[1] Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation基于路径相关蒙特卡罗模拟的加密货币价格预测来源:ARXIV_20240524[2] BERT vs GPT for financial engineering金融工程的BERT与GPT来源:ARXIV_20240524[3] A K means Algorithm for Financial Market Risk Forecasting金融市场风险预测的K均值算法来源:ARXIV_20240524[4] Decision Trees for Intuitive Intraday Trading Strategies用于直观日内交易策略的决策树来源:ARXIV_20240524[5] Tackling Decision Processes with Non Cumulative Objectives using Reinforcement Learning使用强化学习处理具有非累积目标的决策过程来源:ARXIV_20240524[6] A Dynamic Model of Performative Human ML Collaboration一种性能化人机ML协作的动态模型来源:ARXIV_20240524
[1] Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation
标题:基于路径相关蒙特卡罗模拟的加密货币价格预测作者:Ayush Singh, Anshu K. Jha, Amit N. Kumar来源:ARXIV_20240524Abstract : In this paper, our focus lies on the Merton s jump diffusion model, employing jump processes characterized by the compound Poisson process. Our primary objective is to forecast the drift and volatility of the model using a variety of methodologies. We adopt an approach that involves implementing different drift, volatility, and jump terms within the model through various machine learning techniques,......(摘要翻译及全文见知识星球)Keywords :
[2] BERT vs GPT for financial engineering
标题:金融工程的BERT与GPT作者:Edward Sharkey, Philip Treleaven来源:ARXIV_20240524Abstract : The paper benchmarks several Transformer models 4 , to show how these models can judge sentiment from a news event. This signal can then be used for downstream modelling and signal identification for commodity trading. We find that fine tuned BERT models outperform fine tuned or vanilla GPT models on this task. Transformer models have revolutionized the field of natural......(摘要翻译及全文见知识星球)Keywords :
[3] A K means Algorithm for Financial Market Risk Forecasting
标题:金融市场风险预测的K均值算法作者:Jinxin Xu, Kaixian Xu, Yue Wang, Qinyan Shen, Ruisi Li来源:ARXIV_20240524Abstract : Financial market risk forecasting involves applying mathematical models, historical data analysis and statistical methods to estimate the impact of future market movements on investments. This process is crucial for investors to develop strategies, financial institutions to manage assets and regulators to formulate policy. In today s society, there are problems of high error rate and low precision in financial market risk......(摘要翻译及全文见知识星球)Keywords :
[4] Decision Trees for Intuitive Intraday Trading Strategies
标题:用于直观日内交易策略的决策树作者:Prajwal Naga, Dinesh Balivada, Sharath Chandra Nirmala, Poornoday Tiruveedi来源:ARXIV_20240524Abstract : This research paper aims to investigate the efficacy of decision trees in constructing intraday trading strategies using existing technical indicators for individual equities in the NIFTY50 index. Unlike conventional methods that rely on a fixed set of rules based on combinations of technical indicators developed by a human trader through their analysis, the proposed approach leverages decision trees to create unique......(摘要翻译及全文见知识星球)Keywords :
[5] Tackling Decision Processes with Non Cumulative Objectives using Reinforcement Learning
标题:使用强化学习处理具有非累积目标的决策过程作者:Maximilian N gele, Jan Olle, Thomas Fösel, Remmy Zen, Florian Marquardt来源:ARXIV_20240524Abstract : Markov decision processes (MDPs) are used to model a wide variety of applications ranging from game playing over robotics to finance. Their optimal policy typically maximizes the expected sum of rewards given at each step of the decision process. However, a large class of problems does not fit straightforwardly into this framework Non cumulative Markov decision processes (NCMDPs), where instead......(摘要翻译及全文见知识星球)Keywords :
[6] A Dynamic Model of Performative Human ML Collaboration
标题:一种性能化人机ML协作的动态模型作者:Tom Sühr, Samira Samadi, Chiara Farronato来源:ARXIV_20240524Abstract : Machine learning (ML) models are increasingly used in various applications, from recommendation systems in e commerce to diagnosis prediction in healthcare. In this paper, we present a novel dynamic framework for thinking about the deployment of ML models in a performative, human ML collaborative system. In our framework, the introduction of ML recommendations changes the data generating process of human decisions,......(摘要翻译及全文见知识星球)Keywords :
