。。

de_bluestorm

同意楼上，楼主对自身不是做quant的料这个判断还是很准确的。。

Jessie_Q

cheesechan 发表于 2018-4-7 18:10
那你還是不要去做要PhD的quantitative advisory或者风控了.

為啥? 那是因為你到現在還根本不知道, quant  ...

您的意思是需要PhD的quant或者风控 要的research来自理工科？

而如果收master的quant advisory或者quant risk 根本也无需金融/计量PhD学位？

谢谢答主

Jessie_Q

de_bluestorm 发表于 2018-4-8 03:12
同意楼上，楼主对自身不是做quant的料这个判断还是很准确的。。

的确如此

但是risk建模 risk advisory还是可行的

cheesechan

Jessie_Q 发表于 2018-4-8 06:56
您的意思是需要PhD的quant或者风控 要的research来自理工科？

而如果收master的quant advisory或者quant ...

Financial Engineering is itself more close to applied mathematics, than finance. That's why many 1st generation Quant are from physics.

I won't say that finance PhD, finance departments are absent in this field (quantitative finance) since it is easy to find tons of counter-examples; but one things is sure is financial engineering is just one of the many research fields in finance research. Bear in mind that when people are saying that quantitative backgrounds are useful in finance research, this doesn't necessarily means that they are conduct research in financial engineering.

The most common PhD in this field is those from department of Computer Science, Mathematics, Physics, and Statistics, in no particular order.

For econometric, I won't say they are useless in financial engineering (again, this is not true), but this is again clearly not their first or even second purpose. The most directly applicable empirical / data analytics skill for financial engineering nowadays is on the machine learning side, where department of computer science, and then department of statistics are the best place for that.


It is a bit harsh, but I think that is fair to say that, it is expected for a MFE graduate to be aware of the mathematical nature of the field if he/she really want to join this field no matter in industry or academic, especially when he/she is considering a PhD. Those who didn't, is clearly not well prepared, and likely o be better off to consider some other slightly less quantitative roles.

Jessie_Q

cheesechan 发表于 2018-4-8 07:22
Financial Engineering is itself more close to applied mathematics, than finance. That's why many 1s ...

Thank you for your advice.

I agree with you. My math background is not strong so I know I cannot do much quantitative jobs. Thus, my career goal is risk analytics and risk advisory, and they need math and computer skills but not that much.

I consider PhD in finance or econometrics can train risk modeling and financial analytics skills, which may be used in working. That is why I have the plan of pursing PhD.

My question is whether master is enough for me to do less quantitative jobs compared with quants who do high frequency trading, write algorithm and do similar quantitative jobs.

Jessie_Q

cheesechan 发表于 2018-4-8 07:22
Financial Engineering is itself more close to applied mathematics, than finance. That's why many 1s ...

My point is whether master degree is enough to pursue the positions I want.

What is your opinion? Thank you.

redsa12

樓主，如果你一心奔著業界去，你是申請不到任何decent的finance PhD的。那怕你GPA 4.0、GRE/GMAT接近滿分、數學課也修得完美、還有大牛強推(which is impossible，因為大牛只會為有向學術展現一定程度commitment的申請者寫強推)，只要你在SOP裡提到你畢業要去業界，就不會有任何認真經營的finance PhD收你，因為finance PhD的目的就是要培養學者。如果學生畢業了去業界，教授們基本上都是會認定這個人是loser，是fail the market才不得已去業界的。

Jessie_Q

redsa12 发表于 2018-4-8 12:13
樓主，如果你一心奔著業界去，你是申請不到任何decent的finance PhD的。那怕你GPA 4.0、GRE/GMAT接近滿分、 ...

当然不会体现在SOP里 也不会对推荐人讲述就业意向

幸运星星

你本科背景如何？同样的 quant advisory， 具体的工作要求其实差别很大，楼主背景应可胜任大多数这样的岗位，但能否有OFFER却主要看人脉，靠内推。海投则TECH背景显得不足。
读了博士后找工作会好很多，但问题是申计量经济要求数学背景要强，申统计更难。申金融有可能，但最好多做些科研。

de_bluestorm

Jessie_Q 发表于 2018-4-8 12:35
当然不会体现在SOP里 也不会对推荐人讲述就业意向

cheating？？？