Binary Bullion Bot (Enjoy Free BONUS Carol Alexander eBooks [Risk Analysis, Quantitative Finance, Hedging]
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The Binary Bullion Bot settings are easy and even a newbie can handle them.
This bot is essentially a trend following Expert Advisor . It operates on the currency pair EURUSD (M15) and so it is kind of restricted if you are keen to trade other currency pairs. When I first started, I was always asking about the strategy that the Binary Bullion Bot uses but like many other forex bots in the marketplace, it’s like a black box where no description is given as to how they arrive at a final decision whether to buy or sell.
Basically, it’s been programmed to automate the process of forex trading so even if you are a newbie and unsure of how to configure the Binary Bullion Bot systems, don’t worry. Just start with the default settings and don’t mess with the settings until you know what you are doing. That is how I started. I generally have the itch to fiddle with settings but I found that the fault settings are good enough to start with.
The entry of any trade is centered on the volatility indicator running with two different periods. When this indicator shows that volatility is changing, a trend is considered to have started and the Expert advisor will open a position. If it is discovered that the market is going against the trend, the position will be rapidly closed with an average loss of 30 pips. The bot will then wait for another situation with good profit potential.
On the Binary Bullion Bot other hand, if the market moves in the right course as forecasted, then the EA starts to add to the current position. It can reach up to five times its original quantity. Of course in reality, markets can retrace and the positions will not always run their course. But when they do trend as forecasted, they can give a lot of profitable trades.
Trades are opened whenever the forex bot finds that the trading conditions are met throughout the day and night. In this case, the opening positions are not restricted to any specific trading session. The EA opens and closes its positions at the start of each bar and doesn’t send a stoploss and take profit target with the order.
As far as parameters is concerned, the basic Binary Bullion Bot version does not have all the features that some other forex bots have. It allows you to set the lot size manually and there are also parameters for controlling the volatility configurations.
If you are interested to do more configurations yourself, look out for the advanced edition that gives you access to more settings such as the Wave Trailing which is a form of trailing stop and more volatility settings.
The advanced version also has a reinvest capital option. This can be a form of money management that is more advanced and you can increase for each specific quantity of profit made.
To me, the Wave Trailing parameter offered by the advanced edition, is useful. I found that it has been able to improve a bit on the profit in comparison to the basic version. Trades that delivered a lot of profit are allowed to operate for a longer time and thus able to get more gains when this feature of Wave Trailing is enabled. However, some traders did find that there is a higher drawdown risk but most don’t mind.
Regarding lot sizing, you can set the number of lots manually. You are asked to use 0.01 lots for balances under $250 and 0.1 lots for balances over $2000. However, this can depend on your tolerance and style of trading.
As for currency pairs, the program recommends running only on EURUSD M15. I believe you would get the best results are with the one highly recommended.
The Binar Bullion Bot complies with the no-hedging rules. It now offers the option that will allow you to enable compliance with FIFO. This is essential if you’re using a US broker that implements this FIFO rule, otherwise you will not be able to buy and sell.
Over-all, this forex bot, despite its lack of many functions for the basic edition, is in my opinion one of the best trend forex bots. The price is well worth it and is a one time payment. I personally found the Advanced Edition well worth it. If you are worried about the Binary Bullion Bot settings, don’t be. This is an easy bot to handle and when you start just go with the default settings.
Package:
Binary Bullion Bot Advanced ex4,Binary Bullion Bot Manual pdf
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.
Editorial Reviews
From the Inside Flap
In part 1, 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 in part 2 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 explained in part 3, 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.
From the Back Cover
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 the reader 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.
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.
Product details
Ebook: 445 pages
Publisher: Wiley; 1 edition
Language: English
ISBN-10: 0471899755
ISBN-13: 978-0471899754
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 from the accompanying CD-ROM . 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.
Product information
ebook: 320 Seiten
Verlag: Wiley; Auflage: 1.
Sprache: Englisch
ISBN-10: 0470998008
ISBN-13: 978-0470998007
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.
Editorial Reviews
From the Inside Flap
Market Risk Analysis is a series of four volumes:
Volume I: Quantitative Methods in Finance
Volume II: Practical Financial Econometrics
Volume III: Pricing, Hedging and Trading Financial Instruments
Volume IV: Value at Risk Models.
Although the four volumes are very much interlinked, each containing numerous cross-references to other volumes, they are written as self-contained texts.
Volume I covers the essential mathematical and financial background for subsequent volumes. There are six comprehensive chapters covering all the calculus, linear algebra, probability and statistics, numerical methods and portfolio mathematics that are necessary for market risk analysis. It is a complete and pedagogical introduction to quantitative methods applied to finance.
Volume II provides a detailed understanding of financial econometrics, with a unique focus on applications to asset pricing, fund management and market risk analysis. It covers equity factor models, including a detailed analysis of the Barra model and tracking error, principal component analysis, volatility and correlation, GARCH, cointegration, copulas, Markov switching, quantile regression, discrete choice models, non-linear regression, forecasting and model evaluation.
Volume III has five extensive chapters on the pricing, hedging and trading of bonds and swaps, futures and forwards, options and volatility, and detailed descriptions of mapping portfolios of these financial instruments to their risk factors. There are numerous examples, all coded in interactive Excel spreadsheets, including many pricing formulae for exotic options but excluding the calibration of stochastic volatility models, for which Matlab code is provided.
