Statistical Arbitrage Mining for Display Advertising

We study and formulate arbitrage in display advertising. Real-Time Bidding (RTB) mimics stock spot exchanges and utilises computers to algorithmically buy display ads per impression via a real-time auction. Despite the new automation, the ad markets are still informationally inefficient due to the heavily fragmented marketplaces. Two display impressions with similar or identical effectiveness (e.g., measured by conversion or click-through rates for a targeted audience) may sell for quite different prices at different market segments or pricing schemes. In this paper, we propose a novel data mining paradigm called Statistical Arbitrage Mining (SAM) focusing on mining and exploiting price discrepancies between two pricing schemes. In essence, our SAMer is a meta-bidder that hedges advertisers' risk between CPA (cost per action)-based campaigns and CPM (cost per mille impressions)-based ad inventories; it statistically assesses the potential profit and cost for an incoming CPM bid request against a portfolio of CPA campaigns based on the estimated conversion rate, bid landscape and other statistics learned from historical data. In SAM, (i) functional optimisation is utilised to seek for optimal bidding to maximise the expected arbitrage net profit, and (ii) a portfolio-based risk management solution is leveraged to reallocate bid volume and budget across the set of campaigns to make a risk and return trade-off. We propose to jointly optimise both components in an EM fashion with high efficiency to help the meta-bidder successfully catch the transient statistical arbitrage opportunities in RTB. Both the offline experiments on a real-world large-scale dataset and online A/B tests on a commercial platform demonstrate the effectiveness of our proposed solution in exploiting arbitrage in various model settings and market environments.Comment: In the proceedings of the 21st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2015

A Model of Vertical Oligopolistic Competition

This paper develops a model of successive oligopolies with endogenous market entry, allowing for varying degrees of product differentiation and entry costs in both markets. Our analysis shows that the downstream conditions dominate the overall profitability of the two-tier structure while the upstream conditions mainly affect the distribution of profits. We compare the welfare effects of upstream versus downstream deregulation policies and show that the impact of deregulation may be overvalued when ignoring feedback effects from the other market. Furthermore, we analyze how different forms of vertical restraints influence the endogenous market structure and show when they are welfare enhancing

Does \u2018bigger\u2019mean \u2018better\u2019? Pitfalls and shortcuts associated with big data for social research

\u2018Big data is here to stay.\u2019 This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results \u2018obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting

License prices for financially constrained firms

It is often alleged that high auction prices inhibit service deployment. We investigate this claim under the extreme case of financially constrained bidders. If demand is just slightly elastic, auctions maximize consumer surplus if consumer surplus is a convex function of quantity (a common assumption), or if consumer surplus is concave and the proportion of expenditure spent on deployment is greater than one over the elasticity of demand. The latter condition appears to be true for most of the large telecom auctions in the US and Europe. Thus, even if high auction prices inhibit service deployment, auctions appear to be optimal from the consumers’ point of view

Arguably big biology: Sociology, spatiality and the knockout mouse project

© 2013 copyright Palgrave MacmillanThis is a post-peer-review, pre-copyedit version of an article published in BioSocieties. The definitive publisher-authenticated version BioSocieties, 2013, Vol. 8, pp. 417-431 is available online at: http://www.palgrave-journals.com/biosoc/journal/v8/n4/full/biosoc201325a.htmlFollowing the completion of the Human Genome Project (HGP), a critical challenge has been how to make biological sense of the amassed sequence data and translate this into clinical applications. A range of large biological research projects, as well as more distributed experimental collaborations, are seeking to realise this through translational research initiatives and postgenomic approaches. Drawing on interviews with key participants, this article explores the biological assumptions, sociological challenges and spatial imaginaries at play in arguments around one of these developments, which is using genetically altered mice to understand gene function. The knockout mouse project (KOMP) is a large-scale initiative in functional genomics, seeking to produce a ‘knockout mouse’ for each gene in the mouse’s genome, which can then be used to answer questions about gene function in mammals. KOMP is frequently framed as one successor to the HGP, emblematic of the ambitions of internationally coordinated biological research. However, the development of new technologies for generating and managing genetically altered mice, alongside the challenge of asking biologically meaningful questions of vast numbers of animals, is creating new frictions in this extension and intensification of biological research practices. This article introduces two separate approaches to the future of international research using mutant mice as stakeholders to negotiate the biological, sociological and spatial challenges of collaboration. The first centres on the directed research practices and sociological assumptions of KOMP, as individual researchers are reorganised around shared animals, databases and infrastructures. The second highlights an alternative vision of the future of biomedical research, using distributed management to enhance the sensitivities and efficiencies of existing experimental practices over space. These exemplify two different tactics in the organisation of an ‘arguably’ big biology. They also critically embody different sociological and spatial imaginaries for the collaborative practices of international translational research

Social Interactions vs Revisions, What is important for Promotion in Wikipedia?

