Module 6: Advanced Electives

Algorithmic Trading

The use of algorithms has become an important element of modern-day financial markets, used by both the buy side and the sell side. This elective will look into the techniques used by professionals who work within this area.

  • What is Algorithmic Trading
  • Preparing data; Back testing, analysing results and optimisation
  • Build your own algorithm
  • Alternative approaches: Pairs trading; Options; New Analytics
  • A career in Algorithmic trading

Who is it for: Trading, Asset Management, Hedge Fund professionals

Advanced Computational Methods

One key skill for anybody who works within quantitative finance is how to use technology to solve complex mathematical problems.
This elective will look into advanced numerical techniques for solving and implementing the math in an efficient and succinct manner, ensuring that the right techniques are used for the right problems.

  • Finite Difference Methods (algebraic approach) and application to BVP
  • Root finding
  • Interpolation
  • Numerical Integration

Who is it for: IT, quant analytics, derivatives, valuation, actuarial, model validation professionals

Advanced Risk Management

Post-global financial crisis, risk has become a key issue in every financial organization. Organizations need good measures and techniques to manage risk and to be able to show this to the regulators. This elective will look at techniques used within industry to manage risk and discuss how these are useful for an organisation and how they satisfy the regulatory landscape.

  • Risk Management: A Helicopter View
  • Multivariate Risk Models – Risk mapping, Copulas, Correlation and Covariance and PCA
  • Portfolio VAR
  • Measuring Risk Using Extreme Value Theory
  • The Basel Accords

Who is it for: Risk management, trading, fund management professionals

Advanced Volatility Modeling

Volatility and being able to model volatility is a key element to any quant model. This elective will look into the common techniques used to model volatility throughout the industry. It will provide the mathematics and numerical methods for solving problems in stochastic volatility.

  • Fourier Transforms
  • Functions of a Complex Variable
  • Stochastic Volatility
  • Jump Diffusion

Who is it for: Derivatives, structuring, trading, valuations, actuarial, model validation professionals

Advanced Portfolio Management

As quantitative finance becomes more important in today’s financial markets, many buy-side firms are using quantitative techniques to improve their returns and better manage their client capital. This elective will look into the latest techniques used by the buy side in order to achieve these goals.

  • Perform a dynamic portfolio optimisation, using stochastic control
  • Combine views with market data using filtering to determine the necessary parameters
  • Understand the importance of behavioural biases and be able to address them
  • Understand the implementation issues
  • Develop new insights into portfolio risk management

Who is it for: Trading, fund management, asset management professionals

Counterparty Credit Risk Modeling

Post-global financial crisis, counterparty credit risk and other related risks have become much more pronounced and need to be taken into account during the pricing and modeling stages. This elective will go through all the risks associated with the counterparty and how they are included in any modeling frameworks.

  • Credit Risk to Credit Derivatives
  • Counterparty Credit Risk: CVA, DVA, FVA
  • Interest Rates for Counterparty Risk – Dynamic Models and Modeling
  • Interest Rate Swap CVA and implementation of dynamic model

Who is it for: Risk management, structuring, valuations, actuarial, model validation professionals

Behavioural Finance for Quants

Behavioural finance and how human psychology affects our perception of the world, impacts our quantitative models and drives our financial decisions. This elective will equip delegates with tools to identify the key psychological pitfalls, use their mathematical skills to address these pitfalls and build better financial models.

  • System 1 Vs System 2
  • Behavioural Biases; Heuristic processes; Framing effects and Group processes
  • Loss aversion Vs Risk aversion; Loss aversion; SP/A theory
  • Linearity and Nonlinearity
  • Game theory

Who is it for: Trading, Fund Management, Asset Management professionals

Data Analytics with Python

Data and data analysis has become a key tool in any quants toolbox. In this elective you will learn how to use Python and Python libraries to analyse financial data and organise it in ways that allow you to use the data in a meaningful and productive way to make decisions.

  • Python Idioms and Data Structures
  • Using NumPy for Numerical Analysis
  • Using Pandas for Financial Time Series Analysis
  • Financial Data Visualization for Static and Streaming Data

Who is it for: IT, Quant Analytics, Valuation, Actuarial, Model Validation professionals

Python Applications

Python has become an important modeling tool and programing language within the industry. This elective will extend the material discussed in the primer which introduced the Python environment using enthought canopy, as well as much of the basic syntax and structures.

  • Numerical Analysis - fundamental and important techniques applied to finance
  • File manipulation and working with data
  • Functions - Further development of user defined functions as well as the powerful libraries for probability and statistics

Who is it for: IT, quant analytics, derivatives, valuation, trading, asset management professionals