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Articles 31 - 60 of 71
Full-Text Articles in Finance and Financial Management
Automated Theme Search In Ico Whitepapers, Chuanjie Fu, Andrew Koh, Paul Griffin
Automated Theme Search In Ico Whitepapers, Chuanjie Fu, Andrew Koh, Paul Griffin
Research Collection School Of Computing and Information Systems
The authors explore how topic modeling can be used to automate the categorization of initial coin offerings (ICOs) into different topics (e.g., finance, media, information, professional services, health and social, natural resources) based solely on the content within the whitepapers. This tool has been developed by fitting a latent Dirichlet allocation (LDA) model to the text extracted from the ICO whitepapers. After evaluating the automated categorization of whitepapers using statistical and human judgment methods, it is determined that there is enough evidence to conclude that the LDA model appropriately categorizes the ICO whitepapers. The results from a two-population proportion test …
Collusion Attacks And Fair Time-Locked Deposits For Fast-Payment Transactions In Bitcoin, Xingjie Yu, Shiwen Michael Thang, Yingjiu Li, Robert H. Deng
Collusion Attacks And Fair Time-Locked Deposits For Fast-Payment Transactions In Bitcoin, Xingjie Yu, Shiwen Michael Thang, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In Bitcoin network, the distributed storage of multiple copies of the block chain opens up possibilities for doublespending, i.e., a payer issues two separate transactions to two different payees transferring the same coins. While Bitcoin has inherent security mechanism to prevent double-spending attacks, it requires a certain amount of time to detect the doublespending attacks after the transaction has been initiated. Therefore, it is impractical to protect the payees from suffering in double-spending attacks in fast payment scenarios where the time between the exchange of currency and goods or services is shorten to few seconds. Although we cannot prevent double-spending …
Picking Flowers In An Ico Garden, Fam Guo Teng, Paul R. Griffin, Andrew Koh
Picking Flowers In An Ico Garden, Fam Guo Teng, Paul R. Griffin, Andrew Koh
Research Collection School Of Computing and Information Systems
The rise of Initial Coin Offerings (ICO) in recent times and their potential for investment opportunities have investors spending a lot of time researching ICOs or having to follow the crowd. This paper aims to explore four broad factors of ICOs: identity, credibility, investor sentiment, and price movement to develop a framework that is useful in determining ICO quality. Research is shown using data sources including public forums, chat groups, web sites, white papers as well as smart contract details. Finally, a system, based on the framework, is proposed that can be used to detect and regulate ICO activities and …
Risk Pooling, Supply Chain Hierarchy, And Analysts' Forecasts, Nan Hu, Jian-Yu Ke, Ling Liu, Yue Zhang
Risk Pooling, Supply Chain Hierarchy, And Analysts' Forecasts, Nan Hu, Jian-Yu Ke, Ling Liu, Yue Zhang
Research Collection School Of Computing and Information Systems
We investigate whether a firm's risk pooling affects its analysts' forecasts, specifically in terms of forecast accuracy and their use of public vs. private information, and how risk pooling interacts with a firm's position in the supply chain to affect analysts' forecasts. We use a social network analysis method to operationalize risk pooling and supply chain hierarchy, and find that risk pooling significantly reduces analysts' forecast errors and increases (decreases) their use of public (private) information. We also find that the positive (negative) relationships between risk pooling and analyst forecast accuracy and analysts' use of public (private) information are more …
Esg And Corporate Financial Performance: Empirical Evidence From China's Listed Power Generation Companies, Changhong Zhao, Yu Guo, Jiahai Yuan, Mengya Wu, Daiyu Li, Yiou Zhou, Jiangang Kang
Esg And Corporate Financial Performance: Empirical Evidence From China's Listed Power Generation Companies, Changhong Zhao, Yu Guo, Jiahai Yuan, Mengya Wu, Daiyu Li, Yiou Zhou, Jiangang Kang
Research Collection School Of Computing and Information Systems
Nowadays, listed companies around the world are shifting from short-term goals of maximizing profits to long-term sustainable environmental, social, and governance (ESG) goals. People have come to realize that ESG has become an important source of the corporate risk and may affect the company's financial performance and profitability. Recent research shows that good ESG performance could improve the financial performance in some countries. Yet, the question of how does ESG affect financial performance has not been thoroughly discussed and studied in China. In this article, we study China's listed power generation groups to explore the relationship between ESG performance and …
Soa Maturity Influence On Digital Banking Transformation, Alan Megargel, Venky Shankararaman, Terence P. C. Fan
Soa Maturity Influence On Digital Banking Transformation, Alan Megargel, Venky Shankararaman, Terence P. C. Fan
Research Collection School Of Computing and Information Systems
