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Articles 61 - 90 of 93
Full-Text Articles in Finance and Financial Management
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 …
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 …
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 …
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 …
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 …
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 …
Firm Strategy And The Internet In U.S. Commercial Banking, Kim Huat Goh, Robert J. Kauffman
Firm Strategy And The Internet In U.S. Commercial Banking, Kim Huat 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 …
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 …
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, …
Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh
Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh
Research Collection School Of Computing and Information Systems
On May 6, 2010, the U.S. equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (see Figure 1) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. The authors contend that the events of May 6, 2010 exhibit patterns consistent with the type of "flash crash" observed in their earlier study (2010). This paper describes the results of nine different simulations created by using a large-scale computer model to reconstruct the critical elements …
Would Position Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh
Would Position Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh
Research Collection School Of Computing and Information Systems
On May 6, 2010, the US equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (DJIA) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. Earlier research by Lee, Cheng and Koh (2010) identified the conditions under which a “flash crash” can be triggered by systematic traders running highly similar trading strategies, especially when they are “crowding out” other liquidity providers in the market. The authors contend that the events of May 6, …
An Analysis Of Extreme Price Shocks And Illiquidity Among Trend Followers, Bernard Lee, Shih-Fen Cheng, Annie Koh
An Analysis Of Extreme Price Shocks And Illiquidity Among Trend Followers, Bernard Lee, Shih-Fen Cheng, Annie Koh
Research Collection School Of Computing and Information Systems
We construct an agent-based model to study the interplay between extreme price shocks and illiquidity in the presence of systematic traders known as trend followers. The agent-based approach is particularly attractive in modeling commodity markets because the approach allows for the explicit modeling of production, capacities, and storage constraints. Our study begins by using the price stream from a market simulation involving human participants and studies the behavior of various trend-following strategies, assuming initially that their participation will not impact the market. We notice an incremental deterioration in strategy performance as and when strategies deviate further and further from the …
Operational Risk In Trading Platforms, M. Thulasidas
Operational Risk In Trading Platforms, M. Thulasidas
Research Collection School Of Computing and Information Systems
Operational risk is the risk of loss resulting from inadequate or failed internal processes, people, and systems, or from external events. A trading platform is a system, and therefore comes under the umbrella definition of operational risk.
An Agent-Based Commodity Trading Simulation, Shih-Fen Cheng, Yee Pin Lim
An Agent-Based Commodity Trading Simulation, Shih-Fen Cheng, Yee Pin Lim
Research Collection School Of Computing and Information Systems
In this paper, an event-centric commodity trading simulation powered by the multiagent framework is presented. The purpose of this simulation platform is for training novice traders. The simulation is progressed by announcing news events that affect various aspects of the commodity supply chain. Upon receiving these events, market agents that play the roles of producers, consumers, and speculators would adjust their views on the market and act accordingly. Their actions would be based on their roles and also their private information, and collectively they shape the market dynamics. This simulation has been effectively deployed for several training sessions. We will …
House Of Cards, M. Thulasidas
House Of Cards, M. Thulasidas
Research Collection School Of Computing and Information Systems
We are in dire straits - no doubt about it. Our banks and financial edifices are collapsing. Those left standing also look shaky. The financial industry as a whole is battling to survive. And, as its frontline warriors, we will bear the brunt of the blood- bath sure to ensue any minute now. A good opportunity to play solitaire?
Chaos And Uncertainty, M. Thulasidas
Chaos And Uncertainty, M. Thulasidas
Research Collection School Of Computing and Information Systems
The end of 2008 in the finance industry can be summarized in two words – chaos and uncertainty. The subprime crisis, where everybody lost; the dizzying commodity price movements; the pink slip syndrome; the spectacular bank busts; and the gargantuan bail-outs all vouch for it.
Software Nightmares, Manoj Thulasidas
Software Nightmares, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
To err is human, but to really foul things up, you need a computer. So states the remarkably insightful Murphy’s Law. And nowhere else does this ring truer than in our financial workplace. After all, it is the financial sector that drove the rapid progress in the computing industry – which is why the first computing giant had the word “business” in its name. The financial industry keeps up with the developments in the computer industry for one simple reason. Stronger computers and smarter programs mean more money — a concept we readily grasp. As we use the latest and …
The Impact Of Financial Market And Resale Market On Firm Strategies, Zhiling Guo, Andrew B. Whinston
The Impact Of Financial Market And Resale Market On Firm Strategies, Zhiling Guo, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
The ever-increasing use of information technology (IT) in business transactions greatly expands firms? exposure to different electronic markets. This paper provides a framework to understand how firms can leverage different strategies across external financial markets and an internal resale market to improve overall profitability. We develop a model in which a group of risk-averse retailers sell a homogeneous product to their respective uncertain consumer markets. We study a scenario where an internal resale market can be constructed among the retailers and outside financial markets can be used to improve their ability to manage uncertainty. We identify strategies for retailers operating …