Business Commons^™

Mining Fraudulent Patterns In Online Advertising, Richard J. Oentaryo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Advances in web technologies have rendered onlineadvertising as an effective means for small and large businesses to target different market segments on the fly. Online advertising is a huge industry. According to Gartner Inc., worldwide online advertising revenue is projected tohit $11.4 billion in 2013, up from $9.6 billion in 2012. Global revenue will also reach $24.5 billion in 2016, with online advertising creating opportunities for app developers, advertising networks, and service providersin various regions. An online advertising ecosystem is typically coordinated by an advertising commissioner, acting as a broker between advertisers and content publishers. An advertiser plans a budget, …

The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng

Research Collection School Of Computing and Information Systems

This paper investigates the value relevance of accounting information in the presence of ineffective internal control (IIC). Based on Ohlson's valuation model, this paper first documents that IIC can directly affect a firm's market value after control cost of capital, corporate governance, and other, value-relevant variables. Second, this paper finds that the value relevance of earnings and book value in determining a firm's market value are significantly reduced. Collectively, the results of this paper indicate that the effectiveness of internal controls can directly affect a firm's market value and the value relevance of accounting information.

Robust Median Reversion Strategy For On-Line Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Steven Hoi, Shuigeng Zhou

Research Collection School Of Computing and Information Systems

On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L₁-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal …

Integrating Strategic And Tactical Rolling Stock Models With Cyclical Demand, Michael F. Gorman

MIS/OM/DS Faculty Publications

In the transportation industry, companies position rolling stock where it is likely to be needed in the face of a pronounced weekly cyclical demand pattern in orders.

Strategic policies based on assumptions of repetition of cyclical weekly patterns set rolling stock targets; during tactical execution, a myriad dynamic influences cause deviations from strategically set targets. We find that optimal strategic plans do not agree with results of tactical modeling; strategic results are in fact suboptimal in many tactical situations. We discuss managerial implications of this finding and how the two modeling paradigms can be reconciled.

Core Versus Peripheral Information Technology Employees And Their Impact On Firm Performance, Ling Liu, Daniel Q. Chen, Nan Hu, Indranil Bose, Garry D. Bruton

Research Collection School Of Computing and Information Systems

Scholars have widely argued, but not previously examined, that core employees with firm specific skills are critical to the firm's strategic success. This argument has led to the belief that employees whose skills are not firm specific can be readily replaced in the external market and are peripheral to the firm's strategic goals. Employing a resource based view of the firm, we find that the core information technology (IT) employees with firm specific skills are value-adding resources that aid the firm's performance whereas peripheral employees with less firm specific skills provide no value to the firm's performance. Examining the issue …

Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan

Research Collection School Of Computing and Information Systems

Online portfolio selection has been attracting increasing attention from the data mining and machine learning communities. All existing online portfolio selection strategies focus on the first order information of a portfolio vector, though the second order information may also be beneficial to a strategy. Moreover, empirical evidence shows that relative stock prices may follow the mean reversion property, which has not been fully exploited by existing strategies. This article proposes a novel online portfolio selection strategy named Confidence Weighted Mean Reversion (CWMR). Inspired by the mean reversion principle in finance and confidence weighted online learning technique in machine learning, CWMR …

Stock Market Prediction Without Sentiment Analysis: Using A Web-Traffic Based Classifier And User-Level Analysis, Pierpaolo Dondio

Conference papers

This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline classifier solely based on price time-series, and to have similar performances as the classifier built considering price and traffic features together. The best predictive performances are achieved when information about stock capitalization is coupled with …

Detecting Mobility Patterns In Mobile Phone Data From The Ivory Coast, Matthew Dixon, Spencer P. Aiello, Funmi Fapohunda, William Goldstein

Business Analytics and Information Systems

This paper investigates the Data for Development (D4D) challenge [3], an open challenge set by the French mobile phone company, Orange, who have provided anonymized records of their customers in the Ivory Coast. This data spans a 5 month (150 day) horizon spread across 4 different sets containing antenna-to-antenna traffic, trace data for 50,000 customers at varying spatial resolution, and social graphs for 5,000 customers. By leveraging cloud-based and open-source analytics infrastructure to (1) merge the D4D datasets with Geographic Information System (GIS) data and (2) apply data mining algorithms, this paper presents a number of techniques for detecting mobility …

Seller Diversity On A Technology-Based Platform, Ruhai Wu, Mei Lin

Research Collection School Of Computing and Information Systems

Managing a technology portfolio is one of the great challenges for sustained success, especially in high-technology industrieswhere technologies can be a major selling point. For engineers, this portfolio is more of a toolbox for solving design problems,but in large organizations there can be so many technologies used in different business areas that even the engineers may not beaware of all of them. When the same technologies are used in different types of products, knowledge about them can also begenerated by various groups within an organization. To improve the usefulness of a company's technology base, this paperproposes the use of a …