I have access to some tick data and Bloomberg data. Outside of data mining and hoping to find an economic rationale after the fact, what do you usually do to generate ideas before you look at the data? I'm having trouble thinking of anything outside of arbitrage, trading pairs of similar assets, data mining correlated assets, data mining stuff that mean reverts, and data mining "signals" from tick data. Maybe I'm just overthinking and data mining actually works. What are some general strategies that firms actually employ as opposed to strategies fit for the personal trader?

I've heard about stuff on momentum (last 11 months skip a month) and the typical "factor" models like small - big, liqudity, but that seems more suited for like mutual funds.

I guess another question is, do firms actually data mine a lot? I'm trying to get a job so I want to do something that is relevant/practical that I can talk about in an interview as opposed to just "I took a stats class or watched a video on ML".

Should I be digging into random research papers? I mean I have ideas in general, but I only have access to some tick data and Bloomberg - which is pretty limited since it only offers closing values which can be a different timestamp for different products/exchanges.


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    $\begingroup$ It's an extremely difficult question to answer because, if anyone does have any good ideas, they're not going to divulge them anyway. My advice would be to get a job where you work in the field ( if you haven't in the past ) and, depending on the job, you might get some good experience and some good ideas. But, even then, a lot of places will make you sign an NDA and make it very difficult to leave etc. Read the paperback "head of research" if you want to get a better idea of what the field can be like. $\endgroup$ – mark leeds Jun 3 '20 at 3:34
  • $\begingroup$ Thanks. Obviously no on will disclose any good ideas but was curious if there are any systematic approaches to idea generation. $\endgroup$ – confused Jun 24 '20 at 2:17
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    $\begingroup$ @confused: The closest thing I've seen to disclosure in quant is ernest chan's books. I forget the names but, if you google on amazon, they'll come up. I only read the first one but I remember being pretty surprised at the level of open-ness. $\endgroup$ – mark leeds Jun 24 '20 at 4:35
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    $\begingroup$ sounds good. the last part you talk about is called "market-microstructure". a lot of work in that is currently done by econo-physicists. I don't know much about it but bouchard and doyne farmer and lehalle are some of the big names in that. In fact, lehalle is on quant.stackexchange and seems like a very generous person as far as providing relevant references and useful info. $\endgroup$ – mark leeds Jun 30 '20 at 5:19
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    $\begingroup$ The three people I mentioned are prolific. tons of publications and, not their fault, but it can be somewhat difficult to get one's head around all of it. you may want to get bouchard's latest text. I forget title but you'll find it on amazon. ticks, quotes, trades or something like that. $\endgroup$ – mark leeds Jul 1 '20 at 16:34

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