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個人不太看好fintech as a master on the technical side, 覺得這類program還不算well-established, 不夠穩.
和Financial Engineering的master相比, Fintech的往往更重視machine learning, text analytics, big data (in finance), 還有cryptocurrency, 和algo strategies and/or robot advisory.
但現在不少MFE都加了ML和NLP的課, 而big data呢? 其實真要玩到Hadoop/Spark之類的岡很可能都是專心搞data science & engineering, 那不如直接找讀DS/CS的好了...
Cryptocurrency這玩意都不知搞不搞得成, 要是講algo trading, robot advisory這類的, 本來MFE倒是不多有quantitative trading / asset management的課.
技術上來講, FinTech master的定位似乎是不講stochastic calculus, option pricing那堆Q quant的MFE, 把時間省下來搞data analytics and AI之類. 不排除以後MFE會有類似的stream/speicalization.
但現在有開設fintech的master的多半是business school的, 個人估計fntech master很大可能會變成business school版(偏軟)的technology with application in finance, 每樣技術講一點但不會深入 (因為用的的technology太大堆, 要真深入講就要cover from math to stat to cs to ......), 而集中講應用和對industry 的impact (e.g. automation)
舉個例像UCB這個IEOR的:
Required Technical Courses
INDENG 240: Optimization Analytics
INDENG 241: Risk Modeling, Simulation and Data Analysis
INDENG 242: Applications in Data Analysis
And two from:
IND ENG 221 Introduction to Financial Engineering
IND ENG 222 Financial Engineering Systems I
IND ENG 224 Portfolio and Risk Analytics
讀這堆和讀FE的有甚麼分別? 221, 222, 223還是跑不掉stochastic calculus, financial engineering, option pricing......
但Haas MFE能一直保著自家1st tier MFE的地位, 靠的可不主要是教的內容, 而是那個first comer advantage和強力的director and career service (UCB MFE是1st tier MFE中最偏business/finance/soft/experienced candidate的)
要不是有這個, 光光是那個location就坑死人了.....
P.S.
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