Overview of Advanced Methods of Reinforcement Learning in Finance

开始时间: 06/27/2020 持续时间: Unknown

所在平台: Coursera

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大学或机构: CourseraNew

   

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

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In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning. Finally, we will overview trending and potential applications of Reinforcement Learning for high-frequency trading, cryptocurrencies, peer-to-peer lending, and more. After taking this course, students will be able to - explain fundamental concepts of finance such as market equilibrium, no arbitrage, predictability, - discuss market modeling, - Apply the methods of Reinforcement Learning to high-frequency trading, credit risk peer-to-peer lending, and cryptocurrencies trading.

金融强化学习高级方法概述:在我们的专业课程的最后一期,金融强化学习高级方法概述中,我们将更深入地研究第三门课程《金融强化学习》中讨论的主题。 特别是,我们将讨论强化学习,期权定价和物理学之间的联系,强化学习逆向对市场影响和价格动态建模的含义,以及强化学习中的感知-行动周期。最后,我们将概述强化学习在高频交易,加密货币,点对点借贷等方面的趋势和潜在应用。 完成本课程后,学生将能够 -解释金融的基本概念,例如市场均衡,无套利,可预测性, -讨论市场建模, -将强化学习的方法应用于高频交易,信用风险对等借贷和加密货币交易。

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In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in

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