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While it looks like an interesting book, there's no content here.
Also stuff like this only works in simulations, the actual trading fees make this totally unpractical.
Liquidity providers get paid to trade on most exchanges (maker-taker model).

ETA: That's not to say this is a good book. It's not. I'd recommend Vidyamurthy's Pairs Trading and Harris's Trading and Exchanges, but there really aren't many good books on this style of trading--anyone who knows how to do it well has no incentive to write a book on it.

Not if you're a giant broker with servers co-located in the same DC with the actual exchange.

The rest of us can go pound sand though.

Giant broker = small privately held company?

The biggest players in this game are not massive NYC investment banks.

Well.. the biggest player in the game is Goldman.

But, you're right in that there are a bunch of small hedge funds that are operating in this market, too. Still doesn't make it very accessible for those of us without a boatload of money up front to get access.

http://www.nasdaqtrader.com/trader.aspx?ID=topliquidity

GS isn't even top-5 on NASDAQ.

Professional trading was never cheap. The barrier to entry for becoming a high-frequency trading firm is much, much lower than becoming a NYSE specialist was a decade ago. You could co-locate there for a few million dollars, which is small money all things considered.

Top-5 in LIQUIDITY PROVIDERS, not necessarily the same as in programatiC/algo trading. Goldman tops the list and anyone that's traded on a prop desk knows how much influence they have on the domestic equities market:

http://subprint.com/u/28

I haven't read it, but the reviews it's getting seem pretty negative. The author is active on the related linkedin groups but doesn't seem to be willing to respond to the critical reviews, which completely puts me off from buying it.
i just did my taxes and theres no way i would punish myself that much to go through with high frequency trading
Is there anything finance-specific in these kinds of books that I'd learn from reading them, or is it just data mining / statistical inference applied to stock data in the obvious way?