NEWS FLASH

Meetup Dec 12 in North York! Quant ‘Secret Sauce’ tricks of Matlab, bridge to C++/C#, FREE .NET open source HFT trading platform, and MYSQL historical database for back testing

Register and details at:

http://www.meetup.com/quant-finance/events/42092262/

Quant Book Opinion

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems book review

Written by Administrator Wednesday, 26 January 2011 12:39

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems book review

This book seems not to target any special trade outside of those who may want to build a high trading system. From a beginners perspective, I have no doubt this book covers all aspects when it comes to high frequency trading strategies, models, and technology. It seems this book may tick off more advanced readers who think it was written for them. Check out the reviews of over at Amazon:

http://www.amazon.com/High-Frequency-Trading-Practical-Algorithmic-Strategies/dp/0470563761

One review I agree is that book does not specify who the book is written for but as a beginner, you could easily agree that all major aspects are covered. This includes the major algorithms and even different arbitrage strategies but don’t expect this book to go into great detail on each concept. As said, if you are unfamiliar with the algorithms, don’t even think this book will be an intro to these concepts. There are better books for that. I do agree with some of the arguments that are mentioned in reviews over at Amazon on that. It just appears on what your level is on this topic.

There are over twenty  references which means maybe this authors is not much of a contributor to the scene of quant and high frequency trading. I don’t the author would ever go down as a legend like Paul Wilmott or John Hull.

This is easily the best review on Amazon:

