REACFIN TRAINING – TABLE OF CONTENT ALM techniques and market practices Typically a 5 to 6 days training often articulated as follows:

1. Introduction to ALM techniques i. What is ALM a. Concept and definitions b. Key elements of the regulatory framework o For Banks under CRD/CRR (Basel II/III) o For Insurance companies under Solvency II ii. a. Definition b. Historical evolution c. Calculating Yield-to-Maturity o Practical example in Excel and exercises o Useful tips on Bloomberg iii. Maturity Gaps & Cash-Flow Matching a. Concept b. Practical implementation o For risk assessment purposes o For risk mitigation purposes o Pro’s & Con’s o Real-Life examples and exercises in Excel iv. Basic balance-sheet immunization : Duration, Convexity and ALM a. Objective & concepts b. First degree metrics o Duration concept o Macaulay Duration and practical exercises in Excel o Review of Duration properties o Using Duration to measure ’s sensitivity to fluctuations o Evolution of duration over time and effect of coupons detachment (incl. case studies in Excel) o Modified Duration and practical exercises in Excel o Duration and balance-sheet immunization - Concept and theory - Duration based balance-sheet immunization: practical exercises - Main drawbacks of duration-based balance-sheet immunization o Second degree metrics - Convexity – Concept TVA: BE 0862.986.729 BNP Paribas 001-4174957-56  Deriving the convexity formula RPM Nivelles from Taylor developments

Tel: +32 (0)10 84 07 50 [email protected] www.reacfin.com

Reacfin s.a./n.v. Place de l’Université 25 B-1348 Louvain-la-Neuve

 Convexity – Practical exercises in Excel  Convexity of a bond, evolution in time and effects of detachment  Properties of Convexity  Investor’s attractiveness of higher convexity instruments - Balance-sheet immunization considering convexity - Duration & convexity based balance-sheet immunization: practical exercises in Excel v. Replicating Portfolios techniques a. Objective, concepts & definition b. Theoretical framework c. Typical Approaches & methodologies d. Basic static replication e. Static replication of complex payoffs f. Replication areas and grids g. Dynamic replication h. Handling large dimension problems i. Other implementation challenges j. Practical case study

2. measurements i. Theoretical concepts a. Mathematical concepts (Probability Space, Sigma-algebra, filtrations, etc.) b. Definition of stationary stochastic processes c. Martingales, Fair Games and ii. Value-at-Risk a. Rationale and concept b. Theoretical framework c. Case of the loss on a portfolio d. Empirical VaR vs. distribution based VaR o Historical VaR o Normal VaR o Other extensions e. Practical exercises in Excel f. Issues with VaR measurements o Tail risks: “Smile & skew” o Impact of volatility regimes g. Interpretation of VaR measurements iii. Monte-Carlo simulations a. Rationale and concept b. Key requirements of robust Monte Carlo simulations c. Simplified concept example: Pricing of financial derivatives d. Simplified example of application: Pricing of a plain-vanilla call option (incl. application in Excel) e. What are Risk Factors

2 | P a g e

f. Modelling risk factors in continuous time g. Real World vs. Risk Neutral assumptions o Real World assumptions o Risk Neutral assumptions o Rationale for Real World and Risk neutral assumptions in ALM o From replicating portfolio to risk neutral measures b. Ito’s Lemma h. Geometric Brownian Motion (“GBM” a.k.a. Wiener Processes) i. Euler–Maruyama discretization method (incl. exercise and example in Excel) j. Generating Pseudo-random numbers o Real randomness vs. pseudo randomness o Middle-square method (incl. example in Excel) o Wichmann-Hill method k. Pseudo-randomness quality tests (Marsaglia’s Diehard tests) o Monkey tests o Overlapping Sums Test o Birthday spacing o Permutation based tests o Run tests o Bit-stream test o Other typical tests o Examples and exercises in Excel l. Generating pseudo-random variables with specific distributions m. Simulation of Geometric Brownian Motion: practical implementation with examples in Excel, Matlab, R and C++ n. Variance reduction techniques o Rationale for variance reduction o Thetic – Antithetic Sampling with examples in Excel o Stratified Sampling with examples in Excel o Sobol sequences o Importance sampling o Methods combinations o Limitations o. Non-Normality of markets p. The Merton model : introducing jumps diffusion q. Mean Reversion o Concept o Ornstein–Uhlenbeck process and application in Excel and R r. Short Rates models o Concept o Issue with using Normally distributed changes in rates

