“…Ritchie Mehta is the Founder and CEO of Learn et al and the School of Marketing, a leading education platform that has over 8 FTSE 100 and 250 clients and partners including; Unilever, Three, TSB, RBS, Direct Line Group, Global and Pearson. …”

“…At each stage the theory is developed by application to the FTSE 100 companies and their valuation and strategy. …”

Tabla de Contenidos: “…-- The critics -- More risk, greater returns -- The rise of fundamentals-based index investing -- The efficient markets purists' counter attack -- A middle way - the reality of relatively efficient markets -- Building the perfect index -- Structuring the revolution -- Building the perfect index - the FTSE 100? -- Putting it all together in an index fund -- Capturing the index -- The rise of ETFs -- Defining ETFs -- The European alternative: synthetic replication -- An ETF in action -- Stock lending: smoothing out returns? …”

Tabla de Contenidos: “…15.2 Calibration Problems for Yield Curves -- 15.3 Reversion Speed and Volatility -- 15.4 Local Volatility -- 15.4.1 Dupire's Inversion Formula -- 15.4.2 Identifying Local Volatility -- 15.4.3 Results -- 15.5 Identifying Parameters in Volatility Models -- 15.5.1 Model Calibration for the FTSE-100 -- 16 Optimization Techniques -- 16.1 Model Calibration and Optimization -- 16.1.1 Gradient-Based Algorithms for Nonlinear Least Squares Problems -- 16.2 Heuristically Inspired Algorithms -- 16.2.1 Simulated Annealing -- 16.2.2 Differential Evolution -- 16.3 A Hybrid Algorithm for Heston Model Calibration -- 16.4 Portfolio Optimization -- 17 Risk Management -- 17.1 Value at Risk and Expected Shortfall -- 17.1.1 Parametric VaR -- 17.1.2 Historical VaR -- 17.1.3 Monte Carlo VaR -- 17.1.4 Individual and Contribution VaR -- 17.2 Principal Component Analysis -- 17.2.1 Principal Component Analysis for Non-scalar Risk Factors -- 17.2.2 Principal Components for Fast Valuation -- 17.3 Extreme Value Theory -- 18 Quantitative Finance on Parallel Architectures -- 18.1 A Short Introduction to Parallel Computing -- 18.2 Different Levels of Parallelization -- 18.3 GPU Programming -- 18.3.1 CUDA and OpenCL -- 18.3.2 Memory -- 18.4 Parallelization of Single Instrument Valuations using (Q)MC -- 18.5 Parallelization of Hybrid Calibration Algorithms -- 18.5.1 Implementation Details -- 18.5.2 Results -- 19 Building Large Software Systems for the Financial Industry -- Bibliography -- Index…”