Scheda insegnamento

Anno Accademico 2018/2019

Conoscenze e abilità da conseguire

At the end of the course the student is familiar with the main principles of credit and liquidity risk, and the techniques used to transfer these risks. As for credit risk, the student is familiar with the credit derivative markets, and with the main credit risk models, both structural and reduced form. As for liquidity risk, the student is aware of the concepts of funding and market liquidity. The student has also sound knowledge of counterpart risk and the associated credit risk mitigating techniques.


Academic year 2018-2019, Giacomo Bormetti

At the end of the course, the student is familiar with the main principles of credit risk and frontier issues in risk management, such as high-frequency market risk measurement, behavioral risk, and systemic risk. Concerning credit risk, the student will be able to handle intensity based models for counterparty default and to compute valuation adjustments. As high-frequency risk is concerned, the student will be aware of the main features of the market at intra-day level, their measurement and management (volatility and correlation dynamics, seasonal patterns, high-frequency VaR and ES). Finally, the student will be introduced to the concept of news sentiment, how to measure it, and how it interacts with high frequency dynamics and systemic risk.

I Part. Credit risk and counterparty default: basic definitions. Credit derivatives and term structure of default probabilities. Credit risk models: reduced form intensity based models. Counterparty risk: valuation adjustments. Behavioral value adjustment for the pricing of financial instruments with embedded options.

II Part. Frontier issues in risk management: observation-driven models of intra-day price dynamics. High-frequency Value-at-Risk. High-frequency Value-at-Risk. News, sentiment, and high-frequency market dynamics. Market sentiment and systemic risk.


Textbooks and articles will be suggested during the lectures. Here it follows a list of the main references

  1. L. Ballotta, G. Fusai, and M. Marena, A Gentle Introduction to Default Risk and Counterparty Credit Modelling (2016). Available at SSRN: https://ssrn.com/abstract=2816355
  2. D. Brigo, M. Morini, and A. Pallavicini, Counterparty Credit Risk, Collateral and Funding with Pricing Cases for all Asset Classes. Wiley, Chichester (2013)
  3. M. Bissiri, and R. Cogo, Behavioral Value Adjustments (2017) International Journal of Theoretical and Applied Finance (20)08: 1750050
  4. D. Creal, S. J. Koopman, and A. Lucas, Generalized autoregressive score models with applications (2013) Journal of Applied Econometrics (28)5: 777-795
  5. G. Buccheri, et al., A score-driven conditional correlation model for noisy and asynchronous data: An application to high-frequency covariance dynamics (2017). Available at SSRN: https://ssrn.com/abstract=291243
  6. P. C. Tetlock, Giving content to investor sentiment: The role of media in the stock market (2007) The Journal of finance (62)3: 1139-1168
  7. A. Groß-Klußmann, and N. Hautsch, When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions (2011) Journal of Empirical Finance (18)2: 321-340

Metodi didattici


Modalità di verifica dell'apprendimento

The exam will consist of a term paper and an oral exam.

The paper that will be selected by the student. The typical term paper consists of: i) an introduction of the problem; ii) a review of the relevant literature; iii) the model proposed; iv) an empirical application of the model. The paper will be graded considering completeness of the review and originality of the idea, that can be theoretical or empirical. The paper will be defended in an oral discussion.

After the defense of the paper, the oral exam will continue on several subjects covering the program of the course.

Strumenti a supporto della didattica

Classroom lectures.

Orario di ricevimento

Consulta il sito web di Giacomo Bormetti