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Programma

Dopo una prima parte introduttiva dei concetti principali di probabilità, statistica, econometria, ingegneria finanziaria e istituzioni dei mercati dell’intermediazione finanziaria, il corso introduce gli aspetti di frontiera del rischio di mercato, di credito e di liquidità.
Nel campo del rischio di credito, un obiettivo primario del Master è quello di fornire competenze nell’analisi dei cosiddetti “big data”, ovvero dell’enorme mole di dati che le aziende finanziarie devono gestire. L’orientamento pratico del percorso di formazione passa attraverso l’uso delle tecniche informatiche più diffuse presso le istituzioni finanziarie; in questo modo si intende favorire l’inserimento dei partecipanti al Master nel mondo del lavoro.

Le lezioni si svolgeranno presso CRIF SpA indicativamente dal lunedì al giovedì dalle ore 10:00 alle 16:30 per un totale di 20 ore a settimana di didattica frontale.

  • Insegnamenti

Statistics: Michele Costa

  • Statistical analysis of financial variables: mean-variance analysis and portfolio
  • Linear models: market model and CAPM
  • Inference: parameter estimation, hypothesis testing and residual analysis

Financial econometrics: Luca De Angelis, Luca Fanelli

  • Stylized facts of return distributions
  • Random walk model and efficient market hypothesis
  • Asset pricing: intertemporal equilibrium, puzzles
  • Tail index and existence of moments
  • VAR-based approach to present-value model

Volatility modelling: Giuseppe Cavaliere, Anders Rahbek

  • ARCH and GARCH-type models
  • Maximum likelihood estimation
  • Volatility forecasting
  • Realized volatility and high-frequency data analysis

Programming: Fabio Gobbi, Milo Faccenda

  • Introduction to SAS
  • Programming in R

Probability: Sabrina Mulinacci

  • Probability spaces
  • Random variables, moments, main distributions
  • Random vectors, multivariate distributions, copulae
  • Conditional expected value and properties
  • Equivalent probabilities and Radon-Nikodym’s theorem
  • Discrete-time stochastic processes and filtrations: random walk
  • Discrete-time martingales

Financial calculus: Luca Vincenzo Ballestra

  • Deterministic discount and capitalization factors
  • Stochastic processes: Brownian motion, processes with independent increments, martingales
  • Stochastic integration
  • Stochastic differential calculus: Itô’s Lemma
  • Change of measure: exponential martingale and Girsanov’s theorem
  • EDS and PDE: geometric Brownian motion, Feynman-Kac’s theorem

Modelling of stock and (fixed) income markets: Silvia Romagnoli

  • No arbitrage assumption and fundamental theorems
  • Derivatives (stock market): Pricing and hedging in discrete time (binomial and trinomial model), and in continuous time (Black-Scholes, Ito's market, Black, multieconomy products)
  • Fixed income market: fundamentals equations implied by no-arbitrage assumption
  • Factor models: exponential affine models (Vasicek, Ho-Lee, CIR)
  • From HJM and BGM models to Market Model (FLMM, FSMM)

Financial products: Massimiliano Barbi

  • Fixed-income market and interest rate risk
  • Equity capital market and analysis
  • Forwards and futures
  • FRAs and swaps
  • Options and option applications
  • Convertibles and hybrids

Financial intermediation: Giuseppe Torluccio

  • The Nature and Variety of Financial Intermediation
  • The What, How, and Why of Financial Intermediaries
  • Banks’ balance sheet and income structure
  • Identification and Management of Major Banking Risks
  • Spot Lending and Credit Risk
  • The Funding of the Bank
  • Bank Capital Structure
  • Securitization
  • Banks and markets
  • Comparative banking markets

Financial regulation: Andrea Resti, Francesco Cannata

  • The Bank Recovery and Resolution Directive: main contents and implications for financial risk management
  • Open issues in bank regulation: expected developments and possible pitfalls
  • Banking and financial supervision: framework and developments
  • Regulatory and supervisory issues: the state of the art  

Market risk: Rossella Agliardi, Gian Luca Tassinari

  • Risk measures: VaR; coherent, convex and spectral risk measures
  • Risk measures: elicitability and backtesting
  • Market risk and accounting: Prudent Valuation
  • Risk exposures and sensitivity analysis
  • Risk reporting and cash flow mapping
  • Profit and loss distribution: parametric models
  • Profit and loss of nonlinear products: Monte Carlo methods
  • Non normal returns: historical simulation
  • Spread risk

Credit risk: Umberto Cherubini, Gian Luca Tassinari

  • Single name credit risk: structural models
  • Single name credit risk: intensity based models
  • Double stochastic models
  • Models for the recovery rate
  • Credit derivatives and implied default probabilities
  • Multivariate credit derivatives
  • Multivariate default distributions and copula functions
  • Securitization structures and CDO markets
  • Counter party risk in derivatives: CVA and DVA
  • Credit risk mitigation: CSA and central clearing registers
  • Liquidity risk: funding and liquidity risk

Credit scoring: Gabriele Soffritti

  • Statistical methods for credit scoring based on

       - Logistic regression analysis

       - Discriminant analysis

       - Classification trees

Big data in risk management: Andrea Guizzardi, Silvia Romagnoli

  • Short term forecasting with machine learning techniques
  • Model complexity, data structures and forecasting performances
  • The comparisons of rival model under different risk aversion profiles
  • Clustering algorithms for data set complexity reduction
  • Combinatory copula-based models for financial risk management