scholarly journals Delegated trade and the pricing of public and private information

2015 ◽  
Vol 60 (2-3) ◽  
pp. 8-32 ◽  
Author(s):  
Daniel J. Taylor ◽  
Robert E. Verrecchia
2011 ◽  
Author(s):  
Anne Opschoor ◽  
Michel van der Wel ◽  
Dick J. C. van Dijk ◽  
Nicholas Taylor

2014 ◽  
Vol 04 (03) ◽  
pp. 1450009 ◽  
Author(s):  
Özgür Ş. İnce

This study develops a structural model of the initial public offering (IPO) pricing process that enables the estimation of adjustment rates for public and private pricing information gathered during bookbuilding. The estimated upward adjustment rate of public information is only 21%, significantly less than the 28% rate of private information. Adjustment rates decline towards the IPO date, especially for upward adjustments. The findings contradict information acquisition theories that predict a complete adjustment to public information and highlight the inefficiency of the IPO bookbuilding mechanism in handling new information even when information is publicly available and especially when it is favorable.


2016 ◽  
Vol 12 (5) ◽  
pp. 478-497 ◽  
Author(s):  
Edwin Harold Neave

Purpose The purpose of this paper is to use an equilibrium model to identify the public and private informational requirements for equilibrium pricing and shows that unless these informational requirements are met, skin-in-the-game policies will not be fully effective against moral hazard for banks with relatively large market share. Selling securitizations with recourse can be. Design/methodology/approach The single-period model shows equilibrium prices depend on both public and private information, the latter produced as banks screen loans. If bank has a sufficiently large market share, it can profit by omitting the screening unless investors can detect the change. The author derives the profit function for not screening, shows that a skin-in-the-game policy cannot fully offset its incentives, and proposes a sale with recourse policy that can. Findings To value securitizations correctly, investors require both publicly and privately available information. If investors cannot monitor banks closely, correct pricing can be frustrated by profit maximization incentives, since banks with large market shares can profit from not screening. Skin-in-the-game policies cannot fully offset these incentives. Research limitations/implications The equilibrium model identifies the public and private informational requirements for equilibrium pricing and shows that unless these informational requirements are met, skin-in-the-game policies will not be fully effective for banks with relatively large market share. Selling securitizations with recourse can be more fully effective. Practical implications If it is difficult for investors to obtain private information, skin-in-the-game policies are not provide fully effective remedies against moral hazard. Sales with recourse policies offer promise because they are easy for investors to understand and difficult to evade. Social implications Trading on the basis of private information can create perverse incentives, and appropriate corrective policies can help offset them. Originality/value The general equilibrium methodology, the findings of incentives to avoid screening, the flaws with skin-in-the-game policies, and the proposal for sale with recourse are all new.


Data Science ◽  
2021 ◽  
pp. 1-20
Author(s):  
Laura Boeschoten ◽  
Roos Voorvaart ◽  
Ruben Van Den Goorbergh ◽  
Casper Kaandorp ◽  
Martine De Vos

The General Data Protection Regulation (GDPR) grants all natural persons the right to access their personal data if this is being processed by data controllers. The data controllers are obliged to share the data in an electronic format and often provide the data in a so called Data Download Package (DDP). These DDPs contain all data collected by public and private entities during the course of a citizens’ digital life and form a treasure trove for social scientists. However, the data can be deeply private. To protect the privacy of research participants while using their DDPs for scientific research, we developed a de-identification algorithm that is able to handle typical characteristics of DDPs. These include regularly changing file structures, visual and textual content, differing file formats, differing file structures and private information like usernames. We investigate the performance of the algorithm and illustrate how the algorithm can be tailored towards specific DDP structures.


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