新香港六合彩开奖结果

This module will provide you with the fundamental analytical skills for finance. The module will comprise three main building blocks: basic econometrics, statistics and probabilistic theory and introduction to machine learning in finance. In the first part of the module, you will deal with the basic principles of mathematics and statistics for econometric analysis such as random variables, univariate and multivariate discrete and continuous distributions, expectations and moments, hypotheses testing, estimation and properties of estimators, and time series. You will then learn the basics of finance, starting with key definitions and finishing with: no-arbitrage conditions, bond pricing, and derivatives to the standard models such as CAPM and CCAPM. The third and final part of the module will deal with probability theory and stochastic calculus. Topics will include measures theory, an introduction to probability theory and its applications, diffusions, Markov processes and martingales, introduction to stochastic integration, and stochastic differential equations. The module aims to build your basic knowledge in order for you to critically address and use standard financial methods and terminologies of the day-to-day activity in financial markets, and to set the stage for further analysis of cutting-edge research in financial modelling.

Learning Outcomes

• Gain competency in basic econometrics, statistics and probabilistic theory, and introduction to machine learning algorithms in financial analysis
• Have a solid understanding of key definitions in finance
• Have practical skills to assess bond pricing, risk and portfolio management, as they relate to the standard models of CAPM and CCAPM
• Gain understanding of basic probability theory and stochastic processes
• Have knowledge of machine learning algorithms with applications in financial analysis
• Have the ability to implement the above techniques to address empirical problems in finance, including the ability to code in Python
• Gain critical understanding of standard financial methods and ability to interpret day-to-day financial market activity

Reading List:

• M. Lopez De Prado: 鈥�Advances in Financial Machine Learning鈥�,听Wiley 2018
• T. Hastie, R. Tibshirani, J Friedman: 鈥淭he elements of statistical learning鈥�, Springer 2009