A piece of research writing of c. 15,000 words, which is preliminary to the intended MPhil or PhD degree, must be prepared.

This module introduces students to the working of the British parliament (both House of Commons and House of Lords). Uniquely it is jointly delivered with the...

The course will make you familiar with key concepts in modern quantitative macroeconomics and give a thorough understanding of up-to-date research in a few...

The course will make you familiar with key concepts in modern quantitative macroeconomics and give a thorough understanding of up-to-date research in a few selected topics. Particular attention will be paid to using economic theory, specifically equilibrium models with heterogeneous agents, to interpret data. The course will be relevant to students studying economics at a postgraduate level, as well as those interested in policy research involving quantitative economic modeling.

Prerequisite: ECON0066: Macroeconomics

COMPUTATIONAL METHODS|FINANCIAL ENGINEERING|PROGRAMMING IN C++|PYTHON

Aims:

An introduction to programming in two popular languages of use in the financial markets, and mathematical modelling.

Learning outcomes:

On successful...

Aims:

An introduction to programming in two popular languages of use in the financial markets, and mathematical modelling.Learning outcomes:

On successful completion of the module, a student will be able to:

Apply numerical schemes to solve pricing problems.
	Demonstrate programming proficiency in basic C++ and Python to solve practical problems in Mathematical Finance and modelling in medicine and healthcare.
Content:

Success in mathematical finance requires confidence and expertise in applying numerical analysis and programming to solve a wide range of pricing and risk management problems. This module presents programming in C++and Python. C++ continues to retain its ‘sexy’ status in the financial markets and is arguably the most popular language of use in Quantitative Finance. Python is rapidly becoming the standard in scientific computing, receiving much excitement about the application of Python to mathematical finance; its appeal continues to grow in both academia and industry. It is simple to use and free to download, with a growing amount of add-on modules. It is particularly easy to interface with C++.

C++: Data types; input/output; file management; control of flow and decision making. Functions; headers and source files. Arrays and strings. Pointers; dynamic memory allocation. Recursion. Objects and classes; operator overloading; polymorphism; inheritance.
	Python: Introduction to some of the powerful libraries in Python.
	Scientific manipulations (SciPy); data structures (NumPy); graphics (Matplotlib); data analysis (Pandas).
	Numerics and data analysis.
Requisites:

To be eligible to select this module as optional or elective, a student must: (1) be registered on a programme and year of study for which it is a formally available; (2) have taken either Financial Engineering (COMP0048) or Asset Pricing in Continuous Time (MATHGF05) in Term 1.