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[1] Credit Card Fraud Detection and Credit Risk Analysis: Machine Learning Approaches
信用卡欺诈检测和信用风险分析：机器学习方法
来源:SSRN_20250714
[2] Kernel Learning for Mean Variance Trading Strategies
均值-方差交易策略的核学习
来源:ARXIV_20250716
[3] Forecasting Intraday Volume in Equity Markets with Machine Learning
利用机器学习预测股票市场日内交易量
来源:SSRN_20250716
[4] Causality analysis of electricity market liberalization on electricity price using novel Machine Learning methods
基于新型机器学习方法的电力市场自由化对电价的因果关系分析
来源:ARXIV_20250717
[1] Credit Card Fraud Detection and Credit Risk Analysis: Machine Learning Approaches
标题:信用卡欺诈检测和信用风险分析：机器学习方法
作者:Ankita Anand,Siddhartha Chakrabarty
来源:SSRN_20250714
Abstract : This study explores advancements in techniques for detection of credit card fraud detection and credit risk analysis using machine learning approaches. Two distinct datasets were analyzed: a credit card fraud dataset, addressing extreme class imbalance, and the Australian credit dataset for credit risk prediction. Methods like SMOTE and SMOTE-ENN were employed to tackle data imbalance, while ensemble techniques such as Bagging,......(摘要翻译及全文见知识星球)
Keywords : Fraud Detection, Credit Risk Analysis, SMOTE, Ensemble Learning
[2] Kernel Learning for Mean Variance Trading Strategies
标题:均值-方差交易策略的核学习
作者:Owen Futter, Nicola Muca Cirone, Blanka Horvath
来源:ARXIV_20250716
Abstract : In this article, we develop a kernel based framework for constructing dynamic, pathdependent trading strategies under a mean variance optimisation criterion. Building on the theoretical results of (Muca Cirone and Salvi, 2025), we parameterise trading strategies as functions in a reproducing kernel Hilbert space (RKHS), enabling a flexible and non Markovian approach to optimal portfolio problems. We compare this with the......(摘要翻译及全文见知识星球)
Keywords :
[3] Forecasting Intraday Volume in Equity Markets with Machine Learning
标题:利用机器学习预测股票市场日内交易量
作者:Mihai Cucuringu,Chao Zhang,Kang Li
来源:SSRN_20250716
Abstract : This study focuses on forecasting intraday trading volumes, a crucial component for portfolio implementation, especially in high-frequency (HF) trading environments. Given the current scarcity of flexible methods in this area, we employ a suite of machine learning (ML) models enriched with numerous HF predictors to enhance the predictability of intraday trading volumes. Our findings reveal that intraday stock trading volume is......(摘要翻译及全文见知识星球)
Keywords : Intraday trading volume, Machine learning, Commonality
[4] Causality analysis of electricity market liberalization on electricity price using novel Machine Learning methods
标题:基于新型机器学习方法的电力市场自由化对电价的因果关系分析
作者:Orr Shahar, Stefan Lessmann, Daniel Traian Pele
来源:ARXIV_20250717
Abstract : Relationships between the energy and the finance markets are increasingly important. Understanding these relationships is vital for policymakers and other stakeholders as the world faces challenges such as satisfying humanity s increasing need for energy and the effects of climate change. In this paper, we investigate the causal effect of electricity market liberalization on the electricity price in the US. By......(摘要翻译及全文见知识星球)
Keywords :
