Download or read book Dynamic Learning and Pricing with Model Misspecification written by Mila Nambiar and published by . This book was released on 2020 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study a multi-period dynamic pricing problem with contextual information where the seller uses a misspecified demand model. The seller sequentially observes past demand, updates model parameters, and then chooses the price for the next period based on time-varying features. We show that model misspecification leads to correlation between price and prediction error of demand per period, which in turn leads to inconsistent price elasticity estimate and hence suboptimal pricing decisions. We propose a ``random price shock'' (RPS) algorithm that dynamically generates randomized price shocks to estimate price elasticity while maximizing revenue. We show that the RPS algorithm has strong theoretical performance guarantees, that it is robust to model misspecification, and that it can be adapted to a number of business settings, including (1) when the feasible price set is a price ladder, and (2) when the contextual information is not IID. We also perform offline simulations gauging the performance of RPS on a large fashion retail dataset, and find that is expected to earn 8~20% more revenue on average than competing algorithms that do not account for price endogeneity.
Download or read book On the Surprising Sufficiency of Linear Models for Dynamic Pricing with Demand Learning written by Omar Besbes and published by . This book was released on 2014 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider a multi-period single product pricing problem with an unknown demand curve. The seller's objective is to adjust prices in each period so as to maximize cumulative expected revenues over a given finite time horizon; in doing so, the seller needs to resolve the tension between learning the unknown demand curve and maximizing earned revenues. The main question that we investigate is the following: how large of a revenue loss is incurred if the seller uses a simple parametric model which differs significantly (i.e., is misspecified) relative to the underlying demand curve. This "price of misspecification'' is expected to be significant if the parametric model is overly restrictive. Somewhat surprisingly, we show (under reasonably general conditions) that this may not be the case.
Download or read book The Elements of Joint Learning and Optimization in Operations Management written by Xi Chen and published by Springer Nature. This book was released on 2022-09-20 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.
Download or read book Revenue Management and Pricing Analytics written by Guillermo Gallego and published by Springer. This book was released on 2019-08-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: “There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available.” Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. “The book by Gallego and Topaloglu provides a fresh, up-to-date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in-depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it." Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. “This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field.” Robert L. Phillips, Director of Pricing Research at Amazon “At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference.” Richard Ratliff, Research Scientist at Sabre “This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers.” Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK.
Download or read book Innovative Technology at the Interface of Finance and Operations written by Volodymyr Babich and published by Springer Nature. This book was released on 2022-06-09 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the challenges and opportunities arising from an assortment of technologies as they relate to Operations Management and Finance. It contains primers on operations, finance, and their interface. Innovative technologies and new business models enabled by those technologies are changing the practice and the theory of Operations Management and Finance, as well as their interface. These technologies and business models include Big Data and Analytics, Artificial Intelligence, Machine Learning, Blockchain, IoT, 3D printing, sharing platforms, crowdfunding, and crowdsourcing. The book will be an attractive choice for PhD-level courses and for self-study.
Download or read book Uncertainty Within Economic Models written by Lars Peter Hansen and published by World Scientific. This book was released on 2014-09-09 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by Lars Peter Hansen (Nobel Laureate in Economics, 2013) and Thomas Sargent (Nobel Laureate in Economics, 2011), Uncertainty within Economic Models includes articles adapting and applying robust control theory to problems in economics and finance. This book extends rational expectations models by including agents who doubt their models and adopt precautionary decisions designed to protect themselves from adverse consequences of model misspecification. This behavior has consequences for what are ordinarily interpreted as market prices of risk, but big parts of which should actually be interpreted as market prices of model uncertainty. The chapters discuss ways of calibrating agents' fears of model misspecification in quantitative contexts.
Download or read book Robustness written by Lars Peter Hansen and published by Princeton University Press. This book was released on 2016-06-28 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
Download or read book Nonlinear Oligopolies written by Gian Italo Bischi and published by Springer Science & Business Media. This book was released on 2009-12-01 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest trends, methods and results in nonlinear dynamics with a special focus on oligopolies. It contains a number of technical appendices that summarize techniques of global dynamics not easily accessible elsewhere.
Download or read book Recursive Macroeconomic Theory written by Lars Ljungqvist and published by MIT Press. This book was released on 2004 with total page 1120 pages. Available in PDF, EPUB and Kindle. Book excerpt: A significant new edition of a text that offers both tools and sample applications; extensive revisions and seven new chapters improve and expand upon the original treatment.
Download or read book The Behavioral Foundations of Model Misspecification written by Aislinn Bohren and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we link two common approaches to modeling how agents distort beliefs: (i) defining an updating rule that maps each signal realization to a subjective posterior, and (ii) Bayesian learning with a misspecified model. Each approach has relative advantages: updating rules have a more transparent link to the underlying bias being modeled and are identifiable from belief data, while misspecified models are 'complete,' in that no further assumptions on belief formation are necessary to analyze the model, and have general solution concepts and convergence results. Our main result shows that any misspecified model can be decomposed into an updating rule and another object -- a forecast -- which captures how the agent forecasts future beliefs. Moreover, we derive necessary and sufficient conditions for a forecast and updating rule to be jointly represented by a misspecified model, establish that this representation is unique, and construct it. These conditions characterize all of the belief formation implications implicit in the misspecified model approach. Finally, we consider two natural ways to select forecasts: introspection-proofness and naive consistency, and derive when a representation with each type of forecast exists.
