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Financial Mathematics
Our aim is to introduce the fundamental mathematical and statistical concepts in Finance
and Investment Banking to students and anyone else who might be interested in pursuing a
degree course with an aspiration to find jobs in Finance sector.
We tried to keep the equations to minimum and explain the concepts as
much as possible. Numerical examples are provided wherever possible. Here we go:
Financial Mathematics is an application of mathematical methods to financial markets and risk management, to predict the behaviour
of the markets and suggest strategies for investment.
The mathematical finance is closely related to the financial economics. While the financial economics
defines the underlying financial structure/model (of a company), the mathematical finance helps
to extend these models to provide products based on the underlying equity or shares (of the company).
For example, a financial economist might study the fundamentals of a company to determine the share price of that
company. A financial mathematician might use that share price, among other information, to determine the value of the
complex derivative products based on that company's share.
Many quantitative analysis tools used in the financial industries are basically derived from the
advanced mathematical and statistical methods.
For example, stochastic calculus is the basis for
derivative pricing models. Value-at-Risk techniques to assess and manage market risk of portfolios
involve understanding of probability distribution functions and Monte Carlo simulations.
Follow the links given here to: understand the
stock price behaviour
and volatility;
learn Monte Carlo Techniques to simulate
stock price behaviour; understand what "options" are and learn why do we need them.
In the following links: learn advantages and limitations of
the Black-Scholes option pricing model; find out what put-call parity is;
estimate volatility using ARCH/GARCH models; and calculate Value-at-Risk of equity portfolios.
Mathematical Finance discipline is closely related to other disciplines such as
Econometrics,
Business Statistics and
Business Intelligence.
The difference is that these disciplines use a different set of
information techniques.
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