算法和高频交易

联合创作 · 2023-09-26 00:14

本书将基础经济学、高频数据的经验基础和数学工具以及模型联系在一起,为读者在试图理解和设计成功的交易算法时面对的各种各样的问题,提供足够广阔的视野。本书分为三个部分。第一部分给出了交易市场的基本概念、理论以及经验事实。第1章介绍了电子交易市场、市场参与者和订单簿。第2章概述了金融微观结构市场模型。第3章和第4章对市场进行了实证和统计分析。第二部分也就是第5章介绍了交易算法分析相关的数学工具。第三部分深入研究算法交易策略的建模。第6-8章涉及**执行策略,即代理商必须在预先指定的窗口上清算或收购大头寸,使用市价单或限价单进行持续交易。第9章涉及基于交易量日程的执行算法,为希望跟踪市场整体交易量的投资者制定战略。第10章展示了做市商如何在限价订单簿中选择限价单的发布位置。考虑了包括对库存风险的厌恶,逆向选择以及价格动态的短期趋势等因素。第11章专注于统计套...

本书将基础经济学、高频数据的经验基础和数学工具以及模型联系在一起,为读者在试图理解和设计成功的交易算法时面对的各种各样的问题,提供足够广阔的视野。本书分为三个部分。第一部分给出了交易市场的基本概念、理论以及经验事实。第1章介绍了电子交易市场、市场参与者和订单簿。第2章概述了金融微观结构市场模型。第3章和第4章对市场进行了实证和统计分析。第二部分也就是第5章介绍了交易算法分析相关的数学工具。第三部分深入研究算法交易策略的建模。第6-8章涉及**执行策略,即代理商必须在预先指定的窗口上清算或收购大头寸,使用市价单或限价单进行持续交易。第9章涉及基于交易量日程的执行算法,为希望跟踪市场整体交易量的投资者制定战略。第10章展示了做市商如何在限价订单簿中选择限价单的发布位置。考虑了包括对库存风险的厌恶,逆向选择以及价格动态的短期趋势等因素。第11章专注于统计套利和配对交易。第12章展示如何利用限价订单簿中提供的交易量信息来改善执行算法。

Álvaro Cartea, University College London

Álvaro Cartea is a Reader in Financial Mathematics at University College London. Before joining UCL, he was Associate Professor of Finance at Universidad Carlos III, Madrid (2009–2012) and from 2002 to 2009 he was a Lecturer (with tenure) in the School of Economics, Mathematics and Statistics at Birkbeck, University of London. He was pre...

Álvaro Cartea, University College London

Álvaro Cartea is a Reader in Financial Mathematics at University College London. Before joining UCL, he was Associate Professor of Finance at Universidad Carlos III, Madrid (2009–2012) and from 2002 to 2009 he was a Lecturer (with tenure) in the School of Economics, Mathematics and Statistics at Birkbeck, University of London. He was previously JP Morgan Lecturer in Financial Mathematics at Exeter College, Oxford.

Sebastian Jaimungal, University of Toronto

Sebastian Jaimungal is an Associate Professor and Chair of Graduate Studies in the Department of Statistical Sciences, University of Toronto, where he teaches in the PhD and Masters in Mathematical Finance programs. He consults for major banks and hedge funds focusing on implementing advance derivative valuation engines and algorithmic trading strategies. He is also an associate editor for the SIAM Journal on Financial Mathematics, the International Journal of Theoretical and Applied Finance, the journal Risks and the Argo newsletter. Jaimungal is Vice Chair for the SIAM activity group on Financial Engineering and Mathematics, and his research has been widely published in academic and practitioner journals. His recent interests include high-frequency and algorithmic trading, applied stochastic control, mean-field games, real options, and commodity models and derivative pricing.

José Penalva, Universidad Carlos III de Madrid

José Penalva is an Associate Professor at the Universidad Carlos III de Madrid, where he teaches in the PhD and Masters in Finance programs, as well as at the undergraduate level. He is currently working on information models and market microstructure and his research has been published in Econometrica and other top academic journals.

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