Provides conceptual knowledge on quantitative finance and a theoretical background prior to the application of Python
Offers a hands-on experience of implementing and using Python
Focuses on advanced financial analysis in an academic yet descriptive manner

Autorentext

Mauricio Garita is an academic, a writer and an economist that has centered his career in the combination of finance and economics with the use of Python. He obtained his first PhD in Political Science and Sociology from the Universidad Pontificia de Salamanca, Spain with a thesis centered on game theory and economic development. Prior to obtaining his PhD, he completed a Master of Science from Manchester Business School, UK and a secondary Master's in Asset Management from the Instituto de Estudios Bursátiles de la Universidad Complutense, Spain.

As an academic, his research is focused on financial issues, economics and competitiveness in Latin America with a special focus in Central America. He has written books and articles on topics such as business in Latin America, the economic impact of the Civil War in Guatemala, the fiscal impact of reforms in Latin America and the impact of the financial crisis in Central America. As a professor he centers his coursesin the areas of economics, project valuation and financial analysis.

During his professional career he has worked with organizations such as the World Bank, the Central American Institute of Fiscal Studies, the Secretariat for Central America Economic Integration, Transparency International and on financial consulting. Currently he works at Universidad Francisco Marroquin as a director of the master's in finance program at the university business school. Before he worked at the finance department at the Universidad del Valle de Guatemala where he assisted in both the creation of the Master's in Advanced Finance and a collaboration on with the Advanced Risk Portfolio Management (ARPM) program.

Inhalt

1. How to use python?.- 2. Using data structures in Python.- 3. Using Data in Python.- 4. Descriptive statistics using Python.- 5. Statistical approach to multiple variables.- 6. Comparing stocks between companies.- 7. Porfolio and Risk.- 8. Value at Risk.