Dynamic models of advertising competition

The dynamic modelling and analysis of advertising competition continues to be a topic of importance to scholars and practitioners. The second edition of this text reviews empirical and analytical research on the topic and extends the research through analytical and numerical investigation. Three types of ...

Asset pricing

discrete time approach

The theory of asset pricing has grown markedly more sophisticated since the early 1980s, with the application of powerful mathematical tools such as probability theory, stochastic processes and numerical analysis. The main goal of this text is to provide a systematic exposition, with practical applications ...

General equilibrium foundations of finance

structure of incomplete markets models

The purpose of this text is to give a sound economic foundation of finance based on the general equilibrium model with incomplete markets which embodies the famous CAPM as an important special case. This goal is achieved by giving reasonable restrictions on the agents' characteristics ...

Quantitative models for performance evaluation and benchmarking

data development analysis with spreadsheets and DEA Excel solver

It is difficult to evaluate an organization's performance when there are multiple inputs and multiple outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. This work introduces DEA as ...

The theory of search games and rendezvous

Search Theory is one of the classic methodological disciplines in operations research and applied mathematics. It deals with the problem faced by a searcher who wishes to minimize the time required to find a hidden object. Traditionally, the target of the search is assigned to ...

Value-at-risk

theory and practice

Value-at-risk (VaR) is a measure of market risk that has been widely adopted since the mid-1990s for use on trading floors. This is the first advanced book published on VaR. It describes how to design, implement, and use scalable production VaR measures on actual trading ...

Quantitative methods for trading and investment

This much-needed book, from a selection of top international experts, fills a gap by providing a manual of applied quantitative financial analysis. It focuses on advanced empirical methods for modelling financial markets in the context of practical financial applications. Data, software and techniques specifically aligned ...

Bayesian econometrics

Researchers in many fields are increasingly finding the Bayesian approach to statistics to be an attractive one. This book introduces the reader to the use of Bayesian methods in the field of econometrics at the advanced undergraduate or graduate level. The book is self-contained and ...

Elements of financial risk management

Value-at-Risk has emerged as the standard tool for measuring and reporting financial market risk. More than 80 commercial vendors offer enterprise or trading risk management systems that provide VAR-like measures. Risk managers are therefore often left with the daunting task of having to choose from ...

Dynamic programming in economics

Dynamic Programming in Economics is an outgrowth of a course intended for students in the first year PhD program and for researchers in Macroeconomics Dynamics. It can be used by students and researchers in Mathematics as well as in Economics. The purpose of Dynamic Programming ...

Life-cycle costing

using activity-based costing and Monte Carlo methods to manage future costs and risks

1. Introduction. What Does It Cost? .The Role of Life-Cycle Costing. Why Activity-Based Life-Cycle Costing? Notes. 2. Basics of Life-Cycle Costing. What Is a Life Cycle? What Is a Cost? Four Ways of LCC. Notes. 3. Uncertainty Analysis and Risk Management.What are Risk and ...

Modelling trends and cycles in economic time series

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to ...

Weak convergence of financial markets

The book provides an overview of weak convergence of stochastic processes and its application to the study of financial markets. Split into three parts, the first recalls the mathematics of stochastic processes and stochastic calculus with special emphasis on contiguity properties and weak convergence of ...

Money demand in Europe

an empirical approach

The EURO has now been in place for more than two years, but only the future will tell if the ECB can manage the EURO currency in the long- term. This book discusses the economic principals underlying the demand for money, and the possibilities to ...

Attractors, bifurcations & chaos

nonlinear phenomena in economics

The first part of this book is an introduction to the mathematical methods of modern nonlinear dynamics. It deals with differential equations, ordinary and partial, iterated maps, and bifurcation theory. The second part focuses applications to economics and regional science. Topics such as business cycles ...

Econometric analysis of count data

Proper count data probability models allow for rich inferences, both with respect to the stochastic count process that generated the data, and with respect to predicting the distribution of outcomes. The book starts with a presentation of the benchmark Poisson regression model. Alternative models address ...

Empirical modeling of the economy and the environment

Eds. Cristoph Böhringer abd Andreas Löscher The papers presented in this volume address a wide range of policy themes in the context of environmental regulation. Investigated issues include the interaction between environmental regulation and economic growth, international competitiveness, structural change, pollution leakage, technological innovation, tax ...

Semiparametric regression for the applied econometrician

This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples include estimation of Engel curves and equivalence scales, scale economies, semiparametric Cobb-Douglas, translog and CES cost functions, household gasoline consumption, hedonic housing prices, option prices and state price ...

Applied time series modelling and forecasting

A time series is a sequence of numerical data in which each item is associated with a particular instant in time. Examples of time series include: monthly unemployment figures, weekly measures of money supply and daily closing prices of stock indices. This text covers time ...

Satisficing games and decision making

with applications to engineering and computer science

In our day-to-day lives we constantly make decisions which are simply #good enough# rather than optimal. Most computer-based decision making algorithms, on the other hand, doggedly seek only the optimal solution based on rigid criteria and reject any others. In this book, Professor Stirling outlines ...