Containing many results that are new, or which exist only in recent research articles, Interest Rate Modeling: Theory and Practice, 2nd Edition portrays the theory of interest rate modeling as a three-dimensional object of finance, mathematics, and computation. It introduces all models with financial-economical justifications, develops options along the martingale approach, and handles option evaluations with precise numerical methods. Features Presents a complete cycle of model construction and applications, showing readers how to build and use models Provides a systematic treatment of intriguing industrial issues, such as volatility and correlation adjustments Contains exercise sets and a number of examples, with many based on real market data Includes comments on cutting-edge research, such as volatility-smile, positive interest-rate models, and convexity adjustment New to the 2nd edition: volatility smile modeling; a new paradigm for inflation derivatives modeling; an extended market model for credit derivatives; a dual-curved model for the post-crisis interest-rate derivatives markets; and an elegant framework for the xVA.

The Regression Discontinuity (RD) design is one of the most popular and credible research designs for program evaluation and causal inference. This volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the RD literature, covering a wide range of methodological and practical topics. Some chapters touch on foundational methodological issues such as identification, interpretation, implementation, falsification testing, estimation and inference, while others focus on more recent and related topics such as identification and interpretation in a discontinuity-in-density framework, empirical structural estimation, comparative RD methods, and extrapolation. These chapters not only give new insights for current methodological and empirical research, but also provide new bases and frameworks for future work in this area. This volume contributes to the rapidly expanding RD literature by bringing together theoretical and applied econometricians, statisticians, and social, behavioural and biomedical scientists, in the hope that these interactions will further spark innovative practical developments in this important and active research area.

This volume presents new methods and applications in longitudinal data estimation methodology in applied economic. Featuring selected papers from the 2020 the International Conference on Applied Economics (ICOAE 2020) held virtually due to the corona virus pandemic, this book examines interdisciplinary topics such as financial economics, international economics, agricultural economics, marketing and management. Country specific case studies are also featured.

This book gives a thorough and systematic introduction to the latest research results about fuzzy decision-making method based on prospect theory. It includes eight chapters: Introduction, Intuitionistic fuzzy MADM based on prospect theory, QUALIFLEX based on prospect theory with probabilistic linguistic information, Group PROMETHEE based on prospect theory with hesitant fuzzy linguistic information, Prospect consensus with probabilistic hesitant fuzzy preference information, Improved TODIM based on prospect theory and the improved TODIM with probabilistic hesitant fuzzy information, etc. This book is suitable for the researchers in the fields of fuzzy mathematics, operations research, behavioral science, management science and engineering, etc. It is also useful as a textbook for postgraduate and senior-year undergraduate students of the relevant professional institutions of higher learning.

This book offers a series of statistical tests to determine if the "crowd out" problem, known to hinder the effectiveness of Keynesian economic stimulus programs, can be overcome by monetary programs. It concludes there are programs that can do this, specifically "accommodative monetary policy." They were not used to any great extent prior to the Quantitative Easing program in 2008, causing the failure of many fiscal stimulus programs through no fault of their own. The book includes exhaustive statistical tests to prove this point. There is also a policy analysis section of the book. It examines how effectively the Federal Reserve's anti-crowd out programs have actually worked, to the extent they were undertaken at all. It finds statistical evidence that using commercial and savings banks instead of investment banks when implementing accommodating monetary policy would have markedly improved their effectiveness. This volume, with its companion volume Why Fiscal Stimulus Programs Fail, Volume 2: Statistical Tests Comparing Monetary Policy to Growth, provides 1000 separate statistical tests on the US economy to prove these assertions.

This book scientifically tests the assertion that accommodative monetary policy can eliminate the "crowd out" problem, allowing fiscal stimulus programs (such as tax cuts or increased government spending) to stimulate the economy as intended. It also tests to see if natural growth in th economy can cure the crowd out problem as well or better. The book is intended to be the largest scale scientific test ever performed on this topic. It includes about 800 separate statistical tests on the U.S. economy testing different parts or all of the period 1960 - 2010. These tests focus on whether accommodative monetary policy, which increases the pool of loanable resources, can offset the crowd out problem as well as natural growth in the economy. The book, employing the best scientific methods available to economists for this type of problem, concludes accommodate monetary policy could have, but until the quantitative easing program, Federal Reserve efforts to accommodate fiscal stimulus programs were not large enough to offset more than 23% to 44% of any one year's crowd out problem. That provides the science part of the answer as to why accommodative monetary policy didn't accommodate: too little of it was tried. The book also tests whether other increases in loanable funds, occurring because of natural growth in the economy or changes in the savings rate can also offset crowd out. It concludes they can, and that these changes tend to be several times as effective as accommodative monetary policy. This book's companion volume Why Fiscal Stimulus Programs Fail explores the policy implications of these results.

