Bøger af Johnathan Mun

Managing Your Personal Finances God's Way is a thought provoking book on how to manage your finances according to biblical principles. Everything that we have belongs to God, but we are entrusted with its care as stewards. To be godly stewards, we need to be both diligent and knowledgeable about our own finances. Money was one of the topics that Jesus talked the most about because He knew the devastating effects it might have on us. The love of money drives a wedge between us and God. To walk closer with God, we need to first put our financial house in order. Follow along as the author takes you on a journey to discovering your finances, from understanding heavenly economics and learning how to get debt free, to home purchasing and stock market investment principles. This book provides many hands on applications with sufficient technical details explained in an easy to follow approach, allowing you to have a better understanding and control of your finances.

Project Economics Analysis Tool (PEAT) User Manual and Visual Guide for version 2015 and beyond, developed by Real Options Valuation, Inc.

ROV Real Options SLS Software User Manual and Examples for version 2014 and beyond, developed by Real Options Valuation, Inc.

ROV Risk Simulator Software User Manual for version 2014 and beyond, developed by Real Options Valuation, Inc.

La Serie de Libros sobre el CQRM Aplicado expone cómo la analítica avanzada que figura en el programa de Certificación en Gestión Cuantitativa de Riesgos (CQRM), se puede aplicar a los problemas de negocios en la vida real. Se hace un énfasis en las aplicaciones pragmáticas con el fin de desmitificar los elementos inherentes al análisis de riesgos. Una caja negra continuará siendo una caja negra si nadie puede entender los conceptos a pesar de su poder y su aplicabilidad. Sólo hasta cuando los métodos de la caja negra se vuelven transparentes, para que los investigadores puedan entender, aplicar y convencer a otros de sus resultados, su valor agregado y la aplicabilidad, es que los enfoques recibirán una amplia atención. Esta transparencia se logra a través de las aplicaciones paso-a-paso de la modelación cuantitativa así como de la presentación de múltiples casos y de la discusión de las aplica-ciones en la vida real.El presente libro va dirigido a aquellas personas que han com-pletado el programa de certificación CQRM; pero también lo pueden usar quienes estén familiarizados con los métodos básicos cuantitativos de investigación- hay algo para todos. Es un texto igualmente aplicable a nivel de segundo año de un MBA/MS o a nivel introductorio de un PhD. Los ejemplos que aparecen en el libro requieren de un conocimiento previo sobre el tema.Para obtener información adicional sobre el programa CQRM, diríjase a los siguientes sitios Web: www.iiper.org www.realoptionsvaluation.com

Modelación de Riesgos (Tercera Edición, Volumen 2 de 2). Aplicación de la Simulación de Monte Carlo, Análisis de Opciones Reales, Pronóstico Estocástico, Optimización de Portafolio, Análisis de Datos, Inteligencia de Negocios, y Modelación de Decisiones.

Modelación de Riesgos (Tercera Edición, Volumen 1 de 2). Aplicación de la Simulación de Monte Carlo, Análisis de Opciones Reales, Pronóstico Estocástico, Optimización de Portafolio, Análisis de Datos, Inteligencia de Negocios, y Modelación de Decisiones.

La Serie de Libros sobre el CQRM Aplicado expone cómo la analítica avanzada que figura en el programa de Certificación en Gestión Cuantitativa de Riesgos (CQRM), se puede aplicar a los problemas de negocios en la vida real. En el Volumen IV, demostramos cómo se pueden aplicar estas analíticas en el contexto de la Gestión de Riesgos Empresariales, utilizando los registros cualitativos de riesgos y ampliando los resultados por medio de los métodos analíticos cuantitativos.Se hace un énfasis en las aplicaciones pragmáticas con el fin de desmitificar los elementos inherentes al análisis de riesgos. Una caja negra continuará siendo una caja negra si nadie puede entender los conceptos a pesar de su poder y su aplicabilidad. Sólo hasta cuando los métodos de la caja negra se vuelven transparentes, para que los investigadores puedan entender, aplicar y convencer a otros de sus resultados, su valor agregado y la aplicabilidad, es que los enfoques recibirán una amplia atención. Esta transparencia se logra a través de las aplicaciones paso-a-paso de la modelación cuantitativa así como de la presentación de múltiples casos y de la discusión de las aplicaciones en la vida real.El presente libro va dirigido a aquellas personas que han completado el programa de certificación CQRM; pero también lo pueden usar quienes estén familiarizados con los métodos básicos cuantitativos de investigación- hay algo para todos. Es un texto igualmente aplicable a nivel de segundo año de un MBA/MS o a nivel introductorio de un PhD. Los ejemplos que aparecen en el libro requieren de un conocimiento previo sobre el tema.Para obtener información adicional sobre el programa CQRM, diríjase a los siguientes sitios Web: www.iiper.org www.realoptionsvaluation.com