Download or read book Dynamics Games and Science I written by Mauricio Matos Peixoto and published by Springer Science & Business Media. This book was released on 2011-03-29 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamics, Games and Science I and II are a selection of surveys and research articles written by leading researchers in mathematics. The majority of the contributions are on dynamical systems and game theory, focusing either on fundamental and theoretical developments or on applications to modeling in biology, ecomonics, engineering, finances and psychology. The papers are based on talks given at the International Conference DYNA 2008, held in honor of Mauricio Peixoto and David Rand at the University of Braga, Portugal, on September 8-12, 2008. The aim of these volumes is to present cutting-edge research in these areas to encourage graduate students and researchers in mathematics and other fields to develop them further.
Download or read book Sunspots and Non Linear Dynamics written by Kazuo Nishimura and published by Springer. This book was released on 2016-12-03 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state-of-the-art in non-linear dynamics and sunspots. These two topics have been the core of an international conference on instability and public policies in a globalized world, organized at Aix-Marseille School of Economics and GREQAM in honor of Jean-Michel Grandmont. He has made significant contributions on general equilibrium theory, monetary theory, learning, aggregation, non-linear dynamics and sunspots. This book assembles contributions by Jean-Michel Grandmont's colleagues, students and friends that have been influenced by his works and that are at the frontier of research in this domain today.
Download or read book Online Learning and Pricing for Multiple Products with Reference Price Effects written by Sheng Ji and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the dynamic pricing problem of a monopolist seller who sells a set of mutually substitutable products over a finite time horizon. Customer demand is sensitive to the price of each individual product and the reference price which is formed from a comparison among the prices of all products. To maximize the total expected profit, the seller needs to determine the selling price of each product and also selects a reference product (to be displayed) that affects the consumer's reference price. However, the seller initially knows neither the demand function nor the customer's reference price, but can learn them from past observations on the fly. As such, the seller faces the classical trade-off between exploration (learning the demand function and reference price) and exploitation (using what has been learned thus far to maximize revenue). We propose a dynamic learning-and-pricing algorithm that integrates iterative least squares estimation and bandit control techniques in a seamless fashion. We show that the cumulative regret, i.e., the expected revenue loss caused by not using the optimal policy over $T$ periods, is upper bounded by $O((n^2+n) sqrt{T} log T)$, which is optimal up to a logarithmic factor in terms of the time horizon $T$ and polynomially scaling with the number of products $n$. We also establish the regret lower bound (for any learning policies) to be $ Omega(n^{1.5} sqrt{T})$. We then generalize our analysis to a more general demand model. Finally, our algorithm performs consistently well numerically, outperforming an exploration-exploitation benchmark. We also identify an interesting ``loss-leader'' phenomenon in our computational study.
Download or read book Stability and Robustness in Misspecified Learning Models written by Mira Frick and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Rethinking Expectations written by Roman Frydman and published by Princeton University Press. This book was released on 2013-01-23 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book originated from a 2010 conference marking the fortieth anniversary of the publication of the landmark "Phelps volume," Microeconomic Foundations of Employment and Inflation Theory, a book that is often credited with pioneering the currently dominant approach to macroeconomic analysis. However, in their provocative introductory essay, Roman Frydman and Edmund Phelps argue that the vast majority of macroeconomic and finance models developed over the last four decades derailed, rather than built on, the Phelps volume's "microfoundations" approach. Whereas the contributors to the 1970 volume recognized the fundamental importance of according market participants' expectations an autonomous role, contemporary models rely on the rational expectations hypothesis (REH), which rules out such a role by design. The financial crisis that began in 2007, preceded by a spectacular boom and bust in asset prices that REH models implied could never happen, has spurred a quest for fresh approaches to macroeconomic analysis. While the alternatives to REH presented in Rethinking Expectations differ from the approach taken in the original Phelps volume, they are notable for returning to its major theme: understanding aggregate outcomes requires according expectations an autonomous role. In the introductory essay, Frydman and Phelps interpret the various efforts to reconstruct the field--some of which promise to chart its direction for decades to come. The contributors include Philippe Aghion, Sheila Dow, George W. Evans, Roger E. A. Farmer, Roman Frydman, Michael D. Goldberg, Roger Guesnerie, Seppo Honkapohja, Katarina Juselius, Enisse Kharroubi, Blake LeBaron, Edmund S. Phelps, John B. Taylor, Michael Woodford, and Gylfi Zoega.
Download or read book Empirical Dynamic Asset Pricing written by Kenneth J. Singleton and published by Princeton University Press. This book was released on 2009-12-13 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Dynamic Pricing and Demand Learning with Limited Price Experimentation written by Wang Chi Cheung and published by . This book was released on 2017 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a dynamic pricing problem where the demand function is not known a priori, price experimentation can be used as a demand learning tool. Existing literature usually assumes no constraint on price changes, but in practice sellers often face business constraints that prevent them from conducting extensive experimentation. We consider a dynamic pricing model where the demand function is unknown but belongs to a known finite set. The seller is allowed to make at most m price changes during T periods. The objective is to minimize the worst case regret, i.e., the expected total revenue loss compared to a clairvoyant who knows the demand distribution in advance. We demonstrate a pricing policy that incurs a regret of O(log^(m) T), or m iterations of the logarithm. Furthermore, we describe an implementation at Groupon, a large e-commerce marketplace for daily deals. The field study shows significant impact on revenue and bookings.
