WILEY Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage

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.

Great entry level book for quantitative researchers

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.