This proceedings volume presents new methods and applications in applied economics with special interest in advanced cross-section data estimation methodology. Featuring select contributions from the 2019 International Conference on Applied Economics (ICOAE 2019) held in Milan, Italy, this book explores areas such as applied macroeconomics, applied microeconomics, applied financial economics, applied international economics, applied agricultural economics, applied marketing and applied managerial economics. International Conference on Applied Economics (ICOAE) is an annual conference that started in 2008, designed to bring together economists from different fields of applied economic research, in order to share methods and ideas. Applied economics is a rapidly growing field of economics that combines economic theory with econometrics, to analyze economic problems of the real world, usually with economic policy interest. In addition, there is growing interest in the field of applied economics for cross-section data estimation methods, tests and techniques. This volume makes a contribution in the field of applied economic research by presenting the most current research. Featuring country specific studies, this book is of interest to academics, students, researchers, practitioners, and policy makers in applied economics, econometrics and economic policy.

This book analyzes evolution of monetary policy in Rwanda since it was first implemented by the National Bank of Rwanda in 1964 when the bank was established. It contributes to the understanding of monetary policy which is formulation and implementation in different stages of development of a financial system that comprises the financial market (money market and capital market), financial intermediaries such as commercial banks, and the financial sector infrastructures such as payment systems and the credit reference bureau. The book breaks down applied empirical research on the assessment of key assumptions of a monetary targeting framework, namely the stability of money multiplier and money demand using econometrics of time series, through a number of case studies. Presenting a detailed empirical analysis of the monetary transmission mechanism, one of the most analyzed topics in central banks in advanced economies, this book is a valuable read for central bankers and other researchers of monetary policy, particularly in developing economies.

This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained.

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

This state-of-the-art account unifies material developed in journal articles over the last 35 years, with two central thrusts: It describes a broad class of system models that the authors call 'stochastic processing networks' (SPNs), which include queueing networks and bandwidth sharing networks as prominent special cases; and in that context it explains and illustrates a method for stability analysis based on fluid models. The central mathematical result is a theorem that can be paraphrased as follows: If the fluid model derived from an SPN is stable, then the SPN itself is stable. Two topics discussed in detail are (a) the derivation of fluid models by means of fluid limit analysis, and (b) stability analysis for fluid models using Lyapunov functions. With regard to applications, there are chapters devoted to max-weight and back-pressure control, proportionally fair resource allocation, data center operations, and flow management in packet networks. Geared toward researchers and graduate students in engineering and applied mathematics, especially in electrical engineering and computer science, this compact text gives readers full command of the methods.

This book explores new topics in modern research on empirical corporate finance and applied accounting, especially the econometric analysis of microdata. Dubbed "financial microeconometrics" by the author, this concept unites both methodological and applied approaches. The book examines how quantitative methods can be applied in corporate finance and accounting research in order to predict companies getting into financial distress. Presented in a clear and straightforward manner, it also suggests methods for linking corporate governance to financial performance, and discusses what the determinants of accounting disclosures are. Exploring these questions by way of numerous practical examples, this book is intended for researchers, practitioners and students who are not yet familiar with the variety of approaches available for data analysis and microeconometrics. "This book on financial microeconometrics is an excellent starting point for research in corporate finance and accounting. In my view, the text is positioned between a narrative and a scientific treatise. It is based on a vast amount of literature but is not overloaded with formulae. My appreciation of financial microeconometrics has very much increased. The book is well organized and properly written. I enjoyed reading it." Wolfgang Marty, Senior Investment Strategist, AgaNola AG

Advances in Austrian Economics is a research annual whose editorial policy is to publish original research articles on Austrian economics. Each volume attempts to apply the insights of Austrian economics and related approaches to topics that are of current interest in economics and cognate disciplines. Volume 21 exemplifies this focus by highlighting key research from the Austrian tradition of economics with other research traditions in economics and related areas.

First published in 2004, this is a rigorous but user-friendly book on the application of stochastic control theory to economics. A distinctive feature of the book is that mathematical concepts are introduced in a language and terminology familiar to graduate students of economics. The standard topics of many mathematics, economics and finance books are illustrated with real examples documented in the economic literature. Moreover, the book emphasises the dos and don'ts of stochastic calculus, cautioning the reader that certain results and intuitions cherished by many economists do not extend to stochastic models. A special chapter (Chapter 5) is devoted to exploring various methods of finding a closed-form representation of the value function of a stochastic control problem, which is essential for ascertaining the optimal policy functions. The book also includes many practice exercises for the reader. Notes and suggested readings are provided at the end of each chapter for more references and possible extensions.