3 | P a g e

o One Factor models - Vasicek (1977) - Cox Ingersoll Ross (1985) - Ho-Lee (1986) - Black-Derman-Toy (1990) - Hull-White 1-factor (1990) - Black- Karansinski (1991) - Practical implementations in Excel and R o Overview of some well-known 2-factors short rates models - G2++ / Hull-White 2-factor (1994) - CIR2++ (2001) - Practical implementations in Excel and R o Practical calibration of mean reverting models (including practical exercises in Excel and R) s. Interest Rates Market models - The Libor Market model - Practical calibration - Recent advances t. models - Rationale for stochastic volatility models and relation with “fat-tails” - Heston and 3/2 models - Chen Model - Constant Elasticity of Variance Model (CEV) - SABR - GARCH model u. Coping with negative interest rates - Model allowing negative interest rates - Displacement factors (or “shifted models”) - Summing probability densities corresponding to solutions to the Fokker-Planck equation with “opposite” signs. o Application: Free-boundary SABR v. Modeling inflation a. Modeling Realized inflation b. Modeling Break-Even Inflation c. The Jarrow-Yildirim model d. Calibration challenges w. Validation of simulation based models - What elements should a good validation process determine? - Sound back-testing principles - Tests for Risk Neutral Scenario’s o Tilinghast martingale tests o Initial yield curve tests - Logical consistency tests - Validating calibration methods - Other tests and elements to be validated iv. Balance-sheet projection a. Concept

4 | P a g e

b. Model architecture c. Instruments projections d. Balance-sheet interactions i. ALM ii. Management Actions iii. Behavioral options e. Using the results of balance-sheet projections i. In ALM ii. For SAA purposes iii. For Risk assessment purposes

3. Advanced balance-sheet immunization i. Term extension of Macaulay duration a. Term extension immunization and practical exercises in Excel ii. DV01, Basis Point Value – Concept and practical exercises in Excel iii. Duration and Non-Bullet Securities iv. Effective Duration or OAS Duration v. Impact of credit spreads on duration and convexity vi. Risky Duration (PV01) vii. Useful tips on Bloomberg viii. Assessing the Interest rates risks of retail none-maturing liabilities (on-sight deposits) a. Characteristics influencing modeling approaches b. Core Balance Theory c. Calibrating the Volatile Balance d. Assessing duration of deposits - Decay rate based approaches  Constant decay rate based projected duration  Behavioral dynamic decay rate models  Practical exercises and case-study - Replicating portfolio’s  Static replicating portfolio’s incl. practical exercises in Excel  Dynamic replicating portfolio’s incl. practical exercises in Excel  Historical calibration & critical assessment  Defining relevant forward looking scenario’s  Stochastic Replicating portfolio’s approaches and their calibration - Stochastic modeling – introduction  The “Hutchison &. Pennacchi” model  The “Jarrow and Van Deventer” model  The “Kalkbrener and Willing” extension  “Blöchlinger” extension  Bardenhewer OAS based model  Other approaches ix. Stress testing a. Concepts b. Relevant scenarios given the institution type c. Deterministic vs. stochastic

5 | P a g e

d. Market practices

3. ALM focused Portfolio Management i. Concepts ii. Financial Instruments a. Bonds - Sovereign & quasi-sovereign bonds - Credit risks & rating principles - Covered Bonds - Corporate Bonds - Subordinated & Hybrids - Structured Credit: Securitization b. Loans c. Derivatives - Forwards & Futures - FRA’s - Futures - Interest Rates Swaps - Accrual swaps - Constant Maturity Swaps - Cross Currency Swaps - Asset Swaps - Options  Caplets, Floorlets, Caps & Floors  Greeks  Delta  Gamma  Dynamic gamma hedging  Vega  Vega to gamma transformation  Theta  The specific case of CMS options  Combination of options  Collars  Spreads  Constructing contingent premium structures  Other combinations  Pricing combination of options  Managing combination of options over time  Market practices  Swaptions  Exotic options & structured products  Binary Options  Asian options  Spread options  Barrier options

6 | P a g e

 Lookback options  CMS steepeners  Snowballs  TARN’s  Inverse floaters  Specific Greeks - Vanna - Vol-Gamma d. ALM & Derivatives: implementing balance-sheet immunization overlay strategies (incl. LDI) e. Related European regulation: EMIR iii. Overlay structures iv. Practically deploying ALM techniques a. Cash-Flow matching b. Immunization c. Portfolio replication v. Typical composition of financial institutions ALM portfolio’s a. Banks b. Insurance companies c. Pension Funds

7 | P a g e