1 / 10

Structuring and Pricing Complex Credit Assets with Monte Carlo / @RISK

Structuring and Pricing Complex Credit Assets with Monte Carlo / @RISK. 22.06.2006 – Jörg Günther. EQUITY VS. CREDIT ASSETS. Balance Sheet Assets Current Assests - - - Fixed Assets - -. Cash Flows CF from Operations CF from Investing

beck
Télécharger la présentation

Structuring and Pricing Complex Credit Assets with Monte Carlo / @RISK

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Structuring and Pricing Complex Credit Assets with Monte Carlo / @RISK 22.06.2006 – Jörg Günther

  2. EQUITY VS. CREDIT ASSETS • Balance Sheet • Assets • CurrentAssests--- • Fixed Assets-- • Cash Flows • CF from Operations • CF from Investing • CF from Financing(or: what is left for 1. Debt Service 2. Equity Distributions) • E&L • Equity-- • Debt-- Pricing- models • Asset Markets Equity Stock-Price Debt Debt-Price; CDS

  3. EQUITY VS. CREDIT ASSETS - DERIVATIVES • Equity Derivatives • Vanilla Options(Call/Put) • Complex Options(Barrier, Basket, Cliquet, ...) • Credit Derivatives • Credit Default Swaps(Credit Risk) • CDO-Tranches • other... • Equity and Credit Assets – and their Derivatives - are • structurally different, but are ultimately based on the • same original Cash Flow of an Entity

  4. DIFFERENCES OF EQUITY AND CREDIT ASSETS • Equity Assets • liquid markets • abundant empirical data on • Underlyings • Options • Credit Assets • Illiquid markets • less empirical data, different focus (default/non-default) • Sophisticated Market & Models • Market & Models„work in progress“

  5. S&Ps RATING METHODOLOGY FOR CDO-TRANCHES • Loss Distribution • Monte-Carlo for Synthetic CDO- Structure • PDs • Recovery Rates • Correlation • Cash-Flow-CDO-Application • Scenarios for • Timing of default • Interest rates • Loss-Distribution used as input for cash-flow-model

  6. BASEL II – HOW MONTE CARLO HELPS TO COVER REGULATORY ISSUES • Balance Sheet Bank • Assets • Loans • E&L • Equity • Debt • Basel II • in % of loan • risk-adjusted • Standard • non-specific,i.e. same orstandardizedrisk-weight;on averagemore equiyto be provided • IRB • eg Project Finance: • Based on Monte-Carlo • More specificRating;on averageless equity

  7. PRICING A WIND POWER PROJECT-FINANCE-DEAL • Cash Flow Model • assumptions • Sources / Uses • Operating Cash Flow • Financing Cash Flow • Risk-Parameters • Scenarios (what-if) • Stochastic Assumptions • Monte-Carlo • Expected Loss • Rating-Class Spread-sheet-example: Wind-Power-Project

  8. STRUCTURING A PORTFOLIO LOAN – THE CASH FLOW STRUCTURE • Cash Flow of Underlyings • Timing Assumptions • Stochastic Assumptions • Asset return • Volatility • Correlation • Cash Flow of Financing Structure • Order of financing and repayment/distributions • defining loss / recovery rate Spread-sheet-example: PE-blind-pool

  9. STRUCTURING A PORTFOLIO LOAN – APPLYING MONTE-CARLO FOR THE PRICING • Structuring Parameters • Size of Equity-Tranche • Order of Distributions (Cash-Flow-Waterfall) • Interests • Outputs of Analysis • Expected Loss • Return on Bank‘s Equity • Return on Sponor‘s Equity • Volatility / Risk of Returns • Precise Pricing • Precise Risk-Return-Packaging Spread-sheet-example: PE-blind-pool

  10. FUNCTIONS OF @RISK OFTEN USED • Function • Distributions • Correlation Matrix • Fit to Distribution • D-Uniform-Distribution • Issue / Questions involved • Calculating Risk: Static -> StochasticAnalysis (Scenario -> Monte-Carlo) • Quantifying Diversification:Portfolio-Structures • Analyzing empirical data • Bootstrapping

More Related