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