1.
The Bureau of Investigative Journalism이 HFT와 관련한 몇 기사를 실었네요.
Robot wars: How high frequency trading changed global markets
The A to Z of high frequency trading
그중 눈에 들어오는 기사가 인포그래픽입니다. Infographic: Trading at the speed of light에 실린 이미지입니다.
2.
또다른 글을 보고서입니다. Casey Research가 HFT전문가와 인터뷰한 글입니다.
Interview with a High-Frequency Trading Expert
이중 HFT전략에 대한 부분입니다.
TCR: So what are some other ways that HFT shops make money?
GARRETT: There are many different strategies. Some take advantage of rebates, which are financial incentives the exchanges offer for being a market-maker.
Here’s where I should clarify that not all HFTs are bad. I’m very sour on HFTs in general because I’ve seen the havoc they can wreak, but there are good ones. Market-makers increase liquidity and make the markets more efficient. That’s great. There are good HFTs.
Some HFTs try to read and process the news quicker than everyone else. There are algorithms designed to read newspaper headlines, search for key words and execute trades based on what they read, all in seconds or less. I wouldn’t say this is particularly nefarious, because the HFTs in this case are just doing what humans do ? trading the news ? but faster.
That said, it can create problems. Awhile back, there was an errant news release about Boeing going bankrupt, and the HFTs started selling because they saw the keywords “bankruptcy” and “Boeing.” The story turned out to be an error.
In that situation, most human traders would pause and think, “Wait a minute, I’ve never heard a thing about Boeing going bankrupt. What’s going on here?” But the computers don’t think. They just execute their instructions, and in this case, it caused a crash.
Then there are the manipulative algorithms, the ones that prey on other investors.
TCR: Can you give us an example?
GARRETT: Sure. Many HFTs will make near-simultaneous trades on different exchanges and profit because of the delay in one of the exchanges. An example will help me explain: let’s use the NASDAQ and EDGE exchanges, and say that ABC stock is trading at $1.00.
The HFT will send a bunch of quotes (offers) to NASDAQ and EDGE, trying to sell ABC stock at $1.01. Once the NASDAQ order is accepted, the HFT can simultaneously cancel the $1.01 sell order on the EDGE exchange and replace it with a buy order at the original price of $1.00. EDGE immediately accepts that $1.00 order, because its system has not caught up to the new price of $1.01, and the HFT’s net position becomes zero.
This is possible because of latency, which is jargon for delay in the system. The net result is, the HFT captures a $0.01 arbitrage.
By scalping this tiny amount from many trades, the profits add up quickly.
A second example: HFTs can model other traders’ behavior. When someone trades through Scottrade or Interactive Brokers, their order has a unique number attached to it ? the same number every time a client places an order. This number is bundled with all relevant trade information (time, price, etc.) and sold as an encrypted “enhanced data feed.” An HFT can then use those past results to predict the trader’s behavior.
전략의 출발은 마켓데이타에서 찾고 있습니다. 트레이들의 매매패턴을 예측하기 위하기 위한 (to predict the trader’s behavior) 출발도 데이타입니다.
TCR: So HFTs try to predict what you’re going to do before you do it. Do the brokers admit to selling this information? Can traders opt out?
GARRETT: This data is standard and available to anyone who wants to buy it, so it’s not that HFTs are purchasing illegal information. But the data set is huge and is only of practical use to players with very fast and powerful computers ? meaning HFTs. And yes, most brokers I have encountered will allow you to opt out of having your unique number attached to your information.
To be clear, I’m not saying HFTs track your individual account and literally jump in front of you right before you trade. But they do use this information on the aggregate to model traders’ behavior. So an HFT could have a very good idea of when traders on, say, E*TRADE’s book will enter into a certain transaction.
