Transcript How to prepare yourself for a Quants job in the financial

How to prepare yourself for a
Quants job in the financial
market?
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
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Strong knowledge of option pricing theory
(quantitative models for pricing and
hedging)
Strong software design and development
skills using C++
Mastery of advanced mathematics and
numerical analysis arising in financial
modeling (probability theory, stochastic
processes, numerical analysis)
General skills:
Analytic, quantitative and problem solving
skills; strong communication skills
Roles and responsibilities

Develop mathematical models for pricing,
hedging and risk management of derivative
securities.

Support of trading activities by explaining
model behavior, identifying risk sources in
portfolios, carrying out scenario analysis.

Design efficient numerical algorithms and
implement high performance computing
solutions – delivery to systems and
applications.
Relevant courses in our
MSc Programs
Financial Mathematics
MATH571 Mathematical Models of Financial Derivatives
[Fall, 07]
MATH572 Interest Rate Models
[Spring, 08]
MAFS524 Software Development with C++ for Quantitative
Finance
[Spring, 08]
MAFS525 Computational Methods for Pricing Structured
Financial Products
[Spring, 08]
MAFS523 Advanced Credit Risk Models
[Summer, 08]
Statistics courses
MAFS513 Quantitative Analysis of Financial Time Series
[Fall, 07]
MAFS511 Advanced Data Analysis with Statistical Programming
[Spring, 08]
MAFS522 Quantitative and Statistical Risk Analysis
[Summer, 08]
Foundation courses
MAFS501 Stochastic Calculus
[Fall, 07]
MAFS502 Advanced Probability and Statistics
[Fall, 07]
MAFS 501
Stochastic Calculus
[3-0-0:3]
Random walk models. Filtration.
Martingales. Brownian motions.
Diffusion processes. Forward and
backward Kolmogorov equations.
Ito’s calculus. Stochastic
differential equations. Stochastic
optimal control problems in
finance.
MAFS 502
Advanced Probability and
Statistics
[3-0-0:3]
Probability spaces, measurable
functions and distributions, conditional
probability, conditional expectations,
asymptotic theorems, stopping times,
martingales, Markov chains, Brownian
motion, sampling distributions,
sufficiency, statistical decision theory,
statistical inference, unbiased
estimation, method of maximum
likelihood.
MAFS 513
Quantitative Analysis of
Financial Time Series [3-0-0:3]
Analysis of asset returns:
autocorrelation, predictability and
prediction. Volatility models:
GARCH-type models, long range
dependence. High frequency data
analysis: transactions data,
duration. Markov switching and
threshold models. Multivariate
time series: cointegration models
and vector GARCH models.
MATH 571
Mathematical Models of
Financial Derivatives [3-0-0:3]
Black-Scholes-Merton framework,
dynamic hedging, replicating
portfolio. Martingale theory of
option pricing, risk neutral
measure. Exotic options: barrier
options, lookback options and
Asian options. Free boundary
value pricing models: American
options, reset options.
Upon completion of the program,
students are expected to achieve
the following intellectual abilities:
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A broad knowledge and understanding of
the financial products commonly traded in
the markets and various practical aspects
of risk management.
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Use of mathematical and statistical tools to
construct quantitative models in derivative
pricing, quantitative trading strategies, risk
management, and scenario simulation,
including appropriate solution methods and
interpretation of results.
To graduate from the MSc
program, each student is required
to complete 30 credits of which
 6
credits from the list of
foundation courses
 9 credits from the list of courses
in statistics
 9 credits from the list of courses
in financial mathematics
 6 credits as free electives*
Needs to maintain a graduation grade
point average of B grade or above.