Digital Banking is an evolution of online banking, where the banks attempt to further enhance customer experience by integrating digital technologies such as mobile technology, social media and analytics. Traditional banks have the highest barriers to entry into the digital banking market due to the presence of legacy core banking systems. These legacy systems while still high performing and reliable, are inflexible to change and are not easily integrated to the modern application systems needed for delivering digital banking services across multiple online banking channels. One solution that is widely adopted in the industry to overcome this obstacle is the …
A Proposal For A Decentralized Liquidity Savings Mechanism With Side Payments, Adam Fugal, Rodney Garratt, Zhiling Guo, Dave Hudson
A Proposal For A Decentralized Liquidity Savings Mechanism With Side Payments, Adam Fugal, Rodney Garratt, Zhiling Guo, Dave Hudson
Research Collection School Of Computing and Information Systems
In most countries, the central bank provides the medium to physically settle the smallest payments (cash) and the means to electronically settle the largest payments, which typically are wholesale payments between banks. For the latter purpose the central bank usually operates a system through which banks can settle payments in central bank money. Historically, interbank payments were settled via (end of day) netting systems, but as volumes and values increased central banks became worried about the risks inherent in deferred net settlement systems, so most central banks opted for the implementation of a Real Time Gross Settlement (RTGS) system. With …
On The Fintech Revolution: Interpreting The Forces Of Innovation, Disruption And Transformation In Financial Services, Peter Gomber, Robert J. Kauffman, Chris Parker, Bruce W. Weber
On The Fintech Revolution: Interpreting The Forces Of Innovation, Disruption And Transformation In Financial Services, Peter Gomber, Robert J. Kauffman, Chris Parker, Bruce W. Weber
Research Collection School Of Computing and Information Systems
Firms in the financial services industry have been faced with the dramatic and relatively recentemergence of new technology innovations, and process disruptions. The industry as a whole, and many newfintech start-ups are looking for new pathways to successful business models, the creation of enhanced customerexperience, and new approaches that result in services transformation. Industry and academic observers believethis to be more of a revolution than a set of less impactful changes, with financial services as a whole due formajor improvements in efficiency, in customer centricity and informedness. The long-standing dominance ofleading firms that are not able to figure out how …
Real-Time Inbound Marketing: A Use Case For Digital Banking, Alan Megargel, Venky Shankararaman, Srinivas K. Reddy
Real-Time Inbound Marketing: A Use Case For Digital Banking, Alan Megargel, Venky Shankararaman, Srinivas K. Reddy
Research Collection School Of Computing and Information Systems
Over the years banks have been strategically using digital technologies to help transform various aspects of their business. In recent times, this strategy has evolved into one of digital augmentation of the bank’s processes, products and channels. This allows for reaching out to customers and partners through digital platforms, for example; the addition of mobile apps for customers to access and perform service transactions. Marketing continues to play a major role in supporting the expansion of business and increasing revenue for the bank. Marketing has evolved from mass direct targeting to more personalised, face-to-face and real-time targeting. In the digital …
Fair Deposits Against Double-Spending For Bitcoin Transactions, Xingjie Yu, Shiwen M. Thang, Yingjiu Li, Robert H. Deng
Fair Deposits Against Double-Spending For Bitcoin Transactions, Xingjie Yu, Shiwen M. Thang, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In Bitcoin network, the distributed storage of multiple copies of the blockchain opens up possibilities for double spending, i.e., a payer issues two separate transactions to two different payees transferring the same coins. To detect the doublespending and penalize the malicious payer, decentralized non-equivocation contracts have been proposed. The basic idea of these contracts is that the payer locks some coins in a deposit when he initiates a transaction with the payee. If the payer double spends, a cryptographic primitive called accountable assertions can be used to reveal his Bitcoin credentials for the deposit. Thus, the malicious payer could be …
How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang
How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang
Research Collection School Of Computing and Information Systems
In the era of Fintech innovation and e-commerce, faster settlement of massive retail transactions is crucial for business growth and financial system stability. However, speeding up payments settlement can create periodic liquidity shortfalls to banks which would incur high cost of funds in the settlement process. We propose a new hybrid settlement mechanism design that integrates features of real-time gross settlement, deferred net settlement, and central queue management structure. The hybrid mechanism is managed by an intermediary and is particularly suitable to settle large volume of small-value retail payments. We evaluate the mechanism using computer experiments and simulation. We find …
