed-Frequency Data Based on Hybrid RR-MIDAS and CNN-LSTM Models
On Stock Volatility Forecasting under Mixed-Frequency Data Based on Hybrid RR-MIDAS and CNN-LSTM Models Open
Most of the deep-learning algorithms on stock price volatility prediction in the existing literature use data such as same-frequency market indicators or technical indicators, and less consider mixed-frequency data, such as macro-data. Com…
View article: Volatility Dynamics and Mixed jump-GARCH Model Based Jump Detection in Financial Markets
Volatility Dynamics and Mixed jump-GARCH Model Based Jump Detection in Financial Markets Open
View article: Nonparametric Threshold Estimation for Drift Function in Jump–Diffusion Model of Interest Rate Using Asymmetric Kernel
Nonparametric Threshold Estimation for Drift Function in Jump–Diffusion Model of Interest Rate Using Asymmetric Kernel Open
The existing estimators for the drift coefficient in the diffusion model with jumps involve jump components and possess larger boundary error. How to effectively estimate the drift function is an important issue that faces challenges and h…
View article: Exponential Inequality of Marked Point Processes
Exponential Inequality of Marked Point Processes Open
This paper presents the uniform concentration inequality for the stochastic integral of marked point processes. We developed a new chaining method to obtain the results. Our main result is presented under an entropy condition for partition…
View article: Threshold reweighted Nadaraya–Watson estimation of jump-diffusion models
Threshold reweighted Nadaraya–Watson estimation of jump-diffusion models Open
In this paper, we propose a new method to estimate the diffusion function in the jump-diffusion model. First, a threshold reweighted Nadaraya–Watson-type estimator is introduced. Then, we establish asymptotic normality for the estimator an…
View article: Volatility Forecasting for High-Frequency Financial Data Based on Web Search Index and Deep Learning Model
Volatility Forecasting for High-Frequency Financial Data Based on Web Search Index and Deep Learning Model Open
The existing index system for volatility forecasting only focuses on asset return series or historical volatility, and the prediction model cannot effectively describe the highly complex and nonlinear characteristics of the stock market. I…
View article: Variance reduction estimation for return models with jumps using gamma asymmetric kernels
Variance reduction estimation for return models with jumps using gamma asymmetric kernels Open
This paper discusses Nadaraya-Watson estimators for the unknown coefficients in second-order diffusion model with jumps constructed with Gamma asymmetric kernels. Compared with existing nonparametric estimators constructed with Gaussian sy…
View article: Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps
Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps Open
In this article, local linear estimators are adapted for the unknown infinitesimal coefficients associated with continuous‐time asset return models with jumps, which can correct the bias automatically due to their simple bias representatio…
View article: Bias Correction Estimation for Continuous-Time Asset Return Model with Jumps
Bias Correction Estimation for Continuous-Time Asset Return Model with Jumps Open
In this paper, local linear estimators are adapted for the unknown infinitesimal coefficients associated with continuous-time asset return model with jumps, which can correct the bias automatically due to their simple bias representation. …
View article: On Double Smoothed Volatility Estimation of Potentially Nonstationary Jump-Diffusion Model
On Double Smoothed Volatility Estimation of Potentially Nonstationary Jump-Diffusion Model Open
In this paper, we present the double smoothed nonparametric approach for infinitesimal conditional volatility of jump-diffusion model based on high frequency data. Under certain minimal conditions, we obtain the strong consistency and asym…
View article: Local Nonparametric Estimation for Second-Order Jump-Diffusion Model Using Gamma Asymmetric Kernels
Local Nonparametric Estimation for Second-Order Jump-Diffusion Model Using Gamma Asymmetric Kernels Open
This paper discusses the local linear smoothing to estimate the unknown first and second infinitesimal moments in second-order jump-diffusion model based on Gamma asymmetric kernels. Under the mild conditions, we obtain the weak consistenc…
View article: Discretization Error of Stochastic Iterated Integrals
Discretization Error of Stochastic Iterated Integrals Open
In this paper, the weak convergence about the discretization error of stochastic iterated integrals in the Skorohod sense are studied, while the integrands and integrators of iterated integrals are supposed to be semimartingales with jumps…
View article: One-step Local M-estimator for Integrated Jump-Diffusion Models
One-step Local M-estimator for Integrated Jump-Diffusion Models Open
In this paper, robust nonparametric estimators, instead of local linear estimators, are adapted for infinitesimal coefficients associated with integrated jump-diffusion models to avoid the impact of outliers on accuracy. Furthermore, consi…
View article: Central Limit Theorems of Local Polynomial Threshold Estimators for Diffusion Processes with Jumps
Central Limit Theorems of Local Polynomial Threshold Estimators for Diffusion Processes with Jumps Open
Central limit theorems play an important role in the study of statistical inference for stochastic processes. However, when the nonparametric local polynomial threshold estimator, especially local linear case, is employed to estimate the d…
View article: Effect of variable network clustering on the accuracy of node centrality
Effect of variable network clustering on the accuracy of node centrality Open
Measurements of node centrality are based on characterizing the network topology structure in a certain perspective. Changing the network topology structure would affect the accuracy of the measurements. In this paper, we employ the Holme-…