国际金融工程师协会(IAFE)推荐的金融工程师必备知识清单

Resources : FE Core Body of Knowledge

Below is a suggested core body of knowledge for a financial engineering course.

For each suggested course, we have indicated the results of a survey of recruiters who attend the annual IAFE Career Fair. We asked these recruiters to rank as High, Medium, or Low how useful they would find that course for a newly hired Masters student to have studied before beginning work. While the resulting percentages are not the result of a scientifically designed survey, we believe that they will be useful as a rough indicator of industry sentiment. The excel sheet is also linked below. 

FE Core Body of Knowledge

Where a course title may not be clear, we've provided a few sample topics to the right. 

High Medium Low Sample topics

Mathematical tools 

M1 Stochastic calculus 55 35 10 Brownian motion, Ito calculus, Girsanov's theorem

M2 PDEs applied to finance 42 46 12 

M3 Numerical methods 74 26 0 

M4 Basic fixed income math 64 28 8 Discount factors, bootstrapping a discount curve, duration

Statistical tools 

S1 Data analysis / Statistical inference 68 29 3 

S2 Time series analysis 59 37 4 

S3 Regression analysis 68 29 3 

Economic / financial tools 

E1 Microeconomics 32 39 29 

E2 Macroeconomics 32 39 29 

E3 Econometrics 41 45 14 

E4 Corporate finance 33 26 41 

E5 Game theory / Auction theory 32 39 29 

E6 Real options 45 22 33 

Computational tools 

C1 Object-oriented programming applied to finance 64 32 4 

C2 Monte Carlo simulation 71 25 4 

C3 Optimization 71 29 0 

C4 Finite difference solutions for PDEs / Dynamic programming 33 56 11 

Derivative securities models 

D1 Basic overview of derivatives models 72 28 0 Risk-neutral pricing, Black-Scholes formula, Greeks

D2 Advanced overview of derivatives models 50 46 4 Local volatility models, stochastic volatility models, jump diffusion models

D3 Interest rate option models 61 25 14 Heath-Jarrow-Morton, LIBOR market model

D4 Credit models 57 22 21 

D5 Mortgage-backed & asset-backed models 43 21 36 

D6 Energy models & weather derivatives 25 29 46 

D7 FX models 43 32 25 

D8 Equity models 62 27 11 

D9 Convertible bond & hybrid models 43 39 18 

Investments & trading 

T1 Basic capital markets & portfolio theory 50 32 18 Efficient frontier, CAPM, arbitrage pricing model

T2 Advanced capital markets and portfolio theory 36 50 14 Black-Litterman, dynamic asset models

T3 Statistical arbitrage 57 32 11 

T4 Market microstructure / algorithmic trading /optimal execution 56 26 18 

T5 Behavioral finance 25 43 32 

Institutional background 

I1 Risk management 64 32 4 

I2 Structuring / Financial engineering 54 43 3 

I3 Tax & accounting aspects of derivatives 14 22 64

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