How does quant/alpha quant find ideas?

[KevinLuo]

I am a senior college student and am currently working as a Alpha quant intern in a small fund. What recently concerning me is that I find myself lost when seeking for new ideas for Alpha factor design. My direct leader is quite friendly. He regularly gives me some ideas he comes up with I also seek for some ideas from brokers' reports and journal articles. The internship is going just fine.

However, I am increasingly worried about the long-term career problem. I feels that there is no specific methodology to follow. For instane, the first alpha factor I tried to write is a statistic with intraday minute return(simple and naive). After finishing the first one, I moved on to a totally different method following the idea given by my advisor. I feel that the work of quant especially the alpha quant is no similar to any other work in the world. There does not exist a framework to follow and the alpha factor I find is surely to lose efficiency in few months or years. I guess I need to form my own "trading system or research system" and alpha quant is not actually a sustainable job.

Everything above is just my naive thinking. After all, I am new to this field and this thinking might be a result of lacking experience and capability. Can anyone give some sugguestion on whatever about seeking for ideas or career path or anything related. I really appreciate your help. Thanks!

 

[khoatran]

Hi Kevin,
Well I actually had the same question. I've had internships with an investment fund and an advisory firm where my tasks were to do alpha research. In my case, my managers usually provide me with some datasets available and some initial research papers to read and start thinking about, and that's it. Most of the time I was left alone to come up with something by myself. And from my discussions with friends and people in the industry, this is mainly what alpha research is all about, banging your head against the wall and hoping it to one day break There is no methodology to reach a certain idea. And believe me if there were, someone would've had exploited it, rendering it again to no methodology Academic research can be one source for you to start out. Don't read it too narrowly, sometimes you may find ideas used in almost non-relevant fields. The weakness of academic research is that Professors don't really care about practical aspects, but more about interesting concepts, hence the majority of academic research will be useless and not replicable. Aside from that, it's all about trial and error, and original thinking. Most people get ideas from conferences and colleagues, basically "inspired" by someone else. This is the reason why places like RenTech guard their secret strictly. You're be amazed by how people can get "inspired" from things that seem trivial at first. Alpha research is original research. and like doing a PhD, you are confused all the time trying to find some solutions that might not even exist lol. There is, however, statistical methodologies that you can learn to test and make sure your idea works when implemented. That being said, yes alpha quant, for most cases, is not a sustainable job as you said. It highly depends on your team and managers. Some managers without a quantitative background will likely grow impatient and actually blame you for providing no actual result, which is likely to be the case as this is a highly experimental endeavor. So my 2 cent advice is, pick your team carefully if you are gonna go down this career path.

 

[khoatran]

Well, on second thought I think there are things we can do to better our chances.
1) Have strong fundamentals (math, stats, etc.).
2) Keep up with new research. I should qualify my above statement that most academic research is not useful right out of the box. They always require adjustments to work. But you should keep up with new methods. Sometimes ideas can come from irrelevant fields. But also don't get hyped up. Techniques come and go. Some will work, some won't, and will be forgotten then decades later somebody will revisit it and make it work. But strong fundamentals will help you to understand what's worthy and what's not.
3) Improve your programming and implementation. A simple bug will render your fancy strategy useless. And some strategies will only work with advanced optimization.
4) Study new financial instruments. They can help you shift your perspectives. E.g. options can open the world of volatility for you, and securitized products can give you an understanding of correlations.