[1] Reinforcement Learning in Agent Based Market Simulation基于Agent的市场模拟中的强化学习来源:ARXIV_20240401[2] Using Images as Covariates使用图像作为协变量来源:ARXIV_20240401[3] Predicting the impact of e commerce indices on international trade in Iran and other selected members of the Organization for Economic Co operation and Development (OECD) by using the artificial intelligence and P VAR model利用人工智能和P VAR模型预测电子商务指数对伊朗和经济合作与发展组织（经合组织）其他选定成员国国际贸易的影响来源:ARXIV_20240401[4] Empowering Credit Scoring Systems with Quantum Enhanced Machine Learning用量子增强的机器学习增强信用评分系统来源:ARXIV_20240402[5] From attention to profit从关注到利润来源:ARXIV_20240402[6] Using Machine Learning to Forecast Market Direction with Efficient Frontier Coefficients利用机器学习预测具有有效前沿系数的市场方向来源:ARXIV_20240402[7] Missing Data Imputation With Granular Semantics and AI driven Pipeline for Bankruptcy Prediction基于粒度语义和人工智能驱动的破产预测管道的缺失数据预测来源:ARXIV_20240402
[1] Reinforcement Learning in Agent Based Market Simulation
标题:基于Agent的市场模拟中的强化学习作者:Zhiyuan Yao, Zheng Li, Matthew Thomas, Ionut Florescu来源:ARXIV_20240401Abstract : Investors and regulators can greatly benefit from a realistic market simulator that enables them to anticipate the consequences of their decisions in real markets. However, traditional rule based market simulators often fall short in accurately capturing the dynamic behavior of market participants, particularly in response to external market impact events or changes in the behavior of other participants. In this study,......(摘要翻译及全文见知识星球)Keywords :
[2] Using Images as Covariates
标题:使用图像作为协变量作者:Ardyn Nordstrom, Morgan Nordstrom, Matthew D. Webb来源:ARXIV_20240401Abstract : This paper details an innovative methodology to integrate image data into traditional econometric models. Motivated by forecasting sales prices for residential real estate, we harness the power of deep learning to add information contained in images as covariates. Specifically, images of homes were categorized and encoded using an ensemble of image classifiers (ResNet 50, VGG16, MobileNet, and Inception V3).......(摘要翻译及全文见知识星球)Keywords :
[3] Predicting the impact of e commerce indices on international trade in Iran and other selected members of the Organization for Economic Co operation and Development (OECD) by using the artificial intelligence and P VAR model
标题:利用人工智能和P VAR模型预测电子商务指数对伊朗和经济合作与发展组织（经合组织）其他选定成员国国际贸易的影响作者:Soheila Khajoui, Saeid Dehyadegari, Sayyed Abdolmajid Jalaee来源:ARXIV_20240401
Abstract : This study aims at predicting the impact of e commerce indicators on international trade of the selected OECD countries and Iran, by using the artificial intelligence approach and P VAR. According to the nature of export, import, GDP, and ICT functions, and the characteristics of nonlinearity, this analysis is performed by using the MPL neural network. The export, import, GDP, and......(摘要翻译及全文见知识星球)Keywords :
[4] Empowering Credit Scoring Systems with Quantum Enhanced Machine Learning
标题:用量子增强的机器学习增强信用评分系统作者:Javier Mancilla, André Sequeira, Iraitz Montalbán, Tomas Tagliani, Frnacisco Llaneza, Claudio Beiza来源:ARXIV_20240402Abstract : Quantum Kernels are projected to provide early stage usefulness for quantum machine learning. However, highly sophisticated classical models are hard to surpass without losing interpretability, particularly when vast datasets can be exploited. Nonetheless, classical models struggle once data is scarce and skewed. Quantum feature spaces are projected to find better links between data features and the target class to be predicted......(摘要翻译及全文见知识星球)Keywords :
[5] From attention to profit
标题:从关注到利润作者:Zhaofeng Zhang, Banghao Chen, Shengxin Zhu, Nicolas Langrené来源:ARXIV_20240402Abstract : In traditional quantitative trading practice, navigating the complicated and dynamic financial market presents a persistent challenge. Former machine learning approaches have struggled to fully capture various market variables, often ignore long term information and fail to catch up with essential signals that may lead the profit. This paper introduces an enhanced transformer architecture and designs a novel factor based on the......(摘要翻译及全文见知识星球)Keywords :
[6] Using Machine Learning to Forecast Market Direction with Efficient Frontier Coefficients
标题:利用机器学习预测具有有效前沿系数的市场方向作者:Nolan Alexander, William Scherer来源:ARXIV_20240402Abstract : We propose a novel method to improve estimation of asset returns for portfolio optimization. This approach first performs a monthly directional market forecast using an online decision tree. The decision tree is trained on a novel set of features engineered from portfolio theory the efficient frontier functional coefficients. Efficient frontiers can be decomposed to their functional form, a square root......(摘要翻译及全文见知识星球)Keywords :
[7] Missing Data Imputation With Granular Semantics and AI driven Pipeline for Bankruptcy Prediction
标题:基于粒度语义和人工智能驱动的破产预测管道的缺失数据预测作者:Debarati Chakraborty, Ravi Ranjan来源:ARXIV_20240402Abstract : This work focuses on designing a pipeline for the prediction of bankruptcy. The presence of missing values, high dimensional data, and highly class imbalance databases are the major challenges in the said task. A new method for missing data imputation with granular semantics has been introduced here. The merits of granular computing have been explored here to define this method. The......(摘要翻译及全文见知识星球)Keywords :
