在Quantnet上看到了一篇关于AlgoTrading的帖子

RonHe 发表于 2012-7-29 13:25
是不是做短线可以把市场数据当信号来理解和处理啊？
求问

Pattern recognition那一套。。。跟技术分析很像

hangli2 发表于 2012-8-3 20:32
Pattern recognition那一套。。。跟技术分析很像

为什么总感觉技术分析在金融里是个贬义词。。

RonHe 发表于 2012-8-3 20:51
为什么总感觉技术分析在金融里是个贬义词。。

不符合传说中的efficient market hypothesis的说法都会被芝加哥学派斥为异端，当然大家都知道那只不过是个hypothesis~哈哈

技术分析也算是应用统计学性质来预测了，只是看着太过粗糙了

oldfishdk 发表于 2012-7-29 13:11
我觉得大家都把Algo Trading等同于HFT了吧,但HFT应该只是一个Algo Trading的子类吧.

或说我看到过招人确 ...

确实，AlgoTrading的持仓时间有些是比较长的，写着写着就混淆了

传说RenTech是不招有华尔街工作经验的人的。。。。

哥大即将有了。。看我的新帖。。

literally, algo trading is a broad term. but when street talks about it, it usually mean algorithm market making. Most if not all of them are high frequency. Major players include BB, broker house and trading firms. It is not investment but short term trading/order execution. So low level technology/algorithm are more imporatnt than financial knowledge. That's why top firms like HRT only hire from hard science (mostly CS/EE) major with no financial market experience.

When we talk about quant fund with market neutral strategy like stats arb, the term quantiative trading/quantitative investment is more appropriate. Although some of them are also high frequency, the model behind is more important. So math/stats/econ/ people are prefered to CS/EE

bon1net 发表于 2012-10-11 21:40
literally, algo trading is a broad term. but when street talks about it, it usually mean algorithm m ...

Your view is quite informative. Thanks.

bon1net 发表于 2012-10-11 21:40
literally, algo trading is a broad term. but when street talks about it, it usually mean algorithm m ...

很有收获，希望仁兄有机会能针对这个开个帖子，想了解的人会很多

bon1net 发表于 2012-10-11 21:40
literally, algo trading is a broad term. but when street talks about it, it usually mean algorithm m ...

second this

1. Algo trading != HFT, Quite different
2. I don't think one guy need to know all of Unix internals, C, FPGA, Market Microstructure, Signal processing, Econometrics, Low level networking as well as FIX, Stats and data mining, Probability at a deep level, Game theory, AI.
   Usually firms have dedicated developers to do FPFA/Unix/Low lever networking, FIX... these are skill sets for developers/engineerings, and quants knows Market Microstructure/Sig Proc/Stat/Data Mining.... etc. It is not hard to find a phd with such knowledge, in my opinion, a Stat/IE/ecom phd or EE/CS phd on ML/Stochastic control, etc.
3. MFE programs do not do a good job in providing courses for HFT or quant trading strategies (NYU does not do a good job I think...even don't have machine learning class on the list, while Courant CS has a very good ML faculty...), that is why not many MFE grads went into HFT/quant trading strategies (unless he/she had a phd) business. I think the main reason is, no one wants to teach other people how to make money...