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Full-Text Articles in Physical Sciences and Mathematics

Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou Jul 2016

Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., 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 portfolios based …


Analyzing Proactive Fraud Detection Software Tools And The Push For Quicker Solutions, Kerri Aiken May 2016

Analyzing Proactive Fraud Detection Software Tools And The Push For Quicker Solutions, Kerri Aiken

Economic Crime Forensics Capstones

This paper focuses on proactive fraud detection software tools and how these tools can help detect and prevent possible fraudulent schemes. In addition to relying on routine audits, companies are designing proactive methods that involve the inclusion of software tools to detect and deter instances of fraud and abuse. This paper discusses examples of companies using ACL and SAS software programs and how the software tools have positively changed their auditing systems.

Novelis Inc., an aluminum and recycling company, implemented ACL into their internal audit software system. Competitive Health Analytics (Division of Humana) implemented SAS in order to improve their …