“…Finally, you will compute Value at Risk (VaR) and simulate portfolio values using Monte Carlo Simulation which is a broader class of computational algorithms. …”

Tabla de Contenidos: “…Market Risk Analysis Volume IV; Contents; List of Figures; List of Tables; List of Examples; Foreword; Preface to Volume IV; IV.1 Value at Risk and Other Risk Metrics; IV.2 Parametric Linear VaR Models; IV.3 Historical Simulation; IV.4 Monte Carlo VaR; IV.5 Value at Risk for Option Portfolios; IV.6 Risk Model Risk; IV.7 Scenario Analysis and Stress Testing; IV.8 Capital Allocation; References; Index…”

Tabla de Contenidos: “….-4: Object-Oriented Techniques -- 5: Design Patterns for Options Processing -- 6: Template-Based Techniques -- 7: STL for Derivatives Programming -- 8: Functional Programming Techniques -- 9: Linear Algebra Algorithms -- 10: Algorithms for Numerical Analysis -- 11: Models Based on Differential Equations -- 12: Basic Models for Options Pricing -- 13: Monte Carlo Methods -- 14: Using C++ Libraries for Finance -- Appendix A: Features of C++20…”

Tabla de Contenidos: “…A tour of C++ and environs -- New and improved C++ fundamentals -- Modelling functions in C++ -- Advanced c++ template programming -- Tuples in c++ and their applications -- Type traits, advanced lambdas and multiparadigm design in C++ -- Multiparadigm design in C++ -- C++ numerics, IEEE754 and boost C++ multiprecision -- An introduction to unified software design (USD) -- New data types, containers and algorithms in C++ and boost C++ libraries -- Lattice models fundamental data structures and algorithms -- Lattice models applications to computational finance -- Numerical linear algebra : tridiagonal systems and applications -- Data visualisation in Excel -- Univariate statistical distributions -- Bivariate statistical distributions and two-asset option pricing -- STL algorithms in detail -- STL algorithms part II -- An introduction to optimisation and the solution of nonlinear equations -- The finite difference method for PDEs mathematical background -- Software framework for one-factor option models -- Extending the software framework -- A PDE software framework in C++11 for a class of path-dependent options -- Ordinary differential equations and their numerical approximation -- Advanced ordinary differential equations and method of lines (MOL) -- Random number generation and distributions -- Microsoft .net, C# and C++11 interoperability -- C++ concurrency, Part I Threads -- C++ concurrency, part II Tasks -- Parallel patterns language (PPL) -- Monte Carlo simulation, Part I -- Monte Carlo simulation, Part II -- Bibliography -- Appendix -- Index…”

Tabla de Contenidos: “…Asset and Portfolio Optimization -- 14. Monte Carlo Methods -- 15. Extending Financial Libraries -- 16. …”

Tabla de Contenidos: “…Analyzing big data -- Introduction to data analysis with Scala and Spark -- Recommending music and the audioscrobbler data set -- Predicting forest cover with decision trees -- Anomaly detection in network traffic with K-means clustering -- Understanding Wikipedia with latent semantic analysis -- Analyzing co-occurrence networks with GraphX -- Geospatial and temporal data analysis on the New York City taxi trip data -- Estimating financial risk through Monte Carlo simulation -- Analyzing genomics data and the BDG project -- Analyzing neuroimaging data with PySpark and Thunder…”

Tabla de Contenidos: “…Analyzing big data -- Introduction to data analysis with Scala and Spark -- Recommending music and the audioscrobbler data set -- Predicting forest cover with decision trees -- Anomaly detection in network traffic with K-means clustering -- Understanding Wikipedia with latent semantic analysis -- Analyzing co-occurrence networks with GraphX -- Geospatial and temporal data analysis on the New York City taxi trip data -- Estimating financial risk through Monte Carlo simulation -- Analyzing genomics data and the BDG project -- Analyzing neuroimaging data with PySpark and Thunder…”

Tabla de Contenidos: “…Determining Capacity Credit for Wind Used in MISO Resource Adequacy -- Wind Power Scenario Tree Tool: Development and Methodology -- Probabilistic Ramp Detection and Forecasting for Wind Power Prediction -- Application of Hourly Time Series Models in Day Ahead Wind Power Commitment -- Probabilistic Guarantees for the N-1 Security of Systems with Wind Power Generation -- Adequacy and Security Measures in Integrated Intermittent Renewable Generation -- Representation of Wind and Load Correlation in Non-Sequential Monte Carlo Reliability Evaluation -- Composite Reliability Assessment of Power Systems with Large Penetration of Renewable Sources…”

Tabla de Contenidos: “…Example: Clutter simulation of a radar system5.5 Signal Processing Toolbox; Example: Filter signal using circular convolution; 5.6 Statistics and Machine Learning Toolbox; Example: Estimation of descriptive statistics measures using the Monte Carlo method; 5.7 Chapter Review; Chapter 6: Multiple GPUs; 6.1 Identify and run code on a specific GPU device; 6.2 Examples using multiple GPUs; Example 1: Monte Carlo simulation to approximate the area of a figure; Example 2: Estimation of descriptive statistics measures using the Monte Carlo method; Example 3: Image edge detection on multiple images…”

Tabla de Contenidos: “…Decision Analysis. -- 16. Monte Carlo Simulation. -- 17. Optimization Simulation. -- Appendix. …”

Tabla de Contenidos: “…chapter 1 The Golem of Prague / chapter 2 Small Worlds and Large Worlds / chapter 3 Sampling the Imaginary / chapter 4 Linear Models / chapter 5 Multivariate Linear Models / chapter 6 Overfitting, Regularization, and Information Criteria / chapter 7 Interactions / chapter 8 Markov Chain Monte Carlo / chapter 9 Big Entropy and the Generalized Linear Model / chapter 10 Counting and Classification / chapter 11 Monsters and Mixtures / chapter 12 Multilevel Models / chapter 13 Adventures in Covariance / chapter 14 Missing Data and Other Opportunities / chapter 15 Horoscopes…”

Tabla de Contenidos: “…Linear factor models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Monte Carlo methods -- Confronting the partition function -- Approximate inference -- Deep generative models" -- OhioLink Library Catalog…”

Tabla de Contenidos: “…Front Cover; Foreword; Table of Contents; Preface; Preface to the Second Edition; Chapter 1: Introduction; Chapter 2: The Physics of Light Transport; Chapter 3: Monte Carlo Methods; Chapter 4: Strategies for Computing Light Transport; Chapter 5: Stochastic Path-Tracing Algorithms; Chapter 6: Stochastic Radiosity; Chapter 7: Hybrid Algorithms; Chapter 8: The Quest for Ultimate Realism and Speed; Chapter 9: Conclusion; Appendix A: A Class Library for Global Illumination; Appendix B: Hemispherical Coordinates; Appendix C: Theoretical Analysis of Stochastic Relaxation Radiosity; Bibliography…”