The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.

The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms.

A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice. Introduction to Financial Models for Management and Planning, Second Edition enables professionals and students to learn how to develop and use computer-based models for financial planning. This volume provides critical tools for the financial toolbox, then shows how to use them tools to build successful models.

In this Element and its accompanying second Element, A Practical Introduction to Regression Discontinuity Designs: Extensions, Matias Cattaneo, Nicolas Idrobo, and Rociio Titiunik provide an accessible and practical guide for the analysis and interpretation of regression discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. In this Element, the authors discuss the foundations of the canonical Sharp RD design, which has the following features: (i) the score is continuously distributed and has only one dimension, (ii) there is only one cutoff, and (iii) compliance with the treatment assignment is perfect. In the second Element, the authors discuss practical and conceptual extensions to this basic RD setup.

The Super Bowl is the most watched sporting event in the United States. But what does participating in this event mean for the players, the halftime performers, and the cities who host the games? Is there an economic benefit from being a part of the Super Bowl and if so, how much? This Palgrave Pivot examines the economic consequences for those who participate in the Super Bowl. The book fills in gaps in the literature by examining the benefits and costs of being involved in the game. Previously, the literature has largely ignored the affect the game has had on the careers of the players, particularly the stars of the game. The economic benefit of being the halftime performer has not been considered in the literature at all. While there have been past studies about the economic impact on the cities who host of the game, this book will expand on previous research and update it with new data.

'Experiments in Organizational Economics' highlights the importance of replicating previous economic experiments. Replication enables experimental findings to be subjected to rigorous scrutiny. Despite this obvious advantage, direct replication remains relatively scant in economics. One possible explanation for this situation is that publication outlets favor novel work over tests of robustness. Readers will gain a better understanding of the role that replication plays in economic discovery as well as valuable insights into the robustness of previously reported findings.

Technical analysis points out that the best source of information to beat the market is the price itself. Introducing readers to technical analysis in a more succinct and practical way, Ramlall focuses on the key aspects, benefits, drawbacks, and the main tools of technical analysis. Chart Patterns, Point & Figure, Stochastics, Sentiment indicators, Elliot Wave Theory, RSI, R, Candlesticks and more are covered, including both the concepts and the practical applications. Also including programming technical analysis tools, this book is a valuable tool for both researchers and practitioners.

Advances in Econometrics is a research annual whose editorial policy is to publish original research articles that contain enough details so that economists and econometricians who are not experts in the topics will find them accessible and useful in their research. Volume 37 exemplifies this focus by highlighting key research from new developments in econometrics.

This book presents selected peer-reviewed contributions from the International Conference on Time Series and Forecasting, ITISE 2018, held in Granada, Spain, on September 19-21, 2018. The first three parts of the book focus on the theory of time series analysis and forecasting, and discuss statistical methods, modern computational intelligence methodologies, econometric models, financial forecasting, and risk analysis. In turn, the last three parts are dedicated to applied topics and include papers on time series analysis in the earth sciences, energy time series forecasting, and time series analysis and prediction in other real-world problems. The book offers readers valuable insights into the different aspects of time series analysis and forecasting, allowing them to benefit both from its sophisticated and powerful theory, and from its practical applications, which address real-world problems in a range of disciplines. The ITISE conference series provides a valuable forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.

This selection of Professor Dhrymes's major papers combines important contributions to econometric theory with a series of well-thought-out, skilfully-executed empirical studies. The theoretical papers focus on such issues as the general linear model, simultaneous equations models, distributed lags and ancillary topics. Most of these papers originated with problems encountered in empirical research. The applied studies deal with production function and productivity topics, demand for labour, arbitrage pricing theory, demand for housing and related issues. Featuring careful exposition of key techniques combined with relevant theory and illustrations of possible applications, this book will be welcomed by academic and professional economists concerned with the use of econometric techniques and their underlying theory.

Contemporary economists, when analyzing economic behavior of people, need to use the diversity of research methods and modern ways of discovering knowledge. The increasing popularity of using economic experiments requires the use of IT tools and quantitative methods that facilitate the analysis of the research material obtained as a result of the experiments and the formulation of correct conclusions. This proceedings volume presents problems in contemporary economics and provides innovative solutions using a range of quantitative and experimental tools. Featuring selected contributions presented at the 2018 Computational Methods in Experimental Economics Conference (CMEE 2018), this book provides a modern economic perspective on such important issues as: sustainable development, consumption, production, national wealth, the silver economy, behavioral finance, economic and non-economic factors determining the behavior of household members, consumer preferences, social campaigns, and neuromarketing. International case studies are also offered.