Reinforcement Learning in Finance

开始时间: 06/27/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 其他类别

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/reinforcement-learning-in-finance

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This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management. By the end of this course, students will be able to - Use reinforcement learning to solve classical problems of Finance such as portfolio optimization, optimal trading, and option pricing and risk management. - Practice on valuable examples such as famous Q-learning using financial problems. - Apply their knowledge acquired in the course to a simple model for market dynamics that is obtained using reinforcement learning as the course project. Prerequisites are the courses "Guided Tour of Machine Learning in Finance" and "Fundamentals of Machine Learning in Finance". Students are expected to know the lognormal process and how it can be simulated. Knowledge of option pricing is not assumed but desirable.

金融中的强化学习:本课程旨在介绍强化学习(RL)的基本概念,并为RL的应用开发用例,用于期权评估,交易和资产管理。 在本课程结束时,学生将能够 -使用强化学习来解决财务方面的经典问题,例如投资组合优化,最优交易以及期权定价和风险管理。 -练习一些有价值的例子,例如使用财务问题进行著名的Q学习。 -将他们在课程中获得的知识应用到一个简单的市场动态模型中,该模型使用强化学习作为课程项目而获得。 先决条件是“金融机器学习导览”和“金融机器学习基础”课程。希望学生了解对数正态过程及其模拟方法。期权定价的知识不是假定的,而是可取的。

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This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop

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