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Algorithmic Pricing And Competition
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Book Synopsis Algorithmic Pricing and Competition by : Stephanie Assad
Download or read book Algorithmic Pricing and Competition written by Stephanie Assad and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic theory provides ambiguous and conflicting predictions about the association between algorithmic pricing and competition. In this paper we provide the first empirical analysis of this relationship. We study Germany's retail gasoline market where algorithmic-pricing software became widely available by mid-2017, and for which we have access to comprehensive, high-frequency price data. Because adoption dates are unknown, we identify gas stations that adopt algorithmic-pricing software by testing for structural breaks in markers associated with algo-rithmic pricing. We find a large number of station-level structural breaks around the suspected time of large-scale adoption. Using this information we investigate the impact of adoption on outcomes linked to competition. Because station-level adoption is endogenous, we use brand headquarter-level adoption decisions as instruments. Our IV results show that adoption in-creases margins by 9%, but only in non-monopoly markets. Restricting attention to duopoly markets, we find that market-level margins do not change when only one of the two stations adopts, but increase by 28% in markets where both do. These results suggest that AI adoption has a significant effect on competition.
Book Synopsis Virtual Competition by : Ariel Ezrachi
Download or read book Virtual Competition written by Ariel Ezrachi and published by Harvard University Press. This book was released on 2016-11-14 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: “A fascinating book about how platform internet companies (Amazon, Facebook, and so on) are changing the norms of economic competition.” —Fast Company Shoppers with a bargain-hunting impulse and internet access can find a universe of products at their fingertips. But is there a dark side to internet commerce? This thought-provoking exposé invites us to explore how sophisticated algorithms and data-crunching are changing the nature of market competition, and not always for the better. Introducing into the policy lexicon terms such as algorithmic collusion, behavioral discrimination, and super-platforms, Ariel Ezrachi and Maurice E. Stucke explore the resulting impact on competition, our democratic ideals, our wallets, and our well-being. “We owe the authors our deep gratitude for anticipating and explaining the consequences of living in a world in which black boxes collude and leave no trails behind. They make it clear that in a world of big data and algorithmic pricing, consumers are outgunned and antitrust laws are outdated, especially in the United States.” —Science “A convincing argument that there can be a darker side to the growth of digital commerce. The replacement of the invisible hand of competition by the digitized hand of internet commerce can give rise to anticompetitive behavior that the competition authorities are ill equipped to deal with.” —Burton G. Malkiel, Wall Street Journal “A convincing case for the need to rethink competition law to cope with algorithmic capitalism’s potential for malfeasance.” —John Naughton, The Observer
Book Synopsis Virtual Competition by : Ariel Ezrachi
Download or read book Virtual Competition written by Ariel Ezrachi and published by Harvard University Press. This book was released on 2016-11-14 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: “A fascinating book about how platform internet companies (Amazon, Facebook, and so on) are changing the norms of economic competition.” —Fast Company Shoppers with a bargain-hunting impulse and internet access can find a universe of products at their fingertips. But is there a dark side to internet commerce? This thought-provoking exposé invites us to explore how sophisticated algorithms and data-crunching are changing the nature of market competition, and not always for the better. Introducing into the policy lexicon terms such as algorithmic collusion, behavioral discrimination, and super-platforms, Ariel Ezrachi and Maurice E. Stucke explore the resulting impact on competition, our democratic ideals, our wallets, and our well-being. “We owe the authors our deep gratitude for anticipating and explaining the consequences of living in a world in which black boxes collude and leave no trails behind. They make it clear that in a world of big data and algorithmic pricing, consumers are outgunned and antitrust laws are outdated, especially in the United States.” —Science “A convincing argument that there can be a darker side to the growth of digital commerce. The replacement of the invisible hand of competition by the digitized hand of internet commerce can give rise to anticompetitive behavior that the competition authorities are ill equipped to deal with.” —Burton G. Malkiel, Wall Street Journal “A convincing case for the need to rethink competition law to cope with algorithmic capitalism’s potential for malfeasance.” —John Naughton, The Observer
Book Synopsis Algorithmic Antitrust by : Aurelien Portuese
Download or read book Algorithmic Antitrust written by Aurelien Portuese and published by Springer Nature. This book was released on 2022-01-21 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are ubiquitous in our daily lives. They affect the way we shop, interact, and make exchanges on the marketplace. In this regard, algorithms can also shape competition on the marketplace. Companies employ algorithms as technologically innovative tools in an effort to edge out competitors. Antitrust agencies have increasingly recognized the competitive benefits, but also competitive risks that algorithms entail. Over the last few years, many algorithm-driven companies in the digital economy have been investigated, prosecuted and fined, mostly for allegedly unfair algorithm design. Legislative proposals aim at regulating the way algorithms shape competition. Consequently, a so-called “algorithmic antitrust” theory and practice have also emerged. This book provides a more innovation-driven perspective on the way antitrust agencies should approach algorithmic antitrust. To date, the analysis of algorithmic antitrust has predominantly been shaped by pessimistic approaches to the risks of algorithms on the competitive environment. With the benefit of the lessons learned over the last few years, this book assesses whether these risks have actually materialized and whether antitrust laws need to be adapted accordingly. Effective algorithmic antitrust requires to adequately assess the pro- and anti-competitive effects of algorithms on the basis of concrete evidence and innovation-related concerns. With a particular emphasis on the European perspective, this book brings together experts and scrutinizes on the implications of algorithmic antitrust for regulation and innovation.
