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Description of  Long-Term Portfolio Simulation - For XVA, Limits, Liquidity and Regulatory Capital

The changes in financial markets and regulatory environment following the financial crisis created many new analytics requirements. These requirements include those for computing CVA. In addition, advanced limit management based on potential future exposure (PFE) has taken an increased role following the crisis. Calculation of PFE-based limits also requires simulation of portfolio to maturity in either risk neutral or real measure. Other important requirements include modelling funding (FVA), collateral needs and cheapest to deliver collateral, and projection of portfolio cashflows for liquidity management. Previously many of these calculations were only performed by the largest sell side firms. Now, most of them are also required by small and medium banks, as well as asset managers and corporates. These new requirements can only be met by performing path consistent Monte Carlo simulation of portfolios involving a large number of risk factors over long time horizon (up to and exceeding 30 years). Written by industry expert Alexander Sokol, this is the first book to focus specifically on model construction and calibration for long-term portfolio simulation. The book offers insider knowledge and techniques for the unique modelling methodologies required in simulating entire portfolios. The book will address the following topics for multiple asset classes, including interest rate, cross currency and hybrid, CDS and credit products, and structured products: - Methodology fundamentals - Risk neutral models - Real world models - Margin period of risk - General wrong way risk - Systemic wrong way risk - Cashflow aggregation - American Monte Carlo - CVA and funding - Collateral optimisation - Liquidity and PFE-based limits - Regulatory capital Long-Term Portfolio Simulation is a comprehensive reference for quants responsible for building models for CVA, PFE, limits, liquidity, or funding, as well as those auditing and reviewing the models. Read more