Digital Commons Network^™

Japanese Monetary Policy And Its Impact On Stock Market Implied Volatility During Pleasant And Unpleasant Weather, Marinela Adriana Finta

Research Collection Lee Kong Chian School Of Business

We investigate the effect of Japan’s Monetary Policy Meeting releases on the intraday dynamics of the Nikkei Stock Average Volatility Index and its futures during pleasant and unpleasant weather. We show that at the time of a monetary policy release when the temperature is pleasant, there is a significant decline in Japanese equities’ implied volatility and futures, which lasts for about 10 minutes and 5 minutes, respectively. This decline is longer and exhibits a greater variation when releases occur during cold days. Finally, we emphasize the achievable economic profits and losses, given the reaction of Nikkei VI futures to the …

Is The Ground Truth Really Accurate? Dataset Purification For Automated Program Repair, Deheng Yang, Yan Lei, Xiaoguang Mao, David Lo, Huan Xie, Meng Yan

Research Collection School Of Computing and Information Systems

Datasets of real-world bugs shipped with human-written patches are intensively used in the evaluation of existing automated program repair (APR) techniques, wherein the human-written patches always serve as the ground truth, for manual or automated assessment approaches, to evaluate the correctness of test-suite adequate patches. An inaccurate human-written patch tangled with other code changes will pose threats to the reliability of the assessment results. Therefore, the construction of such datasets always requires much manual effort on isolating real bug fixes from bug fixing commits. However, the manual work is time-consuming and prone to mistakes, and little has been known on …

Investment Decisions And Trading Behavior Of Institutional And Retail Investors, Antonia Kirilova

Dissertations and Theses Collection (Open Access)

This dissertation consists of three studies in the areas of empirical asset pricing, market microstructure, and behavioral finance. I study the trading behavior and portfolio choices of institutions and retail investors in the equity and derivatives markets. Examining the ways in which different market participants make investment decisions allows us to understand their role in shaping financial market dynamics. This is important in order to know how to structure markets for enhanced market efficiency, and to protect less sophisticated investors through better policies and regulations. Although there is a considerable amount of literature disputing the ability of retail investors and …

Digital Strategies For Reshaping The Competitiveness Of Hopsca, Wafong Hoi

Dissertations and Theses Collection (Open Access)

The digital transformation strategy has a profound impact on the commercial real estate industry in China. However, so far, research on digital innovation strategies in the business field predominantly surrounds the retailing and systematic research identifying the effect of digital strategies on HOPSCA and commercial operational service provider has yet to be conducted. On the issue of digital transformation strategies of HOPSCA, there is currently a lack of relevant empirical evidence in the fields of management and economics to quantitatively analyze its effects, and there is not readily available and reliable experience for reference in the business practices.

Based on …

Uncertainty Matters: Bayesian Probabilistic Forecasting For Residential Smart Meter Prediction, Segmentation, And Behavioral Measurement And Verification, Jonathan Roth, Jayashree Chadalawada, K. Rishee Jain, Clayton Miller

Research Collection College of Integrative Studies

As new grid edge technologies emerge—such as rooftop solar panels, battery storage, and controllable water heaters—quantifying the uncertainties of building load forecasts is becoming more critical. The recent adoption of smart meter infrastructures provided new granular data streams, largely unavailable just ten years ago, that can be utilized to better forecast building-level demand. This paper uses Bayesian Structural Time Series for probabilistic load forecasting at the residential building level to capture uncertainties in forecasting. We use sub-hourly electrical submeter data from 120 residential apartments in Singapore that were part of a behavioral intervention study. The proposed model addresses several fundamental …

Adapting Taxation For The Digital Economy In Singapore, Vincent Ooi

Research Collection Yong Pung How School Of Law

The advent of the digital economy has had profound implications for taxation. Tax systems have been forced to adapt as they become increasingly unsuited for the realities of modern commerce. While Singapore has largely followed international developments, particularly in the area of international taxation, it has often made numerous innovative policy decisions in line with its national interests. The various policy decisions which Singapore has made on taxing the digital economy span both international and domestic tax. In the area of domestic tax, the examples have been further divided by subject matter, like e-commerce, digital tokens, automation, and electronic instruments. …

Applying 'Earable' Inertial Sensing For Real-Time Head Posture Detection, Meeralakshmi Radhakrishnan, Kushaan Misra, V. Ravichandran

Research Collection School Of Computing and Information Systems

We explore the use of personal earable devices for detecting and correcting incorrect head postures, which can trigger the medical condition of “Forward Head Posture”. We demonstrate how the gyroscope and accelerometer sensors on an earable device can be used to detect episodes where the head is rotated sufficiently forward, for significantly long durations (> 30secs), and then generate suitable audio-based corrective feedback. Using a small-scale preliminary study, we show that our approach is promising as it provides both high precision (100%) & recall (89%).

