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Binary Bullion Bot with Carol Alexander eBooks [Risk Analysis, Quantitative Finance, Hedging]

Binary Bullion Bot with Carol Alexander eBooks [Risk Analysis, Quantitative Finance, Hedging]
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Carol Alexander eBooks.jpg


Market Models provides an authoritative and up�to�date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data Analysis, this book is the first of its kind to address the vital techniques required for model selection and development. Model developers are faced with many decisions, about the pricing, the data, the statistical methodology and the calibration and testing of the model prior to implementation. It is important to make the right choices and Carol Alexander′s clear exposition provides valuable insights at every stage.

In each of the 13 Chapters, Market Models presents real world illustrations to motivate theoretical developments. The accompanying CD contains spreadsheets with data and programs; this enables you to implement and adapt many of the examples. The pricing of options using normal mixture density functions to model returns; the use of Monte Carlo simulation to calculate the VaR of an options portfolio; modifying the covariance VaR to allow for fat�tailed P&L distributions; the calculation of implied, EWMA and ′historic′ volatilities; GARCH volatility term structure forecasting; principal components analysis; and many more are all included.

Carol Alexander brings many new insights to the pricing and hedging of options with her understanding of volatility and correlation, and the uncertainty which surrounds these key determinants of option portfolio risk. Modelling the market risk of portfolios is covered where the main focus is on a linear algebraic approach; the covariance matrix and principal component analysis are developed as key tools for the analysis of financial systems. The traditional time series econometric approach is also explained with coverage ranging from the application cointegration to long�short equity hedge funds, to high�frequency data prediction using neural networks and nearest neighbour algorithms.

Throughout this text the emphasis is on understanding concepts and implementing solutions. It has been designed to be accessible to a very wide audience: the coverage is comprehensive and complete and the technical appendix makes the book largely self�contained.

Market Models: A Guide to Financial Data Analysis is the ideal reference for all those involved in market risk measurement, Quantitative trading and investment analysis.


Carol Alexander eBooks .jpg


Written by leading market risk academic, Professor Carol Alexander, Quantitative Methods in Finance forms part one of the Market Risk Analysis four volume set. Starting from the basics, this book helps readers to take the first step towards becoming a properly qualified financial risk manager and asset manager, roles that are currently in huge demand. Accessible to intelligent readers with a moderate understanding of mathematics at high school level or to anyone with a university degree in mathematics, physics or engineering, no prior knowledge of finance is necessary. Instead the emphasis is on understanding ideas rather than on mathematical rigour, meaning that this book offers a fast�track introduction to financial analysis for readers with some Quantitative background, highlighting those areas of mathematics that are particularly relevant to solving problems in financial risk management and asset management. Unique to this book is a focus on both continuous and discrete time finance so that Quantitative Methods in Finance is not only about the application of mathematics to finance; it also explains, in very pedagogical terms, how the continuous time and discrete time finance disciplines meet, providing a comprehensive, highly accessible guide which will provide readers with the tools to start applying their knowledge immediately.

All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available . Empirical examples and case studies specific to this volume include:
Principal component analysis of European equity indices;

Calibration of Student t distribution by maximum likelihood;
Orthogonal regression and estimation of equity factor models;
Simulations of geometric Brownian motion, and of correlated Student t variables;
Pricing European and American options with binomial trees, and European options with the Black�Scholes�Merton formula;
Cubic spline fitting of yields curves and implied volatilities;
Solution of Markowitz problem with no short sales and other constraints;
Calculation of risk adjusted performance metrics including generalised Sharpe ratio, omega and kappa indices.


Carol Alexander eBooks .jpg


Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one�semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet.

All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD�ROM . Empirical examples and case studies specific to this volume include:

Factor analysis with orthogonal regressions and using principal component factors;
Estimation of symmetric and asymmetric, normal and Student t GARCH and E�GARCH parameters;
Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization;
Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management;
Simulation of normal mixture and Markov switching GARCH returns;
Cointegration based index tracking and pairs trading, with error correction and impulse response modelling;
Markov switching regression models (Eviews code);
GARCH term structure forecasting with volatility targeting;
Non�linear quantile regressions with applications to hedging.


[2008] Carol Alexander eBooks [Risk 41jNzz2e4+L._BO2,204,203,200_PIsitb-sticker-arrow-click,TopRight,35,-76_AA300_SH20_OU02_.jpg


Written by leading market risk academic, Professor Carol Alexander, Pricing, Hedging and Trading Financial Instruments forms part three of the Market Risk Analysis four volume set. This book is an in�depth, practical and accessible guide to the models that are used for pricing and the strategies that are used for hedging financial instruments, and to the markets in which they trade. It provides a comprehensive, rigorous and accessible introduction to bonds, swaps, futures and forwards and options, including variance swaps, volatility indices and their futures and options, to stochastic volatility models and to modelling the implied and local volatility surfaces.

All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD�ROM . Empirical examples and case studies specific to this volume include:

Duration�Convexity approximation to bond portfolios, and portfolio immunization;
Pricing floaters and vanilla, basis and variance swaps;
Coupon stripping and yield curve fitting;
Proxy hedging, and hedging international securities and energy futures portfolios;
Pricing models for European exotics, including barriers, Asians, look�backs, choosers, capped, contingent, power, quanto, compo, exchange, �best�of� and spread options;
Libor model calibration;
Dynamic models for implied volatility based on principal component analysis;
Calibration of stochastic volatility models (Matlab code);
Simulations from stochastic volatility and jump models;
Duration, PV01 and volatility invariant cash flow mappings;
Delta�gamma�theta�vega mappings for options portfolios;
Volatility beta mapping to volatility indices.


[2008] Carol Alexander eBooks [Risk 41QjuwTqrAL._BO2,204,203,200_PIsitb-sticker-arrow-click,TopRight,35,-76_AA300_SH20_OU02_.jpg


Written by leading market risk academic, Professor Carol Alexander, Value�at�Risk Models forms part four of the Market Risk Analysis four volume set. Building on the three previous volumes this book provides by far the most comprehensive, rigorous and detailed treatment of market VaR models. It rests on the basic knowledge of financial mathematics and statistics gained from Volume I, of factor models, principal component Analysis, statistical models of volatility and correlation and copulas from Volume II and, from Volume III, knowledge of pricing and hedging financial instruments and of mapping portfolios of similar instruments to risk factors. A unifying characteristic of the series is the pedagogical approach to practical examples that are relevant to market risk analysis in practice.

All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying . Empirical examples and case studies specific to this volume include:

Parametric linear value at risk (VaR)models: normal, Student t and normal mixture and their expected tail loss (ETL);
New formulae for VaR based on autocorrelated returns;
Historical simulation VaR models: how to scale historical VaR and volatility adjusted historical VaR;
Monte Carlo simulation VaR models based on multivariate normal and Student t distributions, and based on copulas;
Examples and case studies of numerous applications to interest rate sensitive, equity, commodity and international portfolios;
Decomposition of systematic VaR of large portfolios into standard alone and marginal VaR components;
Backtesting and the assessment of risk model risk;
Hypothetical factor push and historical stress tests, and stress testing based on VaR and ETL.


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