量化前沿速递：机器学习[20240717]

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[1] Attribution Methods in Asset Pricing

资产定价中的归因方法

来源:ARXIV_20240715

[2] Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses

利用人工智能为小企业解锁众筹成功

来源:ARXIV_20240716

[3] Deep Reinforcement Learning Strategies in Finance

金融领域的深度强化学习策略

来源:ARXIV_20240716

[4] Machine learning in weekly movement prediction

机器学习在每周运动预测中的应用

来源:ARXIV_20240716

[5] Decentralised Finance and Automated Market Making

去中心化金融和自动化做市

来源:SSRN_20240717

[1] Attribution Methods in Asset Pricing

标题:资产定价中的归因方法

作者:Dangxing Chen, Yuan Gao

来源:ARXIV_20240715

Abstract : Over the past few decades, machine learning models have been extremely successful. As a result of axiomatic attribution methods, feature contributions have been explained more clearly and rigorously. There are, however, few studies that have examined domain knowledge in conjunction with the axioms. In this study, we examine asset pricing in finance, a field closely related to risk management. Consequently, when......(摘要翻译及全文见知识星球)

Keywords :

[2] Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses

标题:利用人工智能为小企业解锁众筹成功

作者:Teng Ye, Jingnan Zheng, Junhui Jin, Jingyi Qiu, Wei Ai, Qiaozhu Mei

来源:ARXIV_20240716

Abstract : While small businesses are increasingly turning to online crowdfunding platforms for essential funding, over 40 of these campaigns may fail to raise any money, especially those from low socio economic areas. We utilize the latest advancements in AI technology to identify crucial factors that influence the success of crowdfunding campaigns and to improve their fundraising outcomes by strategically optimizing these......(摘要翻译及全文见知识星球)

Keywords :

[3] Deep Reinforcement Learning Strategies in Finance

标题:金融领域的深度强化学习策略

作者:Alireza Mohammadshafie, Akram Mirzaeinia, Haseebullah Jumakhan, Amir Mirzaeinia

来源:ARXIV_20240716

Abstract : Recent deep reinforcement learning (DRL) methods in finance show promising outcomes. However, there is limited research examining the behavior of these DRL algorithms. This paper aims to investigate their tendencies towards holding or trading financial assets as well as purchase diversity. By analyzing their trading behaviors, we provide insights into the decision making processes of DRL models in finance applications. Our......(摘要翻译及全文见知识星球)

Keywords :

[4] Machine learning in weekly movement prediction

标题:机器学习在每周运动预测中的应用

作者:Han Gui

来源:ARXIV_20240716

Abstract : To predict the future movements of stock markets, numerous studies concentrate on daily data and employ various machine learning (ML) models as benchmarks that often vary and lack standardization across different research works. This paper tries to solve the problem from a fresh standpoint by aiming to predict the weekly movements, and introducing a novel benchmark of random traders. This benchmark......(摘要翻译及全文见知识星球)

Keywords :

[5] Decentralised Finance and Automated Market Making

标题:去中心化金融和自动化做市

作者:Marcello Monga

来源:SSRN_20240717

Abstract : Automated market makers (AMMs) are a new type of trading venues which are revolutionising the way market participants interact. At present, the majority of AMMs are constant function market makers (CFMMs) where a deterministic trading function determines how markets are cleared. Within CFMMs, we focus on constant product market makers (CPMMs) which implements the concentrated liquidity (CL) feature. In this thesis......(摘要翻译及全文见知识星球)

Keywords : automated market making, decentralised finance, blockchain, smart contracts, algorithmic trading, market making, statistical arbitrage