Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user’s visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection

Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user’s visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection

Systems for Challenged Network Environments.

Developing regions face significant challenges in network access, making even simple network tasks unpleasant and rich media prohibitively difficult to access. Even as cellular network coverage is approaching a near-universal reach, good network connectivity remains scarce and expensive in many emerging markets. The underlying theme in this dissertation is designing network systems that better accommodate users in emerging markets. To do so, this dissertation begins with a nuanced analysis of content access behavior for web users in developing regions. This analysis finds the personalization of content access---and the fragmentation that results from it---to be significant factors in undermining many existing web acceleration mechanisms. The dissertation explores content access behavior from logs collected at shared internet access sites, as well as user activity information obtained from a commercial social networking service with over a hundred million members worldwide. Based on these observations, the dissertation then discusses two systems designed for improving end-user experience in accessing and using content in constrained networks. First, it deals with the challenge of distributing private content in these networks. By leveraging the wide availability of cellular telephones, the dissertation describes a system for personal content distribution based on user access behavior. The system enables users to request future data accesses, and it schedules content transfers according to current and expected capacity. Second, the dissertation looks at routing bulk data in challenged networks, and describes an experimentation platform for building systems for challenged networks. This platform enables researchers to quickly prototype systems for challenged networks, and iteratively evaluate these systems using mobility and network emulation. The dissertation describes a few data routing systems that were built atop this experimentation platform. Finally, the dissertation discusses the marketplace and service discovery considerations that are important in making these systems viable for developing-region use. In particular, it presents an extensible, auction-based market platform that relies on widely available communication tools for conveniently discovering and trading digital services and goods in developing regions. Collectively, this dissertation brings together several projects that aim to understand and improve end-user experience in challenged networks endemic to developing regions.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91401/1/azarias_1.pd

Getting Hooked on Gnarly Rods

At Gnarly Rods, our objective is to supply builders and fishermen alike with the quality gear, components, and service necessary to catch everything life has to offer. From providing rod building parts, to repairs, to fully customized fishing rods, we are the destination for all things in custom fishing. Conceptualized in 2015, Gnarly Rods will be based out of Springdale, AR, and started by Robert and Cody Nelson, a father and son pair as passionate for fishing as they are family and the influence the outdoors can have in life. As of now, we will be the only two employees in the company, and plan to remain as such until the business requires more employees. Robert will be responsible for maintaining finances and being the head builder, while Cody will be focused on driving marketing and sales, while also building rods as necessary for the company. It is at this time we believe we must now convert our passions into a profitable business opportunity. We will also be investigating our financial projections, product offerings, and marketing tactics

Glucksman Fellowship Program Student Research Reports

The Glucksman Institute for Research in Securities Markets awards fellowships each year to outstanding second year Stern MBA students to work on independent research projects under a faculty member's supervision. Four research projects completed by the Glucksman Fellows of 2011-2012 are included in this special issue of the Finance Department Working Paper Series. These papers focus on important topics in empirical financial economics. Samuel Welt, under the supervision of William Silber, analyzes the economic and political factors that determine the magnitude of increases in the debt ceiling voted by Congress. Karen Shortt, under the direction of Aswath Damodaran , investigates the relationship between corporate environmental performance and abnormal stock price movements of a firm. Oren Livne, under the supervision of Alexander Ljungqvist, provides an overview of the evolution of the private company secondary marketplace in the United States, and evaluates the ability of secondary market data to predict share price changes post IPO. Ismael Orenstein, under the supervision of Yakov Amihud, analyzes the impact of the Federal Reserve’s Quantitative Easing (QE) program on the relative pricing of treasury securities. These papers, reflecting the research effort of four outstanding Stern MBA students, are summarized in more detail in the Table of Contents on the next page