Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage

Great entry level book for quantitative researchers

I love this book as a quant including but not limited to: 1/ very intuitive, clear, consistent, and concise 2/ very good summary of the whole framework related to quant trading 3/ As a mathematician, I love the reference provided in the footnote on every page to lengthy proofs without good notation, and context. 4/ 240 pages is another reason I like it Thank you for writing this book!

The content seems good (it reads like an interesting high-level review with good pointers to external texts for details), but the print quality is on the cheap side. First the pages are in black and white: there are few figures and images, but they would be much clearer in colour. Second, and most importantly, the book comes in black with a dust cover instead of a printed one. It does feel as nice when handling it, and will age badly. I would be happy to pay more for a better quality, but the option isn't offered, and the above details were kept from the article description. All "hard covers" are not the same.

The book is a great reference covering a lot of ground in just over 200 pages. It is not necessarily beginner-friendly and the reader needs to be prepared to put in the effort to connect the dots. For people already working in the field, it offers a comprehensive review with pointers to recent research and interesting ideas to consider. Many of the sections also start with short brainteasers which are fun to think about.

The book goes through a very useful set of tools and give good explanations of why you want to use them. However, so not expect to learn the underlying maths from this book, the explanations are to short and high level for that. I would recommend this book to anyone with a good understanding of mathematics and a desire to see how it might be applied to finance.

Credo un dei migliori libri sull'argomento in assoluto. Molto scorrevole, spiegazioni chiare, non che che si legga come un romanzo, ma la parte relativa al "Forecasting" è davvero molto interessante. Insieme a "Strategic Risk Management" (di Harvey e Rattray) è la coppia di libri che non deve mancare ad ogni professionista del settore.

I think the book gives an interesting overview of what is used in the industry. However, I feel that the concepts are not explained deep enough to be useful if you don't already know them in some way.

First of all, I give a 5-star rating on this book, as it is truly an excellent book for those who consider whether to become a quant. This is one of the major objectives the author had for writing this book, so he has clearly done a huge favor to all of us non-quant's, and we should be all thankful for his generous offering of his own valuable experience and knowledge as a domain subject expert in the field, based on his successful career as a quant. For the technical contents, I actually disagree with those other fellow readers who gave a 1-star or 2-star rating. We need to set expectation right that we should not expect that with a book of $20 to $40, we can immediately learn everything about how to build a quantitative trading system to start making money immediately. Instead, we should expect how much this book has added to everyone's existing knowledge base in this field. To me, it's quite significant. I have been following the models and strategies as introduced in Forecasting and Timing Markets: A Quantitative Approach for my investing/trading and achieved moderate success. Now after studying this book, I felt that I should be able to achieve even better performance with all good points I have learnt from this book, such as: (1) PIT - point-in-time for correctly labeling time of each time-series data point or event (2) Lookahead bug that violates causality principle (3) alpha signals (4) inductive bias (5) risk budgeting (6) combining features versus combining forecasts (7) event-based forecasting (8) quant crash (9) liquidity traders (10) portfolio construction method: signal-based allocation (11) maximum daily trade size (12) Position size in terms of percentages of each name's ADV (13) Trade-rule-based strategy (14) Portofolio capacity (15) Max gross market value (GMV) (16) Kelly formula: f = p - (1-p)/R (a refresher over what I learnt before: f = 2p -1 - a special case of R =1) (17) Slow/fast forecast (18) Information asymmetry (19) position turnover (20) Strategy performance during riskier periods such as the quant dislocations of 2007 and 2020 (21) production trading (22) constraints in sizing (23) risk management (24) Programming: check all inputs and function calls that can potentially fail. (25) Order Mgmt System Once again, I am very grateful as this seems to be the first book about what a quant does on a daily basis. Finally, I wish the author and all quants even greater achievements and accomplishments in their career, both from work perspective and financial perspective. I used to be a physicist long time ago as well, with tons of math learnt and research work done, but jumped to computers two decades ago. One thing that this book helped me settle with myself is that I do not regret that I did not pursue a quant career long time ago, as this book helped convince me that complicated, advanced math doesn't seem to work well with the turbulent markets. In this regard, Warren Buffett remains the best (and maybe one of the few) example of how one can deal with the turbulent markets masterfully and CONSISTENTLY.

Das Buch gibt einen guten Überblick, was es in dem Bereich alles gibt. Für Anfänger sicher gut, aber die werden den roten Faden vermissen. Für etwas erfahrerene Trader hat das Buch keinen Wert. Ich habe nix in dem Buch gefunden, was man nicht mit 2 Minuten Internetsuche auch finden würde. Deswegen 3 Punkte, weil viel zu teuer.

On one hand, it's a book that covers a lot of topics and it's well written. The printing and cover is good quality, it's a beautiful book. In the other hand, if you're a newbie to machine learning, math or finance you'll be lost in a second. If you're enough qualified to understand you already know most of the book content. Maybe there is some tips to take from and some ideas to take from this book but that's clearly in between for a newbie and a pro. The author seems very good but I thought I'll learn more things I was expecting more real exemple and less basic theory..it takes me times to read but I didn't get a lot of value from this reading. But still the author seems very good and the book itself is a beautiful object.