TOPICS IN INNOVATION ECONOMICS II
- Overview
- Assessment methods
- Learning objectives
- Contents
- Full programme
- Delivery method
- Teaching methods
- Contacts/Info
None.
The exam consists of a written part (comprising 2 open questions and 2 exercises). Students will have the option to write an essay (in groups of up to 3 members) and present it at the end of the course. The topic of the essay will be chosen by the instructor and the students. In case of a positive evaluation (>18/30), students presenting in the workshop will not be required to attend the written exam.
The course intends to introduce students to classical topics and recent advances regarding mathematical aspects of risk management and their connection with economics of innovation. The tools of risk theory endow students with an analytical mindset and a strong quantitative preparation, which forms the building block for understanding the foundations of quantitative risk theory. The course helps students tackle intriguing questions about risk in economic and financial contexts through a rigorous mathematical approach.
Mathematical and statistical preliminaries. Risk measures: definition and different approaches. Examples of risk measures. Numerical aspects. Applications to project risk management.
Preliminaries. Review on probability theory, quantiles, first and second order stochastic dominance and portfolio theory, and statistics. Risk measures: different approaches. Definition of Value at Risk (VaR) and outline of the Basel Committee rules. Examples of computation of VaR for discrete and continuous distributions. Properties of VaR. Computation of VaR for portfolios of stocks under the assumption of normality of the yields of the stocks. Delta and Delta-Gamma approximations of the computation of the VaR of derivatives portfolios (under the assumption of normality of the yield of the underlyings). Outline of the estimation of the Variance-Covariance matrix. Historical simulations and Monte Carlo Method for the computation of VaR. Backtesting. Drawbacks and applications of VaR. CVaR and optimization. Axiomatic definition of a coherent risk measure. Conditional Value at Risk (CVaR): definition, examples and coherence. Application of CVaR to portfolio optimization. Coherent (and convex) risk measures and relation with utility theory. Numerical examples and complements.
The course will be composed of 20 hours of lectures and will be based on a set of slides written by the instructor, covering theory and practical examples. Additional readings will be communicated during the semester. The teaching material will be posted on the e-learning platform.
The syllabus can be subject to modifications and changes during the course. Please check periodically the course page on e-learning for possible changes and communications from the instructor.
A Tutoring Service is active at the Department of Economics. More detailed information is available at the following link:
https://www.uninsubria.it/servizi/tutti-i-servizi/tutorato-dieco