Rationality, Irrationality and Escalating Behavior in Lowest Unique Bid Auctions

Information technology has revolutionized the traditional structure of markets. The removal of geographical and time constraints has fostered the growth of online auction markets, which now include millions of economic agents worldwide and annual transaction volumes in the billions of dollars. Here, we analyze bid histories of a little studied type of online auctions – lowest unique bid auctions. Similarly to what has been reported for foraging animals searching for scarce food, we find that agents adopt Lévy flight search strategies in their exploration of “bid space”. The Lévy regime, which is characterized by a power-law decaying probability distribution of step lengths, holds over nearly three orders of magnitude. We develop a quantitative model for lowest unique bid online auctions that reveals that agents use nearly optimal bidding strategies. However, agents participating in these auctions do not optimize their financial gain. Indeed, as long as there are many auction participants, a rational profit optimizing agent would choose not to participate in these auction markets

Multiagent model and mean field theory of complex auction dynamics

Acknowledgements We are grateful to Ms Yinan Zhao for providing the data and to Yuzhong Chen and Cancan Zhou for discussions and suggestions. This work was supported by ARO under Grant No. W911NF-14-1-0504 and by NSFC under Grants Nos. 11275003 and 61174165. The visit of QC to Arizona State University was partially sponsored by the State Scholarship Fund of China.Peer reviewedPublisher PD

Lévy flights in human behavior and cognition

Lévy flights represent the best strategy to randomly search for a target in an unknown environment, and have been widely observed in many animal species. Here, we inspect and discuss recent results concerning human behavior and cognition. Different studies have shown that human mobility can be described in terms of Lévy flights, while fresh evidence indicates that the same pattern accounts for human mental searches in online gambling sites. Thus, Lévy flights emerge as a unifying concept with broad cross-disciplinary implications. We argue that the ubiquity of such a pattern, both in behavior and cognition, suggests that the brain regions responsible for this behavior are likely to be evolutionarily old (i.e. no frontal cortex is involved), and that fMRI techniques might help to confirm this hypothesis

The Twitter of Babel: Mapping World Languages through Microblogging Platforms

Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the enormous amount of digital data produced by human activities. Although a characterization of several aspects of our societies is emerging from the data revolution, a number of questions concerning the reliability and the biases inherent to the big data “proxies” of social life are still open. Here, we survey worldwide linguistic indicators and trends through the analysis of a large-scale dataset of microblogging posts. We show that available data allow for the study of language geography at scales ranging from country-level aggregation to specific city neighborhoods. The high resolution and coverage of the data allows us to investigate different indicators such as the linguistic homogeneity of different countries, the touristic seasonal patterns within countries and the geographical distribution of different languages in multilingual regions. This work highlights the potential of geolocalized studies of open data sources to improve current analysis and develop indicators for major social phenomena in specific communities

The Bidder’s Curse

We employ a novel approach to identify overbidding in auctions. We compare online auction prices to fixed prices for the same item on the same webpage. In detailed data on auctions of a board game, 42 percent of auctions exceed the simultaneous fixed price. The result replicates in a broad cross-section of auctions (48 percent overbidding). A small fraction of overbidders, 17 percent of bidders, suffices to generate the large fraction of auctions with overbidding. We show that the observed behavior is inconsistent with rational behavior, even allowing for uncertainty about prices and switching costs, since the expected auction price also exceeds the fixed price. Limited attention best explains our results

In Praise of Investor Irrationality

How should a market filled with investors who chronically make bad investments, but is nevertheless efficient, be regulated? A growing body of evidence suggests that this is the state of most securities markets; investors rely on cognitive processes that produce systematically bad choices, and yet the market remains largely efficient. In fact, cognitive errors might be essential to their efficient operation. Even investors who make systematic errors also often possess real and unique information that can contribute to accurate pricing of securities. If such investors became mindful of their limited ability to distinguish between real information and erroneous information, they would decline to rely on their beliefs to invest and would thereby withhold private information from the market. Over-confidence on the part of these investors leads them to trade anyway. This over-confidence provides market liquidity, but more importantly, provides the market with the private information that individual investors possess (but should, rationally, withhold). Hence, reforms designed to save investors from the costs of their cognitive errors would reduce market liquidity and deprive the market of valuable information. In short, markets need irrationality

In Praise of Investor Irrationality

How should a market filled with investors who chronically make bad investments, but is nevertheless efficient, be regulated? A growing body of evidence suggests that this is the state of most securities markets; investors rely on cognitive processes that produce systematically bad choices, and yet the market remains largely efficient. In fact, cognitive errors might be essential to their efficient operation. Even investors who make systematic errors also often possess real and unique information that can contribute to accurate pricing of securities. If such investors became mindful of their limited ability to distinguish between real information and erroneous information, they would decline to rely on their beliefs to invest and would thereby withhold private information from the market. Over-confidence on the part of these investors leads them to trade anyway. This over-confidence provides market liquidity, but more importantly, provides the market with the private information that individual investors possess (but should, rationally, withhold). Hence, reforms designed to save investors from the costs of their cognitive errors would reduce market liquidity and deprive the market of valuable information. In short, markets need irrationality

Behavioral Antitrust

Competition policy is entering a new age. Interest in competition laws has increased world-wide, and the United States no longer holds a monopoly on antitrust policy. In the aftermath of the financial crisis, the question for competition authorities is whether and to what extent does bounded rationality, self-interest and willpower matter. This article explores how the behavioral economics literature will advance competition policy. With increasing interest in the United States and abroad in the implications of behavioral economics for competition policy, this Article first provides an overview of behavioral economics. It next discusses how the assumption of rational, self-interested profit-maximizers became so embedded in competition policy. The Article then discusses to what extent the behavioral economics literature can inform antitrust policies, and provides several recommendations related to the practical application of behavioral economics to competition policy going forward