Book Synopsis The Theory of Industrial Organization by : Jean Tirole
Download or read book The Theory of Industrial Organization written by Jean Tirole and published by MIT Press. This book was released on 1988-08-26 with total page 1482 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Theory of Industrial Organization is the first primary text to treat the new industrial organization at the advanced-undergraduate and graduate level. Rigorously analytical and filled with exercises coded to indicate level of difficulty, it provides a unified and modern treatment of the field with accessible models that are simplified to highlight robust economic ideas while working at an intuitive level. To aid students at different levels, each chapter is divided into a main text and supplementary section containing more advanced material. Each chapter opens with elementary models and builds on this base to incorporate current research in a coherent synthesis. Tirole begins with a background discussion of the theory of the firm. In Part I he develops the modern theory of monopoly, addressing single product and multi product pricing, static and intertemporal price discrimination, quality choice, reputation, and vertical restraints. In Part II, Tirole takes up strategic interaction between firms, starting with a novel treatment of the Bertrand-Cournot interdependent pricing problem. He studies how capacity constraints, repeated interaction, product positioning, advertising, and asymmetric information affect competition or tacit collusion. He then develops topics having to do with long term competition, including barriers to entry, contestability, exit, and research and development. He concludes with a "game theory user's manual" and a section of review exercises. Important Notice: The digital edition of this book is missing some of the images found in the physical edition.
Book Synopsis Algorithms, Collusion and Competition Law by : Steven Van Uytsel
Download or read book Algorithms, Collusion and Competition Law written by Steven Van Uytsel and published by Edward Elgar Publishing. This book was released on 2023-01-20 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is algorithmic collusion? This evaluative book provides an insight into tackling this important question for competition law, with contrasting critical perspectives, including theoretical, empirical, and doctrinal – the latter frequently from a comparative perspective. Bringing together scholarly discussion on algorithmic collusion, the book questions whether competition law is adeptly equipped to deal with its various facets.
Book Synopsis Algorithmic Pricing and Tacit Collusion by : Richard Steppe
Download or read book Algorithmic Pricing and Tacit Collusion written by Richard Steppe and published by . This book was released on 2018 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Competition and Regulation in the Data Economy by : Gintarè Surblytė-Namavičienė
Download or read book Competition and Regulation in the Data Economy written by Gintarè Surblytė-Namavičienė and published by Edward Elgar Publishing. This book was released on 2020-10-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This incisive book provides a much-needed examination of the legal issues arising from the data economy, particularly in the light of the expanding role of algorithms and artificial intelligence in business and industry. In doing so, it discusses the pressing question of how to strike a balance in the law between the interests of a variety of stakeholders, such as AI industry, businesses and consumers.
Book Synopsis Artificial Intelligence, Algorithmic Pricing and Collusion by : Emilio Calvano
Download or read book Artificial Intelligence, Algorithmic Pricing and Collusion written by Emilio Calvano and published by . This book was released on 2018 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pricing algorithms are increasingly replacing human decision making in real marketplaces. To inform the competition policy debate on possible consequences, we run experiments with pricing algorithms powered by Artificial Intelligence in controlled environments (computer simulations). In particular, we study the interaction among a number of Q-learning algorithms in the context of a workhorse oligopoly model of price competition with Logit demand and constant marginal costs. We show that the algorithms consistently learn to charge supra-competitive prices, without communicating with each other. The high prices are sustained by classical collusive strategies with a finite punishment phase followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand and to changes in the number of players.
Book Synopsis Algorithmic Pricing by : Emilio Calvano
Download or read book Algorithmic Pricing written by Emilio Calvano and published by . This book was released on 2018 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pricing decisions are increasingly in the “hands” of artificial algorithms. Scholars and competition authorities have voiced concerns that those algorithms are capable of sustaining collusive outcomes more effectively than human decision makers. If this is so, then our traditional policy tools for fighting collusion may have to be reconsidered. We discuss these issues by critically surveying the relevant law, economics and computer science literatures.