The Applied CQRM Book Series showcases how the advanced analytics covered in the Certified in Quantitative Risk Management (CQRM) certification program can be applied to real-life business problems. In Volume V, we show how Credit, Market, Operational, and Liquidity (CMOL) Risks can be modeled using the CMOL software, Risk Simulator, and Modeling Toolkit. Pragmatic applications are emphasized in order to demystify the many elements inherent in risk analysis. A black box will remain a black box if no one can understand the concepts despite its power and applicability. It is only when the black box methods become transparent, so that researchers can understand, apply, and convince others of their results, value-add, and applicability, that the approaches will receive widespread attention. This transparency is achieved through step-by-step applications of quantitative modeling as well as through presenting multiple cases and discussing real-life applications. This book is targeted at those individuals who have completed the CQRM certification program but can also be used by anyone familiar with basic quantitative research methods--there is something for everyone. It is also applicable for use as a second-year MBA/MS-level or introductory PhD textbook. The examples in the book assume some prior knowledge of the subject matter. Additional information on the CQRM program can be obtained at: www.iiper.org www.realoptionsvaluation.com

The Applied CQRM Book Series showcases how the advanced analytics covered in the Certified in Quantitative Risk Management (CQRM) certification program can be applied to real-life business problems. In Volume III, we show how ROV's PEAT software can be used to evaluate a project's economics, simulate its uncertainties, run sensitivity analysis, and use their analytical properties for making strategic decisions. Pragmatic applications are emphasized in order to demystify the many elements inherent in risk analysis. A black box will remain a black box if no one can understand the concepts despite its power and applicability. It is only when the black box methods become transparent, so that researchers can understand, apply, and convince others of their results, value-add, and applicability, that the approaches will receive widespread attention. This transparency is achieved through step-by-step applications of quantitative modeling as well as presenting multiple cases and discussing real-life applications. This book is targeted at those individuals who have completed the CQRM certification program but can also be used by anyone familiar with basic quantitative research methods--there is something for everyone. It is also applicable for use as a second-year MBA/MS-level or introductory PhD textbook. The examples in the book assume some prior knowledge of the subject matter. Additional information on the CQRM program can be obtained at: www.iiper.org www.realoptionsvaluation.com

The Applied CQRM Book Series showcases how the advanced analytics covered in the Certified in Quantitative Risk Management (CQRM) certification program can be applied in real-life business problems. In Volume II, we show how Risk Simulator can be used to generate various probability distributions as well as how to interpret the results and use their analytical properties for making strategic decisions.Pragmatic applications are emphasized in order to demystify the many elements inherent in probability analysis. A black box will remain a black box if no one can understand the concepts despite its power and applicability. It is only when the black box methods become transparent, so that researchers can understand, apply, and convince others of their results, value-add, and applicability, that the approaches will receive widespread attention. This transparency is achieved through step-by-step applications of quantitative modeling as well as presenting multiple cases and discussing real-life applications. This book is targeted at those individuals who have completed the CQRM certification program but can also be used by anyone familiar with basic quantitative research methods--there is something for everyone. It is also applicable for use as a second-year MBA/MS-level or introductory PhD textbook. The examples in the book assume some prior knowledge of the subject matter. Additional information on the CQRM program can be obtained at: www.iiper.org www.realoptionsvaluation.com

