量化前沿速递：机器学习[20240310]

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[1] Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators

利用Transformer神经网络和技术指标增强加密货币价格预测

来源:ARXIV_20240307

[2] A machine learning workflow to address credit default prediction

解决信用违约预测问题的机器学习工作流

来源:ARXIV_20240307

[3] Reinforcement Learning for Optimal Execution when Liquidity is Time-Varying

流动性时变时最优执行的强化学习

来源:-

[4] Can We Beat Random Walk in Forecasting Exchange Rates? Evidence Using a Large Panel of Individual Stock Prices

在预测汇率时我们能打败随机游动吗？使用单个股票价格的大面板的证据

来源:-

[5] Financial Knowledge of Individual Investors and Earnings Management

个人投资者的财务知识与盈余管理

来源:SSRN_20240310

[1] Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators

标题:利用Transformer神经网络和技术指标增强加密货币价格预测

作者:Mohammad Ali Labbaf Khaniki, Mohammad Manthouri

来源:ARXIV_20240307

Abstract : This study presents an innovative approach for predicting cryptocurrency time series, specifically focusing on Bitcoin, Ethereum, and Litecoin. The methodology integrates the use of technical indicators, a Performer neural network, and BiLSTM (Bidirectional Long Short Term Memory) to capture temporal dynamics and extract significant features from raw cryptocurrency data. The application of technical indicators, such facilitates the extraction of intricate patterns,......(摘要翻译及全文见知识星球)

Keywords :

[2] A machine learning workflow to address credit default prediction

标题:解决信用违约预测问题的机器学习工作流

作者:Rambod Rahmani, Marco Parola, Mario G.C.A. Cimino

来源:ARXIV_20240307

Abstract : Due to the recent increase in interest in Financial Technology (FinTech), applications like credit default prediction (CDP) are gaining significant industrial and academic attention. In this regard, CDP plays a crucial role in assessing the creditworthiness of individuals and businesses, enabling lenders to make informed decisions regarding loan approvals and risk management. In this paper, we propose a workflow based approach......(摘要翻译及全文见知识星球)

Keywords :

[3] Reinforcement Learning for Optimal Execution when Liquidity is Time-Varying

标题:流动性时变时最优执行的强化学习

作者:Andrea Macrì,Fabrizio Lillo

来源:-

Abstract : Optimal execution is an important problem faced by any trader. Most solutions are based on the assumption of constant market impact, while liquidity is known to be dynamic. Moreover, models with time-varying liquidity typically assume that it is observable, despite the fact that, in reality, it is latent and hard to measure in real time. In this paper we show that......(摘要翻译及全文见知识星球)

Keywords : Optimal execution; reinforcement learning; double deep q-learning; time varying liquidity

[4] Can We Beat Random Walk in Forecasting Exchange Rates? Evidence Using a Large Panel of Individual Stock Prices

标题:在预测汇率时我们能打败随机游动吗？使用单个股票价格的大面板的证据

作者:Yumeng Cui,Yongmiao Hong,Naijing Huang

来源:-

Abstract : Exchange rate forecast is of great importance to economic agents, including households, businesses, international investors and policy makers. However, predicting exchange rates is a challenging task. The Meese-Rogoff puzzle claims that economic models of exchange rates seem unable to outperform a simple Random Walk model in out-of-sample forecasting. This paper uses a novel econometric micro approach to forecast exchange rates based......(摘要翻译及全文见知识星球)

Keywords : Exchange Rates Forecasting, Large Model, Machine Learning, Individual Stock Prices

[5] Financial Knowledge of Individual Investors and Earnings Management

标题:个人投资者的财务知识与盈余管理

作者:Zhuoyi Yang,Xiong Xiong,Yahui An,Xu Feng,Xing Cao

来源:SSRN_20240310

Abstract : Our paper utilizes text analysis methods and machine learning techniques to construct a professional financial knowledge dictionary to measure the financial knowledge levels of individual investors, investigating whether the financial knowledge of individual investors can constrain earnings management. We find that the higher financial knowledge level of investors significantly constrains earnings management in the next year. After using instrumental variables, the......(摘要翻译及全文见知识星球)

Keywords : Financial Knowledge, Individual Investors, Earnings Management, Textural Analysis