算法和高頻交易
本書將基礎(chǔ)經(jīng)濟(jì)學(xué)、高頻數(shù)據(jù)的經(jīng)驗基礎(chǔ)和數(shù)學(xué)工具以及模型聯(lián)系在一起，為讀者在試圖理解和設(shè)計成功的交易算法時面對的各種各樣的問題，提供足夠廣闊的視野。本書分為三個部分。第一部分給出了交易市場的基本概念、理論以及經(jīng)驗事實。第1章介紹了電子交易市場、市場參與者和訂單簿。第2章概述了金融微觀結(jié)構(gòu)市場模型。第3章和第4章對市場進(jìn)行了實證和統(tǒng)計分析。第二部分也就是第5章介紹了交易算法分析相關(guān)的數(shù)學(xué)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**執(zhí)行策略，即代理商必須在預(yù)先指定的窗口上清算或收購大頭寸，使用市價單或限價單進(jìn)行持續(xù)交易。第9章涉及基于交易量日程的執(zhí)行算法，為希望跟蹤市場整體交易量的投資者制定戰(zhàn)略。第10章展示了做市商如何在限價訂單簿中選擇限價單的發(fā)布位置。考慮了包括對庫存風(fēng)險的厭惡，逆向選擇以及價格動態(tài)的短期趨勢等因素。第11章專注于統(tǒng)計套...
本書將基礎(chǔ)經(jīng)濟(jì)學(xué)、高頻數(shù)據(jù)的經(jīng)驗基礎(chǔ)和數(shù)學(xué)工具以及模型聯(lián)系在一起，為讀者在試圖理解和設(shè)計成功的交易算法時面對的各種各樣的問題，提供足夠廣闊的視野。本書分為三個部分。第一部分給出了交易市場的基本概念、理論以及經(jīng)驗事實。第1章介紹了電子交易市場、市場參與者和訂單簿。第2章概述了金融微觀結(jié)構(gòu)市場模型。第3章和第4章對市場進(jìn)行了實證和統(tǒng)計分析。第二部分也就是第5章介紹了交易算法分析相關(guān)的數(shù)學(xué)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**執(zhí)行策略，即代理商必須在預(yù)先指定的窗口上清算或收購大頭寸，使用市價單或限價單進(jìn)行持續(xù)交易。第9章涉及基于交易量日程的執(zhí)行算法，為希望跟蹤市場整體交易量的投資者制定戰(zhàn)略。第10章展示了做市商如何在限價訂單簿中選擇限價單的發(fā)布位置。考慮了包括對庫存風(fēng)險的厭惡，逆向選擇以及價格動態(tài)的短期趨勢等因素。第11章專注于統(tǒng)計套利和配對交易。第12章展示如何利用限價訂單簿中提供的交易量信息來改善執(zhí)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.