75383 - Workshop in Quantitative Finance

Learning outcomes

The student is exposed to selected frontier issues of research from scholars in each field. Each scholar will address a topic, starting from the basic principles to the frontier questions. From the workshop, the student will collect ideas for his thesis and interests driving him to his future career.

Course contents

Prof. A. Harvey

4th May 2017: 10-12 a.m.

                 2.30-4.30 p.m.

5th May 2017: 10-12 a.m.

                 2.30-4.30 p.m.

Main Topics:

1. Nonlinear models and changing volatility
Unobserved components. Introduction to DCS/GAS models. Nonlinear models: independence, uncorrelatedness and martingale di¤erences. Distributions and heavy tails. Properties of fi…nancial returns. Standard volatility models: GARCH, EGARCH and stochastic volatility. Intra-day data, realized volatility, range and duration.
2. Dynamic conditional score (DCS) models
Location and robustness. EGARCH. Leverage, long memory, components. Skewness and asymmetry. Models for positive variables.
3. Correlations and copulas
Multivariate GARCH models. Dynamic correlation. Dependence and copulas, measures of association, dynamic copulas. Spatial association.
4. Recent developments
Multivariate-F covariance matrices. Changing shape. Censoring and zeroes. Adaptive …ltering. Quantiles.

 

Dott. G. Della Lunga

18th May 2017: 3-6 p.m.

19th May 2017: 9-13 a.m.

Main Topics:

Introduction to Monte Carlo Methods in Finance

• Introduction
  • Some basic ideas
  • Theoretical Foundations of Monte Carlo Simulation
• Single Asset Path Generator
  • Definitions
  • Exact solution advancement
  • Numerical Integration of SDE
  • The Brownian Bridge
• Variance Reduction Methods
  • Antithetic Variables
  • Moment Matching
• Multi Asset Path Generator
  • Cholesky Decomposition
  • Copula Functions
• Valuation of European Option with Stochastic Volatility
  • Square Root Diffusion, the CIR Model
  • The Heston Model
• Valuation of American Option
  • The general problem
  • The Longstaff-Schwartz solution
• MC Simulation for CVA Estimation
  • Definition
  • CVA of a plain vanilla swap: the analytical method
  • CVA of a plain vanilla swap: the simulation approach

Dott. A. Gianfreda

28th April: 2-5 p.m.

11th May: 2-5 p.m.

16th May:3-6 p.m.

23th May 3-6 p.m.

26th May: 2-5 p.m.

Main Topics:

1. Major sources of energy: crude oil, natural gas, LNP and Shale Gas, Coal, Electricity, Renewable energy sources.

2. Energy cycles: exploration, generate or production/extraction, transportation and distribution.

3. Electricity market: sessions and pricing mechanisms, analysis of supply and demand curves and their drivers, price modeling.

4. Energy Risks associated with the energy cycle: market, operational and regulatory risk, together with credit, liquidity and model risk.

5. The physical and financial markets for energy products: spots, forwards, futures, energy derivatives and real options.

 

Readings/Bibliography

Harvey, A. C. (2013) Dynamic Models for Volatility and Heavy Tails.
Cambridge University Press.

Creal, D., Koopman, S.J., and A. Lucas (2013). Generalized autoregressive score models with applications. Journal of Applied Econometrics, 28,777-95.

Creal, D., Koopman, S.J. and A. Lucas (2011). A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations, Journal of Business and Economic Statistics, 29, 552-63.

Websites: econ.cam.ac.uk/DCS; gasmodel.com

Office hours

See the website of Silvia Romagnoli