Overall objectives:

1 - Understanding basic finance concepts
2 - Obtaining skills in using quantitative methods to address financial problems
3 - Creating basic programming skills that allow the implementation of quantitative methods
4 - Promoting writing and structuring rules of academic documents

Syllabus:

1 - Financial Modelling and Spreadsheet Essentials
1.1 - Introduction to financial modelling.
1.2 - Spreadsheet essentials: reference functions, financial functions and data tables
2 - Measuring risk
2.1 - Estimating betas with regression analysis (using daily, weekly, and monthly data)
2.2 - Testing market efficiency (with regression analysis, with pivot tables)
2.3 - Spreadsheet features: recording and editing macros
3 - Portfolio optimization
3.1 - Mean-variance portfolio selection
3.2 - Bond portfolio selection
3.3 - Term structure estimation
3.4 - Capital budgeting
3.5 - Spreadsheet features: matrix operations, using Solver for optimization, and using macros to generate the efficient frontier
4 - Risk analysis
4.1 - Monte-Carlo simulation
4.2 - Risk analysis of discounted cash flow models
4.3 - Spreadsheet features: using specific software for Monte-Carlo simulation
5 - Option valuation
5.1 - Binomial trees
5.2 - Risk neutral valuation
5.3 - American option valuation
5.4 - Estimating stock return volatility
5.5 - Matching volatility with a binomial tree
6 - Real option valuation with binomial trees
7 - Black-Scholes formula and option valuation
7.1 - Black-Scholes formula (pricing European options and estimating implied stock return volatilities)
7.2 - Simulating stock price evolution with Monte-Carlo simulation
8 - Real option valuation with Monte-Carlo simulation

Literature/Sources:

Benninga, Simon , 2014 , Financial Modeling , MIT Press
Damodaran, A. , 2012 , Investment Valuation: Tools and Techniques for Determining the Value of Any Asset , Wiley
Albright, Christian, Winston, Wayne , 2005 , Spreadsheet Modeling and Applications , South-Western College Pub

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
Theoretical and practice classes with texts and spreadsheets, real-life case studies and practical exercises. Software programming for implementing financial models in classroom. Presentation and discussion of team works, on programmatic topics that require reading, summarization and implementation of scientific documents.   Assessment: Regular season: Written test (50%), evaluation sheets (10%), and team work (40%); Supplementary and special season: Written test (60%) and team work (40%).