Volume IV builds on the three previous volumes to provide a comprehensive and detailed treatment of market VaR models. The exposition starts at an elementary level but, as in all the other volumes, the pedagogical approach accompanied by numerous interactive Excel spreadsheets allows readers to experience the application of parametric linear, historical simulation and Monte Carlo VaR models to increasingly complex portfolios. Starting with simple positions, readers are soon applying risk models to large international securities portfolios, commodity futures, path dependent options and much else. This rigorous treatment includes many new results and applications to regulatory and economic capital allocation, measurement of VaR model risk and stress testing.
From the Back Cover
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 tGARCH 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.
Product details
Ebook: 416 pages
Publisher: Wiley; Volume II edition
Language: English
ISBN-10: 0470998016
ISBN-13: 978-0470998014
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.
Editorial Reviews
From the Inside Flap
Market Risk Analysis is a series of four volumes:
Volume I: Quantitative Methods in Finance
Volume II: Practical Financial Econometrics
Volume III: Pricing, Hedging and Trading Financial Instruments
Volume IV: Value at Risk Models.
Although the four volumes are very much interlinked, each containing numerous cross-references to other volumes, they are written as self-contained texts.
Volume I covers the essential mathematical and financial background for subsequent volumes. There are six comprehensive chapters covering all the calculus, linear algebra, probability and statistics, numerical methods and portfolio mathematics that are necessary for market risk analysis. It is a complete and pedagogical introduction to quantitative methods applied to finance.
Volume II provides a detailed understanding of financial econometrics, with a unique focus on applications to asset pricing, fund management and market risk analysis. It covers equity factor models, including a detailed analysis of the Barra model and tracking error, principal component analysis, volatility and correlation, GARCH, cointegration, copulas, Markov switching, quantile regression, discrete choice models, non-linear regression, forecasting and model evaluation.
Volume III has five extensive chapters on the pricing, hedging and trading of bonds and swaps, futures and forwards, options and volatility, and detailed descriptions of mapping portfolios of these financial instruments to their risk factors. There are numerous examples, all coded in interactive Excel spreadsheets, including many pricing formulae for exotic options but excluding the calibration of stochastic volatility models, for which Matlab code is provided.
Volume IV builds on the three previous volumes to provide a comprehensive and detailed treatment of market VaR models. The exposition starts at an elementary level but, as in all the other volumes, the pedagogical approach accompanied by numerous interactive Excel spreadsheets allows readers to experience the application of parametric linear, historical simulation and Monte Carlo VaR models to increasingly complex portfolios. Starting with simple positions, readers are soon applying risk models to large international securities portfolios, commodity futures, path dependent options and much else. This rigorous treatment includes many new results and applications to regulatory and economic capital allocation, measurement of VaR model risk and stress testing.
From the Back Cover
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 30 case studies many of which are contained in interactive Excel spreadsheets available from the accompanying CD-ROM. In this volume alone there are over 200 spreadsheets in 25 workbooks. Here are just some of he illustrative empirical examples and case studies in this volume:
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.
Product details
Ebook: 416 pages
Publisher: Wiley; Volume III edition
ISBN-10: 0470997893
ISBN-13: 978-0470997895
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 CD-ROM . 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.
Editorial Reviews
From the Inside Flap
Market Risk Analysis is a series of four volumes:
Volume I: Quantitative Methods in Finance
Volume II: Practical Financial Econometrics
Volume III: Pricing, Hedging and Trading Financial Instruments
Volume IV: Value at Risk Models.
Although the four volumes are very much interlinked, each containing numerous cross-references to other volumes, they are written as self-contained texts.
Volume I covers the essential mathematical and financial background for subsequent volumes. There are six comprehensive chapters covering all the calculus, linear algebra, probability and statistics, numerical methods and portfolio mathematics that are necessary for market risk analysis. It is a complete and pedagogical introduction to quantitative methods applied to finance.
Volume II provides a detailed understanding of financial econometrics, with a unique focus on applications to asset pricing, fund management and market risk analysis. It covers equity factor models, including a detailed analysis of the Barra model and tracking error, principal component analysis, volatility and correlation, GARCH, cointegration, copulas, Markov switching, quantile regression, discrete choice models, non-linear regression, forecasting and model evaluation.
Volume III has five extensive chapters on the pricing, hedging and trading of bonds and swaps, futures and forwards, options and volatility, and detailed descriptions of mapping portfolios of these financial instruments to their risk factors. There are numerous examples, all coded in interactive Excel spreadsheets, including many pricing formulae for exotic options but excluding the calibration of stochastic volatility models, for which Matlab code is provided.
Volume IV builds on the three previous volumes to provide a comprehensive and detailed treatment of market VaR models. The exposition starts at an elementary level but, as in all the other volumes, the pedagogical approach accompanied by numerous interactive Excel spreadsheets allows readers to experience the application of parametric linear, historical simulation and Monte Carlo VaR models to increasingly complex portfolios. Starting with simple positions, readers are soon applying risk models to large international securities portfolios, commodity futures, path dependent options and much else. This rigorous treatment includes many new results and applications to regulatory and economic capital allocation, measurement of VaR model risk and stress testing.
From the Back Cover
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 CD-ROM . Empirical examples and case studies specific to this volume include:
Parametric linear value at risk (VaR)models: normal, Student tand 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.
Product details
Ebook: 492 pages
Publisher: Wiley; Volume IV edition
Language: English
ISBN-10: 0470997885
ISBN-13: 978-0470997888
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