A Novel Auction Blockchain System with Price Recommendation and Trusted Execution Environment

Online auctions are now widely used, with all the convenience and efficiency brought by internet technology. Despite the advantages over traditional auction methods, some challenges still remain in online auctions. According to the World Business Environment Survey (WBES) conducted by the World Bank, about 60% of companies have admitted to bribery and manipulation of the auction results. In addition, buyers are prone to the winner’s curse in an online auction environment. Since the increase in information availability can reduce uncertainty, easy access to relevant auction information is essential for buyers to avoid the winner’s curse. In this study, we propose an Online Auction Price Suggestion System (OAPSS) to protect the data from being interfered with by third-party programs based on Intel’s Software Guard Extensions (SGX) technology and the characteristics of the blockchain. Our proposed system provides a smart contract by using α-Sutte indicator in the final transaction price prediction as a bidding price recommendation, which helps buyers to reduce the information uncertainty on the value of the product. The amount spent on the smart contract in this study, excluding deployed contracts, plus the rest of the fees is less than US$1. Experimental results of the simulation show that there is a significant difference (p < 0.05) between the recommended price group and the actual price group in the highest bid. Therefore, we may conclude that our proposed bidder’s price recommendation function in the smart contract may mitigate the loss of buyers caused by the winner’s curse.

Why are major sports events trapped in the winner's curse? A case study of the 2017 World Road Cycling Championship

PurposeThis paper sought to determine how a major sport event can become trapped in a winner's curse, in which the fierce competition to host the event forces organisers to spend more on acquiring and hosting it than what it is worth in economic terms.Design/methodology/approachThis study used a combination of document analysis and 47 in-depth interviews with 51 individuals representing various private and public organisations involved in the implementation of the UCI 2017 Road Cycling World Championship. Snowball sampling and a semi-structured interview guide were used to ensure coverage of all relevant information.FindingsThe organiser and the host municipal lacked the necessary experience with events of this size and character. Information from previous championships events was not transferred, and the municipality administration did not utilise experiences from hosting previous events. Limited financial resources prevented the organiser from hiring enough employees with the necessary competence. Lack of communication between the stakeholders who contributed in hosting the event reduced the quality of planning and preparations. A dubious culture and lack of seriousness within the Norwegian Cycling Federation, which was the owner of organising company, seemed to have been transferred to organiser.Originality/valueThe research identifies some of the reasons why major sports events so often turns out to be more problematic than expected in economic terms, not only for the organiser but also for actors in the public sector in the host city. The novelty is that it goes into depth on the underlying reasons and the dynamic forces behind these problems.

Analysis of independent cohorts of outbred CFW mice reveals novel loci for behavioral and physiological traits and identifies factors determining reproducibility

Combining samples for genetic association is standard practice in human genetic analysis of complex traits, but is rarely undertaken in rodent genetics. Here, using 23 phenotypes and genotypes from two independent laboratories, we obtained a sample size of 3,076 commercially available outbred mice and identified 70 loci, more than double the number of loci identified in the component studies. Fine-mapping in the combined sample reduced the number of likely causal variants, with a median reduction in set size of 51%, and indicated novel gene associations, including Pnpo, Ttll6 and GM11545 with bone mineral density, and Psmb9 with weight. However replication at a nominal threshold of 0.05 between the two component studies was low, with less than a third of loci identified in one study replicated in the second. In addition to overestimates in the effect size in the discovery sample (Winner’s Curse), we also found that heterogeneity between studies explained the poor replication, but the contribution of these two factors varied among traits. Leveraging these observations we integrated information about replication rates, study-specific heterogeneity, and Winner’s Curse corrected estimates of power to assign variants to one of four confidence levels. Our approach addresses concerns about reproducibility, and demonstrates how to obtain robust results from mapping complex traits in any genome-wide association study.

A Delegation-Based Theory of Expertise

We investigate information aggregation and competition in a delegation framework. An uninformed principal is unable to perform a task herself and must choose between one of two biased and imperfectly informed experts. In the focal equilibrium, experts exaggerate their biases, anticipating an ideological winner’s curse. We show that having a second expert can benefit the principal, even when equally or more biased than the first expert. The principal can benefit from commitment to an “element of surprise” and prefers experts with equal rather than opposite biases. (JEL D82, D83)

Strategic Nondisclosure in Takeovers

We examine takeover auctions when an informed bidder has better information about the target value than a rival and target shareholders. The informed bidder’s information is either hard or soft, and only hard information can be credibly disclosed. We show that withholding information creates a winner’s curse, thereby serving as a preemption device that deters the rival’s participation. In turn, an endogenous dis- closure cost arises that induces the informed bidder to optimally withhold favorable information to minimize the acquisition price—breaking down the standard unraveling result, even if his information is always hard. Perhaps surprisingly, stronger competition from the uninformed bidder can reduce the target shareholders’ payoff and increase the payoff of the informed bidder while unambiguously improving social welfare. Moreover, “hardened” information can reduce the gains to trade, decreasing welfare but increasing shareholders’ payoff. Our results provide a cautionary note to promoting more competition and more disclosure.

Navigating sample overlap, winner's curse and weak instrument bias in Mendelian randomization studies using the UK Biobank

We performed GWAS on 2514 complex traits from the UK Biobank using a linear mixed model, identifying 40,620 independent significant associations (p<5x10-8). We estimate that winner's curse incurs substantial overestimation of effect sizes in a mean of 35% of discovered associations per trait. We use these results to estimate that the polygenicity of most complex traits is below 10000 common causal variants. We evaluated the impact of winner's curse on causal effect estimation and hypothesis testing in Mendelian randomization analyses. We show that winner's curse substantially amplifies the magnitude of weak instrument bias, though any inflation of false discovery rates tends to be low or modest. We designed a process of pseudo-replication within the UK Biobank data to generate GWAS estimates that minimise bias in MR studies using these data. Our resource is integrated into the OpenGWAS platform and enables a convenient framework for researchers to minimise bias or maximise precision of causal effect estimates.

Correction for sample overlap, winner's curse and weak instrument bias in two-sample Mendelian Randomization

Inverse-variance weighted two-sample Mendelian Randomization (IVW-MR) is the most widely used approach that uses genome-wide association studies summary statistics to infer the existence and strength of the causal effect between an exposure and an outcome. Estimates from this approach can be subject to different biases due to: (i) the overlap between the exposure and outcome samples; (ii) the use of weak instruments and winner's curse. We developed a method that aims at tackling all these biases together. Assuming spike-and-slab genomic architecture and leveraging LD-score regression and other techniques, we could analytically derive and reliably estimate the bias of IVW-MR using association summary statistics only. This allowed us to apply a bias correction to IVW-MR estimates, which we tested using simulated data for a wide range of realistic scenarios. In all the explored scenarios, our correction reduced the bias, in some situations by as much as 30 folds. When applied to real data on obesity-related exposures, we observed significant differences between IVW-based and corrected effects, both for non-overlapping and fully overlapping samples. While most studies are extremely careful to avoid any sample overlap when performing two-sample MR analysis, we have demonstrated that the incurred bias is much less substantial than the one due to weak instruments or winner's curse, which are often ignored.