The Applied CQRM Book Series showcases how the advanced analytics covered in the Certified in Quantitative Risk Management (CQRM) certification program can be applied to real-life business problems. In Volume IV, we show how these analytics can be applied in the context of Enterprise Risk Management, using both qualitative risk registers and extending the results using quantitative analytical methods.Pragmatic applications are emphasized in order to demystify the many elements inherent in risk analysis. A black box will remain a black box if no one can understand the concepts despite its power and applicability. It is only when the black box methods become transparent, so that researchers can understand, apply, and convince others of their results, value-add, and applicability, that the approaches will receive widespread attention. This transparency is achieved through step-by-step applications of quantitative modeling as well as presenting multiple cases and discussing real-life applications. This book is targeted at those individuals who have completed the CQRM certification program but can also be used by anyone familiar with basic quantitative research methods--there is something for everyone. It is also applicable for use as a second-year MBA/MS-level or introductory PhD textbook. The examples in the book assume some prior knowledge of the subject matter. Additional information on the CQRM program can be obtained at: www.iiper.org www.realoptionsvaluation.com

THIRD EDITION (2022) The Applied CQRM Book Series showcases how the advanced analytics covered in the Certified in Quantitative Risk Management (CQRM) certification program can be applied to real-life business problems. In Volume I, we show how Risk Simulator and ROV BizStats can be used to perform quantitative analysis in graduate and postgraduate research. Pragmatic applications are emphasized in order to demystify the many elements inherent in quantitative analysis. A statistical black box will remain a black box if no one can understand the concepts despite its power and applicability. It is only when the black box methods become transparent, so that researchers can understand, apply, and convince others of their results, value-add, and applicability, that the approaches will receive widespread attention. This transparency is achieved through step-by-step applications of quantitative modeling as well as presenting multiple cases and discussing real-life applications. This book is targeted at those individuals who have completed the CQRM certification program but can also be used by anyone familiar with basic quantitative research methods--there is some-thing for everyone. It is also applicable for use as a second-year MBA/MS-level or introductory PhD textbook. The examples in the book assume some prior knowledge of the subject matter. Additional information on the CQRM program can be obtained at: www.iiper.org www.realoptionsvaluation.com THE BASICSCentral Tendency, Spread, Skew, KurtosisProbability, Bayes' Theorem, Trees, Combination, PermutationClassical, Standard, P-Value, CICentral Limit TheoremType I-IV Errors, Sampling Biases>ANALYTICAL METHODST-Tests: Equal/Unequal/Paired Variance, F-Test, Z-TestANOVA, Blocked, Two-Way, ANCOVA, MANOVALinear/Nonlinear CorrelationNormality & Distributional Fitting: Kolmogorov-Smirnov, Chi-Square, Akaike Information Criterion, Anderson-Darling, Kuiper's, Schwarz/Bayes, Box-CoxNonparametrics: Runs, Wilcoxon, Mann-Whitney, Lilliefors, Q-Q, D'Agostino-Pearson, Shapiro-Wilk-Royston, Kruskal-Wallis, Mood's, Cochran's Q, Friedman'sInter/Intra-Rater Reliability, Consistency, Diversity, Internal/External Validity, PredictabilityCohen's Kappa, Cronbach's Alpha, Guttman's Lambda, Inter-Class Correlation, Kendall's W, Shannon-Brillouin-Simpson Diversity, Homogeneity, Grubbs Outlier, Mahalanobis, Linear & Quadratic Discriminant, Hannan-Quinn, Diebold-Mariano, Pesaran-Timmermann, Precision, Error ControlLinear/Nonlinear Multivariate RegressionMulticollinearity, HeteroskedasticityStructural Equation Modeling (SEM), Partial Least Squares (PLS)Endogeneity, Simultaneous Equations Methods, Two-Stage Least SquaresGranger Causality, Engle-Granger>ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (DATA SCIENCE)Bagging Linear BootstrapBagging Nonlinear BootstrapClassification and Regression Trees CARTCustom FitDimension Reduction Principal Component AnalysisDimension Reduction Factor AnalysisEnsemble Common FitEnsemble Complex FitEnsemble Time-SeriesGaussian Mix & K-Means SegmentationK-Nearest NeighborsLinear Fit ModelMultivariate Discriminant Analysis (Linear)Multivariate Discriminant Analysis (Quadratic)Neural Network (Cosine, Tangent, Hyperbolic)Logistic Binary ClassificationNormit-Probit Binary ClassificationPhylogenetic Trees & Hierarchical ClusteringRandom ForestSegmentation ClusteringSupport Vector Machines SVM