Commodities have become an important component of many investors' portfolios and the focus of much political controversy over the past decade. This book utilizes structural models to provide a better understanding of how commodities' prices behave and what drives them. It exploits differences across commodities and examines a variety of predictions of the models to identify where they work and where they fail. The findings of the analysis are useful to scholars, traders and policy makers who want to better understand often puzzling - and extreme - movements in the prices of commodities from aluminium to oil to soybeans to zinc.
This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.
Written by one of the leading experts in the field, this book focuses on the interplay between model specification, data collection, and econometric testing of dynamic asset pricing models. The first several chapters provide an in-depth treatment of the econometric methods used in analyzing financial time-series models. The remainder explores the goodness-of-fit of preference-based and no-arbitrage models of equity returns and the term structure of interest rates; equity and fixed-income derivatives prices; and the prices of defaultable securities. Singleton addresses the restrictions on the joint distributions of asset returns and other economic variables implied by dynamic asset pricing models, as well as the interplay between model formulation and the choice of econometric estimation strategy. For each pricing problem, he provides a comprehensive overview of the empirical evidence on goodness-of-fit, with tables and graphs that facilitate critical assessment of the current state of the relevant literatures. As an added feature, Singleton includes throughout the book interesting tidbits of new research. These range from empirical results (not reported elsewhere, or updated from Singleton's previous papers) to new observations about model specification and new econometric methods for testing models. Clear and comprehensive, the book will appeal to researchers at financial institutions as well as advanced students of economics and finance, mathematics, and science.
GETTING TO THE BOTTOM OF THE BOTTOM LINE Traditional cost management systems typically defeat their own purpose by leading corporations to make decisions that ultimately do not optimize performance. These systems are the foundation for decisions that are made throughout the corporation. In order for organizations to increase performance beyond current capabilities, a new approach is needed that addresses issues such as understanding the true impact of various actions on the bottom line-and eliminating methods that distort numbers and narrow options. Explicit Cost Dynamics (ECD) offers such an alternative, and this expertly written, revolutionary book provides an indispensable introduction to the subject. Informative and easy-to-read, Explicit Cost Dynamics: Provides an alternative view and understanding of the impact of costs, actions, and time on the bottom line of a corporation Explains how this new theory can lead to an overall profit maximization Shows that costs can be considered as either a function of activities performed, as a function of resources expended, or of time Shows that the difference between explicit dollars flowing into and out of a company is equal to the rate of change of cash . . . and much more to help CEOs, CFOs, controllers, cost managers, financial managers, and others involved in the decision-making process improve their organizations' overall bottom lines.
"We examine the relationships between credit default swap (CDS) premiums and bond yield spreads for nine emerging market sovereign borrowers. We find that these two measures of credit risk deviate considerably in the short run, due to factors such as liquidity and contract specifications, but we estimate a stable long-term equilibrium relationship for most countries. In particular, CDS premiums tend to move more than one-for-one with yield spreads, which we show is broadly consistent with the presence of a significant "cheapest-to-deliver" (CTD) option. In addition, we find a variety of cross-sectional evidence of a CTD option being incorporated into CDS premiums. In our analysis of the short-term dynamics, we find that CDS premiums often move ahead of the bond market. However, we also find that bond spreads lead CDS premiums for emerging market sovereigns more often than has been found for investment-grade corporate credits, consistent with the CTD option impeding CDS liquidity for our riskier set of borrowers. Furthermore, the CDS market is less likely to lead for sovereigns that have issued more bonds, suggesting that the relative liquidity of the two markets is a key determinant of where price discovery occurs"--Federal Reserve Board web site.
A new approach to dynamic allocation and pricing that blends dynamic paradigms from the operations research and management science literature with classical mechanism design methods. Dynamic allocation and pricing problems occur in numerous frameworks, including the pricing of seasonal goods in retail, the allocation of a fixed inventory in a given period of time, and the assignment of personnel to incoming tasks. Although most of these problems deal with issues treated in the mechanism design literature, the modern revenue management (RM) literature focuses instead on analyzing properties of restricted classes of allocation and pricing schemes. In this book, Alex Gershkov and Benny Moldovanu propose an approach to optimal allocations and prices based on the theory of mechanism design, adapted to dynamic settings. Drawing on their own recent work on the topic, the authors describe a modern theory of RM that blends the elegant dynamic models from the operations research (OR), management science, and computer science literatures with techniques from the classical mechanism design literature. Illustrating this blending of approaches, they start with well-known complete information, nonstrategic dynamic models that yield elegant explicit solutions. They then add strategic agents that are privately informed and then examine the consequences of these changes on the optimization problem of the designer. Their sequential modeling of both nonstrategic and strategic logic allows a clear picture of the delicate interplay between dynamic trade-offs and strategic incentives. Topics include the sequential assignment of heterogeneous objects, dynamic revenue optimization with heterogeneous objects, revenue maximization in the stochastic and dynamic knapsack model, the interaction between learning about demand and dynamic efficiency, and dynamic models with long-lived, strategic agents.
This paper uses an analytically tractable intertemporal framework for analyzing the dynamic pricing of a utility with an underdeveloped network (a typical case in most developing countries) facing a competitive fringe, short-run network adjustment costs, theft of service, and the threat of a retaliatory regulatory review that is increasing with the price it charges. This simple dynamic optimization model yields a number of powerful policy insights and conclusions. Under a variety of plausible assumptions (in the context of developing countries) the utility will find its long-run profits enhanced if it exercises restraint in the early stages of network development by holding price below the limit defined by the unit costs of the fringe. The utility's optimal price gradually converges toward the limit price as its network expands. Moreover, when the utility is threatened with retaliatory regulatory intervention, it will generally have incentives to restrain its pricing behavior. These findings have important implications for the design of post-privatization regulatory governance in developing countries.
The world of pricing has been changing at a fast pace. There has been a development of new dynamic pricing strategies, an explosion of new pricing tactics, and a focus on smarter buyers. This book focuses on those developments and highlights new perspectives for pricing strategies.
