International Association of Financial Engineers

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