Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk)

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Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk)

Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk)


Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk)


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Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk)

Product details

Series: Mathematics, Finance and Risk

Hardcover: 356 pages

Publisher: Cambridge University Press; 1 edition (October 7, 2015)

Language: English

ISBN-10: 9781107091146

ISBN-13: 978-1107091146

ASIN: 1107091144

Product Dimensions:

7.2 x 0.8 x 10 inches

Shipping Weight: 1.9 pounds (View shipping rates and policies)

Average Customer Review:

3.1 out of 5 stars

10 customer reviews

Amazon Best Sellers Rank:

#661,108 in Books (See Top 100 in Books)

A very practically oriented and mathematically simple narrative. Plenty of examples of exactly solvable dynamic programming problems. Most chapters end with a discussion of practical implications of the calculations.

Very helpful and practical. Some mathematical maturity required.

Not very practical. The book is more of an academic art than a useful trading manual as the title indicated. It maybe useful for someone interested in academic research and paper publishing. As a previous reviewer said, the whole book is just putting everything together into a single HJB equation. It would have been better if the book could have more paragraphs devoted to numerical procedures.

Can be useful but you have to be an advanced calculus student and have to understand proofs well without practical exercises. As of this writing very little is available on their website and I had bought the book more than 9 months ago the exercises and examples are "still coming". You need more data than what is provided for sure unless you want a biased result. On the good side they have a few good ideas. I had no idea what optimal stopping even was before i read this book.

Undoubtedly one of the best books out there on this topic. It is on the mathematical end but rooted on data and realistic applications. Those who want to learn about the maths behind trading algorithms must start here.

Excellent book with detail explanation of derivations and applied to trading data.

Poorly explained on numerous topics. Far too advanced for a normal mathematical reader. Suggestion for the authors: write books the way Emmanuel derman does, or the book "brownian motion calculus" by ubbo weirsema. I would not recommend this book for some one who wants to self study. Unfortunately as of today, you still need a decent background on optimal control theory and calculus of variations to understand any concepts here.

This book gives a thorough coverage of modelling methods and algorithm design with the goal of optimal financial trading. The early parts of the book begin with description of market microstructure through a description of markets in practice, some of the classical theory of price discovery (such as the Kyle and Glosten-Milgrom models), and statistical analysis of high-frequency financial data.The later parts cover mathematical modelling of limit order book dynamics with methods of incorporating several features, and different techniques for formulating optimal trading problems. This material should be understandable by anyone with graduate level mathematics (specific topics in optimal control are introduced over the course of several chapters) and could definitely be used as a reference for a course in asset allocation or algorithmic trading. As such, it would also make an excellent resource for a student with advanced mathematical background that wants an introduction to market microstructure and trading through self-study, either with the intention of continuing with academic research or leading into an industry career where quantitative optimization of trading is an important factor.The two main strengths in my opinion are the extensive number of exercises (helpful in course design) and the clear explanation of the mathematical analysis in the latter half of the book. The most significant weakness is that I found two of the earlier chapters to be quite poorly written. Understanding some of the ideas and discussion of the topics took several rereads, and the interpretation and discussion of the statistical data analysis were quite dry. The clarity and importance of the later sections of the book make up for this though. Don't let the first few chapters turn you off before taking a stab at the second half of the book.

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