Does Director Interlock Impact The Diffusion Of Accounting Method Choice?, Jie Han, Nan Hu, Ling Liu, Gaoliang Tian
Does Director Interlock Impact The Diffusion Of Accounting Method Choice?, Jie Han, Nan Hu, Ling Liu, Gaoliang Tian
Research Collection School Of Computing and Information Systems
This paper examines the influence of director interlock on firms' discrete accounting method choices from the perspective of behavior diffusion. We argue that firm managers will imitate their interlocked-partner firm's accounting method choices when choosing their own accounting methods. We find that when there is an interlock relationship between two firms, their accounting method choices, including inventory and depreciation methods, are similar to each other, indicating that accounting method choices can diffuse across firms through director interlock. In addition, such similarity is greater the longer the interlock relationship between the two firms is and as uncertainty increases. Further, the interlock …
Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou
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 …
The Impact Of Nasd Rule 2711 And Nyse Rule 472 On Analyst Behavior: The Strategic Timing Of Recommendations Issued On Weekends, Yi Dong, Nan Hu
The Impact Of Nasd Rule 2711 And Nyse Rule 472 On Analyst Behavior: The Strategic Timing Of Recommendations Issued On Weekends, Yi Dong, Nan Hu
Research Collection School Of Computing and Information Systems
Amendments to NASD Rule 2711 and NYSE Rule 472, enacted in May 2002, mandate that sell-side analysts disclose the distribution of their security recommendations by buy, hold and sell category. This regulation enhances the transparency of analysts' information and mitigates the long-recognized optimistic bias in their recommendations. However, we find that analysts are more likely to issue sell recommendations or downgrade revisions on weekends when investors have limited attention after these rule changes. This pattern is more pronounced for prestigious analysts, who are more likely to influence stock prices. Market reaction tests reveal an incomplete immediate response and a greater …
Olps: A Toolbox For On-Line Portfolio Selection, Bin Li, Doyen Sahoo, Hoi, Steven C. H.
Olps: A Toolbox For On-Line Portfolio Selection, Bin Li, Doyen Sahoo, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
On-line portfolio selection is a practical financial engineering problem, which aims to sequentially allocate capital among a set of assets in order to maximize long-term return. In recent years, a variety of machine learning algorithms have been proposed to address this challenging problem, but no comprehensive open-source toolbox has been released for various reasons. This article presents the first open-source toolbox for "On-Line Portfolio Selection" (OLPS), which implements a collection of classical and state-of-the-art strategies powered by machine learning algorithms. We hope that OLPS can facilitate the development of new learning methods and enable the performance benchmarking and comparisons of …
Innovations In Financial Is And Technology Ecosystems: High-Frequency Trading Systems In The Equity Market, Robert J. Kauffman, Jun Liu, Dan Ma
Innovations In Financial Is And Technology Ecosystems: High-Frequency Trading Systems In The Equity Market, Robert J. Kauffman, Jun Liu, Dan Ma
Research Collection School Of Computing and Information Systems
Technology-based financial innovations over the past four decades have led to transformations in the financial markets. Understanding technological innovations in financial information systems (IS) and technologies has been challenging for technology consultants and financial industry practitioners due to the underlying complexities though. In this article, we propose an ecosystem analysis approach by extending the technology ecosystem paths of influence model (Adomavicius et al., 2008a) to incorporate stakeholder actions, considering both supply-side and demand-side forces for technological change. Our ecosystem model brings together three original core elements: technology components, technology-based services, and technology-supported business infrastructures. We also contribute a fourth new …
Learning Of Business Processes & Application: An Industry-Ready Approach, Yi Meng Lau, Yu Yee Poon, Mike Wee
Learning Of Business Processes & Application: An Industry-Ready Approach, Yi Meng Lau, Yu Yee Poon, Mike Wee
Research Collection School Of Computing and Information Systems
The Learning Framework for Business Processes was developed by lectures from School of InfoComm Technology (ICT)to support their students’ learning in the Diploma of Financial Informatics. This framework leverage on the use of learning approaches such as Inquiry based learning to create opportunities for students to be engaged, explore, explain and apply their learning. This framework was presented at International Symposium on Advances in Technology Education (ISATE) 2015 in Nagaoka, Japan.
