Onsite or via live stream

*Intensive onsite training on data science for finance, quantitative risk modeling and portfolio construction
New York, August 10 - 15 2020*

*The same program as the Quant Bootcamp, delivered in one single online course at your own pace, and enhanced by practice sessions in the Lab*

*In-depth, master-level online program modern quantitative finance in 4 core courses, with emphasis on data science*

*Short math/coding courses to prepare for the Quant Bootcamp, the Quant Core, or the Quant Marathon*

# Body of Knowledge

#### Financial Engineering for Investment

The module "Financial Engineering for Investment" covers valuation across instruments and asset classes:

- the standard financial engineering materials on risk-neutral valuation for derivatives (Black-Scholes, martingales, etc.)

- non-linear actuarial pricing (distortion measures, risk premium arguments, etc.)

- company/deal valuation, typically more tied to the investment banking and strategic consulting professions (discounted cash flows, comparable analysis, etc.).

This module also covers the connections between valuation, instrument-specific sensitivities (the "Greeks") and the different risk factors in the market.

Finally, this module covers the techniques (Monte Carlo full repricing, analytical approximations, etc.) to model the value of the different instruments at the future investment horizon, in addition to their present value.

- the standard financial engineering materials on risk-neutral valuation for derivatives (Black-Scholes, martingales, etc.)

- non-linear actuarial pricing (distortion measures, risk premium arguments, etc.)

- company/deal valuation, typically more tied to the investment banking and strategic consulting professions (discounted cash flows, comparable analysis, etc.).

This module also covers the connections between valuation, instrument-specific sensitivities (the "Greeks") and the different risk factors in the market.

Finally, this module covers the techniques (Monte Carlo full repricing, analytical approximations, etc.) to model the value of the different instruments at the future investment horizon, in addition to their present value.

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