In detail: The first four chapters are pretty much useless to anybody I can think of, other than reporters and pointy headed panelist types who want to sound clever in cocktail conversations. Chapter five goes over some a standard bestiary of performance metrics. Chapter six is a very limited description of order types -again; something useful to a stuffed shirt over cocktail wieners: utterly useless, almost laughable to a practitioner. Chapters seven and eight has some weak stuff on "how to find signal" in financial noise. It's useful if you never heard of autocorrelation before, but it's not going to help you if you're in that sad state. A book on signal processing or econometrics might help you. There is also evidence that the author has not actually used some of the models and techniques she name drops here: for example, I've never heard of neural nets having the advantage of "significantly speeding up execution of the forecasting algorithm." Every neural net I've ever encountered sucked at speed compared to, say, regression or ARIMA. The section on tick data is weak. Tick data is certainly mentioned, and you'll know what it is at the end of the chapter, but the chapter doesn't actually tell you anything about "working with tick data." There's lots of tricks to ticks; none are covered here. Chapter 10 on market microstructure contains a section on the gamblers ruin which appears to be completely wrong. Either that, it's misprinted, or the rum I needed to get through this review is causing me to see things. It's probably not worth mentioning the equations are mislabeled in the text, but even in my liquored state, I noticed. Chapter 11 is sort of OK, though, for example, Joel Hasbrouck's chapter 11 on the same subject is much more informative. I also would have liked to have seen more and different stuff in there. I mean, what is the utility of including quotes from the Economist on Bayes theorem? I'd rather quotes from someone who knows what they're talking about, rather than quotes from some ding dong journalist, or perhaps some more information about market microstructure models. Chapter 12 on event arbitrage is good in that exists, and gives a rough outline of how it works. Event arb is awesome, because even schmucks like me can do it; I love event arb; nobody talks about it, but the author of this book actually did. Is this chapter useful to a practitioner? Nope. Again; good for the cocktail crowd and newspaper reporters: useless to anyone who wants to trade. Chapter 13 is on everyone's favorite fancy pants trading strategy, "stab art" (and, BTW physics is a hard science, not a "hard" science like it says in this book). "Statistical arbitrage" is a phrase which tends to cover a lot of different stuff; some of which is never discussed here: pairs trades, for example, is the standard textbook example; MIA. Triangle arb is also conflated with stat arb, which is silly and wrong: there is nothing statistical about triangle arb; triangle arb is just plain arbitrage. I guess there is some general hand wavy material which might give a hint to people looking for opportunities, but there is so much missing, it probably reads like greek to the uninitiated. Chapter 14 purports to be about portfolio management for HFT, though really, it's about classical portfolio management, which isn't so useful for HFT. HFT portfolio management is a genuine black art; a real chapter on it revealing some practitioner secrets (or even some decent academic references) would have been invaluable. This chapter also contains such bloopers as confounding Bayesian self-correction with genetic algorithms on page 209, which is sort of like a chef confusing an eggplant with a blender. It does contain an outline of the portfolio optimization technique used by the author, which I guess is vaguely sensible, but is rather ad-hoc and not particularly convincing, and has little to do with issues which arise with HFT portfolios. I take umbrage with chapter 15 on back testing. Back testing is hugely important in any kind of forecasting algorithm; waving your hands over the MAPE formula is pretty much useless. Nowhere is the sin of data mining given the attention it deserves: things like the bootstrap or establishing p-values for overfitting probabilities ... well, maybe I am expecting too much from a book which confuses eggplant with blender. Chapter 16 is supposed to be on implementation. FIX gets mentioned at least. So is C++, and, erm, Java. I do know of one firm which uses Java, but I know a lot more which use Matlab or Python (yes, even in HFT). A few concepts in software development and QA are mentioned in passing. I'm not sure who she's mentioning this for: any nerd who has slung some C knows what unit testing is. I'd rather a few paragraphs on issues with using time series databases. Chapter 17 (the liquor is getting me pretty hazy at this point) is on Risk management. She describes some stuff on using Pareto-Levy distributions to characterize tail risk. I know Taleb and company seem to recommend this, but I've honestly never heard of anyone trying to do it, because fitting Pareto-Levy distributions sucks. Probably some people do, but "I never hoyd of da bums." She describes some bootstrappy way of doing this, which I'm guessing is somewhat more useless than using the bootstrap to see if your dumb trading strategy has any legs to begin with. Trying to pin the tails on the Pareto distribution seems like a bad idea to me: I think of tail risk as consisting of things which you can't really model. The bits on "legal risk" and "operational risk" are good in that these words exist in the book, but bad in that they contain no actionable information: "talk to a lawyer" isn't really helpful to me. They also don't belong right before a section on stop loss orders, which is a really different kind of risk. The remaining chapters have turned into an alcoholic blur for me, but ch 18 "executing and monitoring" is worthless unless you didn't realize trading systems have to be executed and monitored, and at least chapter 19 finally mentions implementation shortfall and VWAP, which are kind of the harmonic oscillators of algorithmic trading at least. A lot of people would put these somewhere at the beginning of the book.

http://www.amazon.com/High-Frequency-Trading-Practical-Algorithmic-Strategies/dp/0470563761

 

New Hedge Fund Training Manual Book Released

Written by Administrator Wednesday, 26 January 2011 12:38

Richard Wilson recently interviewed over 20 hedge fund managers and experts and has placed those interview transcripts within his latest book, "The Hedge Fund Book: A Training Manual for Professionals and Capital Raising Executives"" This book was written using mostly interview transcripts because most professionals who want or need to learn more about hedge funds don't have the connections or time to schedule coffee meetings with 20 hedge fund managers and industry veteran. This book also contains over 30 free video modules created by Richard Wilson which supplement the text and explain certain topics in more detail. Pick up your copy today here: http://www.amazon.com/Hedge-Fund-Book-Professionals-Capital-Raising/dp/0470520639/ref=sr_1_1?s=books&ie=UTF8&qid=1292529246&sr=1-1 Hedge Fund Group http://HedgeFundGroup.org http://HedgeFundCertification.com p.s. This book is required for the Certified Hedge Fund Professional (CHP) Program which will be opening again to an additional 200 participants on January 15th, 2011 here: http://hedgefundcertification.com/Enrollment.html

 

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