Will High-Frequency Trading Practices Transform The Financial Markets In The Asia Pacific Region?, Robert John Kauffman, Yuzhou Hu, Dan Ma
Will High-Frequency Trading Practices Transform The Financial Markets In The Asia Pacific Region?, Robert John Kauffman, Yuzhou Hu, Dan Ma
Research Collection School Of Computing and Information Systems
High-frequency trading (HFT) practices in the global financial markets involve the use of information and communication technologies (ICT), especially the capabilities of high-speed networks, rapid computation, and algorithmic detection of changing information and prices that create opportunities for computers to effect low-latency trades that can be accomplished in milliseconds. HFT practices exist because a variety of new technologies have made them possible, and because financial market infrastructure capabilities have also been changing so rapidly. The U.S. markets, such as the National Association for Securities Dealers Automated Quote (NASDAQ) market and the New York Stock Exchange (NYSE), have maintained relevance and …
Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu
Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
On-line portfolio selection, a fundamental problem in computational finance, has attracted increasing interest from artificial intelligence and machine learning communities in recent years. Empirical evidence shows that stock's high and low prices are temporary and stock prices are likely to follow the mean reversion phenomenon. While existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied, leading to poor performance in certain real datasets. To overcome this limitation, this article proposes a multiple-period mean reversion, or so-called "Moving Average Reversion" (MAR), and …
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Online portfolio selection (PS) has been extensively studied in artificial intelligence and machine learning communities in recent years. An important practical issue of online PS is transaction cost, which is unavoidable and nontrivial in real financial trading markets. Most existing strategies, such as universal portfolio (UP) based strategies, often rebalance their target portfolio vectors at every investment period, and thus the total transaction cost increases rapidly and the final cumulative wealth degrades severely. To overcome the limitation, in this paper we investigate new investment strategies that rebalances its portfolio only at some selected instants. Specifically, we design a novel on-line …
Board Interlock Networks And The Use Of Relative Performance Evaluation, Qian Hao, Nan Hu, Ling Liu, Lee J. Yao
Board Interlock Networks And The Use Of Relative Performance Evaluation, Qian Hao, Nan Hu, Ling Liu, Lee J. Yao
Research Collection School Of Computing and Information Systems
Purpose - The purpose of this paper is to explore how networks of boards of directors affect relative performance evaluation (RPE) in chief executive officer (CEO) compensation. Design/methodology/approach - In this study, the authors propose that an interlocking network is an important inter-corporate setting, which has a bearing on whether boards decide to use RPE in CEO compensation. They adopt four typical graph measures to depict the centrality/position of each board in the interlock network: degree, betweenness, eigenvector and closeness, and study their impacts on RPE use. Findings - The authors find that firms that have more connected board members …
Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi
Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Online portfolio selection is a fundamental problem in computational finance, which has been extensively studied across several research communities, including finance, statistics, artificial intelligence, machine learning, and data mining. This article aims to provide a comprehensive survey and a structural understanding of online portfolio selection techniques published in the literature. From an online machine learning perspective, we first formulate online portfolio selection as a sequential decision problem, and then we survey a variety of state-of-the-art approaches, which are grouped into several major categories, including benchmarks, Follow-the-Winner approaches, Follow-the-Loser approaches, Pattern-Matching--based approaches, and Meta-Learning Algorithms. In addition to the problem formulation …
Robust Median Reversion Strategy For On-Line Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Steven Hoi, Shuigeng Zhou
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 …
Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong
Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Credit risk assessment for consumers has been a cornerstone of risk management in financial institutions and constitutes a component of the three pillars of Basel II. Traditionally, the concept of 5 ‘C’s was widely adopted by financial institutions as the key basis for credit risk assessment for loan applications by prospective borrowers. With the evolution of the credit risk management practices, more quantitative methods such as credit scorecards have been developed, which is implemented through the use of logistic regression, decision trees and neural networks. However, such approaches proved to be inadequate with the validity and effectiveness of the approaches …
Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing, Fengjun Li, Bo Luo, Peng Liu, Dongwon Lee, Chao-Hsien Chu
Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing, Fengjun Li, Bo Luo, Peng Liu, Dongwon Lee, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Today’s organizations raise an increasing need for information sharing via on-demand access. Information brokering systems (IBSs) have been proposed to connect large-scale loosely federated data sources via a brokering overlay, in which the brokers make routing decisions to direct client queries to the requested data servers. Many existing IBSs assume that brokers are trusted and thus only adopt server-side access control for data confidentiality. However, privacy of data location and data consumer can still be inferred from metadata (such as query and access control rules) exchanged within the IBS, but little attention has been put on its protection. In this …
Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan
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 …
Not All That Glitters Is Gold: The Effect Of Attention And Blogs On The Investors' Investing Behaviors, Nan Hu, Yi Dong, Ling Liu, Lee J. Yao
Not All That Glitters Is Gold: The Effect Of Attention And Blogs On The Investors' Investing Behaviors, Nan Hu, Yi Dong, Ling Liu, Lee J. Yao
Research Collection School Of Computing and Information Systems
This article investigates the relationship between a firm’s visibility in blogspaces, termed blog exposure, and the cross-sectional stock returns. We show that blog exposure is fundamentally different from the traditional media coverage, and securities with low blog exposure earn higher returns than stocks with high blog exposure. We further illustrate that such an effect is more prominent for stocks with low institutional ownership. Contrary to traditional media coverage, the return premium associated with blog exposure cannot be explained by either the illiquidity hypothesis or the investor recognition hypothesis based on the rational-agent framework. Instead, our results suggest that blog effect …
Firm Strategy And The Internet In U.S. Commercial Banking, K. H. Goh, Robert J. Kauffman
Firm Strategy And The Internet In U.S. Commercial Banking, K. H. Goh, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
As information technology (IT) becomes more accessible, sustaining any competitive advantage from it becomes challenging. This has caused some critics to dismiss IT as a less valuable resource. We argue that, in addition to being able to generate strategic advantage, IT should also be viewed as a strategic necessity that prevents competitive disadvantage in rapidly changing business environments. We test a set of hypotheses on strategic advantage and strategic necessity in the context of Internet banking investments among the entire population of the United States Federal Deposit Insurance Corporation (FDIC) banks from 2003 to 2005. We seek to understand whether …
Knowledge-Driven Autonomous Commodity Trading Advisor, Yee Pin Lim, Shih-Fen Cheng
Knowledge-Driven Autonomous Commodity Trading Advisor, Yee Pin Lim, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
The myth that financial trading is an art has been mostly destroyed in the recent decade due to the proliferation of algorithmic trading. In equity markets, algorithmic trading has already bypass human traders in terms of traded volume. This trend seems to be irreversible, and other asset classes are also quickly becoming dominated by the machine traders. However, for asset that requires deeper understanding of physicality, like the trading of commodities, human traders still have significant edge over machines. The primary advantage of human traders in such market is the qualitative expert knowledge that requires traders to consider not just …
Confidence Weighted Mean Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivek Gopalkrishnan
Confidence Weighted Mean Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivek Gopalkrishnan
Research Collection School Of Computing and Information Systems
On-line portfolio selection has been attracting increasing attention from the data mining and machine learning communities. All existing on-line 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 evidences show that the stock price relatives may follow the mean reversion property, which has not been fully exploited by existing strategies. This article proposes a novel on-line 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, …