In epistemic community, people are said to be selected on their knowledge contribution to the project (articles, codes, etc.) However, the socialization process is an important factor for inclusion, sustainability as a contributor, and promotion. Finally, what does matter to be promoted? being a good contributor? being a good animator? knowing the boss? We explore this question looking at the process of election for administrator in the English Wikipedia community. We modeled the candidates according to their revisions and/or social attributes. These attributes are used to construct a predictive model of promotion success, based on the candidates's past behavior, computed thanks to a random forest algorithm. Our model combining knowledge contribution variables and social networking variables successfully explain 78% of the results which is better than the former models. It also helps to refine the criterion for election. If the number of knowledge contributions is the most important element, social interactions come close second to explain the election. But being connected with the future peers (the admins) can make the difference between success and failure, making this epistemic community a very social community too

Presynaptic actions of 4-Aminopyridine and γ-aminobutyric acid on rat sympathetic ganglia in vitro

Responses to bath-applications of 4-aminopyridine (4-AP) and -aminobutyric acid (GABA) were recorded intracellularly from neurones in the rat isolated superior cervical ganglion. 4-aminopyridine (0.1–1.0 mmol/l) usually induced spontaneous action potentials and excitatory postsynaptic potentials (EPSPs), which were blocked by hexamethonium. Membrane potential was unchanged; spike duration was slightly increased. Vagus nerve B-and C-fibre potentials were prolonged. In 4-AP solution (0.1–0.3 mmol/l), GABA (0.1 mmol/l), 3-aminopropanesulphonic acid or muscimol evoked bursts of spikes and EPSPs in addition to a neuronal depolarization. These bursts, which were not elicited by glycine, glutamate, taurine or (±)-baclofen, were completely antagonised by hexamethonium, tetrodotoxin or bicuculline methochloride. It is concluded that: (a) 4-AP has a potent presynaptic action on sympathetic ganglia; (b) presynaptic actions of GABA can be recorded postsynaptically in the presence of 4-AP; and (c) the presynaptic GABA-receptors revealed in this condition are similar to those on the postsynaptic membrane

Big data: Finders keepers, losers weepers?

This article argues that big data’s entrepreneurial potential is based not only on new technological developments that allow for the extraction of non-trivial, new insights out of existing data, but also on an ethical judgment that often remains implicit: namely the ethical judgment that those companies that generate these new insights can legitimately appropriate (the fruits of) these insights. As a result, the business model of big data companies is essentially founded on a libertarian-inspired ‘finders, keepers’ ethic. The article argues, next, that this presupposed ‘finder, keepers’ ethic is far from unproblematic and relies itself on multiple unconvincing assumptions. This leads to the conclusion that the conduct of companies working with big data might lack ethical justification

Towards a synthesized critique of neoliberal biodiversity conservation

During the last three decades, the arena of biodiversity conservation has largely aligned itself with the globally dominant political ideology of neoliberalism and associated governmentalities. Schemes such as payments for ecological services are promoted to reach the multiple ‘wins’ so desired: improved biodiversity conservation, economic development, (international) cooperation and poverty alleviation, amongst others. While critical scholarship with respect to understanding the linkages between neoliberalism, capitalism and the environment has a long tradition, a synthesized critique of neoliberal conservation - the ideology (and related practices) that the salvation of nature requires capitalist expansion - remains lacking. This paper aims to provide such a critique. We commence with the assertion that there has been a conflation between ‘economics’ and neoliberal ideology in conservation thinking and implementation. As a result, we argue, it becomes easier to distinguish the main problems that neoliberal win-win models pose for biodiversity conservation. These are framed around three points: the stimulation of contradictions; appropriation and misrepresentation and the disciplining of dissent. Inspired by Bruno Latour’s recent ‘compositionist manifesto’, the conclusion outlines some ideas for moving beyond critique