Book Synopsis Twenty Lectures on Algorithmic Game Theory by : Tim Roughgarden
Download or read book Twenty Lectures on Algorithmic Game Theory written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2016-08-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Download or read book The Ends Game written by Marco Bertini and published by MIT Press. This book was released on 2022-01-11 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: How companies like Dollar Shave Club and Rent the Runway rewrite the rules of commerce by pursuing outcomes rather than products and services. The seventh book in the Management on the Cutting Edge series—for business professionals looking to do deliver excellent customer service while maximizing value and revenue. Would you rather pay for healthcare or for better health? For school or education? For groceries or nutrition? A car or transportation? A theater performance or entertainment? In The Ends Game, Marco Bertini and Oded Koenigsberg describe how some firms are rewriting the rules of commerce: instead of selling the “means” (their products and services), they adopt innovative revenue models to pursue “ends” (actual outcomes). They examine companies such as: • Dollar Shave Club • Rent the Runway • Netflix • Spotify • Michelin • Adobe • Pearson • And many more! They show that paying by the pill, semester, food item, vehicle, or show does not necessarily reflect the value that customers actually derive from their purchases. Revenue models anchored on the ownership of products, they argue, are patently inferior.
Book Synopsis Algorithmic Collusion by : Karsten T. Hansen
Download or read book Algorithmic Collusion written by Karsten T. Hansen and published by . This book was released on 2020 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivated by their increasing prevalence, we study outcomes when competing sellers use machine learning algorithms to run real-time dynamic price experiments. These algorithms are often misspecified, ignoring the effect of factors outside their control, e.g. competitors' prices. We show that the long-run prices depend on the informational value (or signal to noise ratio) of price experiments: if low, the long-run prices are consistent with the static Nash equilibrium of the corresponding full information setting. However, if high, the long-run prices are supra-competitive -- the full information joint-monopoly outcome is possible. We show this occurs via a novel channel: competitors' algorithms' prices end up running correlated experiments. Therefore, sellers' misspecified models overestimate own price sensitivity, resulting in higher prices. We discuss the implications on competition policy.
Book Synopsis The Cambridge Handbook of the Law of Algorithms by : Woodrow Barfield
Download or read book The Cambridge Handbook of the Law of Algorithms written by Woodrow Barfield and published by Cambridge University Press. This book was released on 2020-11-05 with total page 1327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.
Book Synopsis The Theory of Collusion and Competition Policy by : Joseph E. Harrington, Jr.
Download or read book The Theory of Collusion and Competition Policy written by Joseph E. Harrington, Jr. and published by MIT Press. This book was released on 2017-11-16 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: A review of the theoretical research on unlawful collusion, focusing on the impact and optimal design of competition law and enforcement. Collusion occurs when firms in a market coordinate their behavior for the purpose of producing a supracompetitive outcome. The literature on the theory of collusion is deep and broad but most of that work does not take account of the possible illegality of collusion. Recently, there has been a growing body of research that explicitly focuses on collusion that runs afoul of competition law and thereby makes firms potentially liable for penalties. This book, by an expert on the subject, reviews the theoretical research on unlawful collusion, with a focus on two issues: the impact of competition law and enforcement on whether, how long, and how much firms collude; and the optimal design of competition law and enforcement. The book begins by discussing general issues that arise when models of collusion take into account competition law and enforcement. It goes on to consider game-theoretic models that encompass the probability of detection and penalties incurred when convicted, and examines how these policy instruments affect the frequency of cartels, cartel duration, cartel participation, and collusive prices. The book then considers the design of competition law and enforcement, examining such topics as the formula for penalties and leniency programs. The book concludes with suggested future lines of inquiry into illegal collusion.
Book Synopsis Machine Learning for Algorithmic Trading by : Stefan Jansen
Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
Book Synopsis Algorithmic Price Recommendations and Collusion by : Matthias Hunold
Download or read book Algorithmic Price Recommendations and Collusion written by Matthias Hunold and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates the collusive and competitive effects of algorithmic price recommendations on market outcomes. These recommendations are often non-binding and common in many markets, especially on online platforms. We develop a theoretical framework and derive two algorithms that recommend collusive pricing strategies. Utilizing a laboratory experiment, we find that sellers condition their prices on the recommendation of the algorithms. The algorithm with a soft punishment strategy lowers market prices and has a pro-competitive effect. The algorithm that recommends a subgame perfect equilibrium strategy increases the range of market outcomes, including more collusive ones. Variations in economic preferences lead to heterogeneous treatment effects and explain the results.
