Financial Engineering is a multidisciplinary field that entails the application of an engineering methodology and approach to the financial management of projects, businesses and other forms of financial investments. Financial engineering is primarily quantitative, involving data analysis and the application of statistical techniques, in the evaluation of risk and economic impact of financial decisions. This is against the backdrop of the enormous volume of data available in financial markets, and the usefulness of statisticsl and quantitative techniques in evaluating investment choices and making financial decisions.

Papers submitted for consideration in the Statistics and Data analysis for Financial Engineering Section cover topics on the application of probability distributions and advanced statistical techniques such as regression, multivariate models, factor models, Monte-Carlo simulations, Bayesian statistics and Co-integration. Papers that pose theoretical arguments and exemplify practical applications are welcome.

The goal of this section is to promote intellectual contributions that integrate, utilize and statistically analyse data and information obtained from different fields that are relevant to financial engineering. Readers of this section will be exposed to the wide range of contemporary quantitative techniques commonly used in risk analysis and investment decision making, and gain an understanding of thier applications to the empirical analysis of financial data.