Learning To Assess The Quality Of Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermúdez I Badia

Research Collection School Of Computing and Information Systems

Due to the limited number of therapists, task-oriented exercises are often prescribed for post-stroke survivors as in-home rehabilitation. During in-home rehabilitation, a patient may become unmotivated or confused to comply prescriptions without the feedback of a therapist. To address this challenge, this paper proposes an automated method that can achieve not only qualitative, but also quantitative assessment of stroke rehabilitation exercises. Specifically, we explored a threshold model that utilizes the outputs of binary classifiers to quantify the correctness of a movements into a performance score. We collected movements of 11 healthy subjects and 15 post-stroke survivors using a Kinect sensor …

Privacy-Preserving Multi-Keyword Searchable Encryption For Distributed Systems, Xueqiao Liu, Guomin Yang, Willy Susilo, Joseph Tonien, Jian Shen

Research Collection School Of Computing and Information Systems

As cloud storage has been widely adopted in various applications, how to protect data privacy while allowing efficient data search and retrieval in a distributed environment remains a challenging research problem. Existing searchable encryption schemes are still inadequate on desired functionality and security/privacy perspectives. Specifically, supporting multi-keyword search under the multi-user setting, hiding search pattern and access pattern, and resisting keyword guessing attacks (KGA) are the most challenging tasks. In this article, we present a new searchable encryption scheme that addresses the above problems simultaneously, which makes it practical to be adopted in distributed systems. It not only enables multi-keyword …

Traceable Monero: Anonymous Cryptocurrency With Enhanced Accountability, Yannan Li, Guomin Yang, Wily Susilo, Yong Yu, Man Ho Au, Dongxi Liu

Research Collection School Of Computing and Information Systems

Monero provides a high level of anonymity for both users and their transactions. However, many criminal activities might be committed with the protection of anonymity in cryptocurrency transactions. Thus, user accountability (or traceability) is also important in Monero transactions, which is unfortunately lacking in the current literature. In this paper, we fill this gap by introducing a new cryptocurrency named Traceable Monero to balance the user anonymity and accountability. Our framework relies on a tracing authority, but is optimistic, in that it is only involved when investigations in certain transactions are required. We formalize the system model and security model …

Improving Multi-Hop Knowledge Base Question Answering By Learning Intermediate Supervision Signals, Gaole He, Yunshi Lan, Jing Jiang, Wayne Xin Zhao, Ji Rong Wen

Research Collection School Of Computing and Information Systems

Multi-hop Knowledge Base Question Answering (KBQA) aims to find the answer entities that are multiple hops away in the Knowledge Base (KB) from the entities in the question. A major challenge is the lack of supervision signals at intermediate steps. Therefore, multi-hop KBQA algorithms can only receive the feedback from the final answer, which makes the learning unstable or ineffective. To address this challenge, we propose a novel teacher-student approach for the multi-hop KBQA task. In our approach, the student network aims to find the correct answer to the query, while the teacher network tries to learn intermediate supervision signals …

All The Wiser: Fake News Intervention Using User Reading Preferences, Kuan Chieh Lo, Shih Chieh Dai, Aiping Xiong, Jing Jiang, Lun Wei Ku

Research Collection School Of Computing and Information Systems

To address the increasingly significant issue of fake news, we develop a news reading platform in which we propose an implicit approach to reduce people's belief in fake news. Specifically, we leverage reinforcement learning to learn an intervention module on top of a recommender system (RS) such that the module is activated to replace RS to recommend news toward the verification once users touch the fake news. To examine the effect of the proposed method, we conduct a comprehensive evaluation with 89 human subjects and check the effective rate of change in belief but without their other limitations. Moreover, 84% …

Trust And Retirement Preparedness: Evidence From Singapore, Benedict S. K. Koh, Olivia S. Mitchell, Joelle H. Fong

Research Collection Lee Kong Chian School Of Business

Trust is an essential component of any financial system, and distrust can undermine savings and economic growth. Our study draws on the Singapore Life Panel to assess how trust ties to older respondents’ (1) pension plan participation and withdrawals; (2) life, health, and long-term care insurance holdings; and (3) stock market engagement. We show that the widely-used ‘trust in people’ question is uncorrelated with household behaviours related to retirement preparedness. Instead, trust in private and public financial representatives is positively associated with pension savings, investments, and insurance holdings. Financial literacy also plays an important and consistent role in retirement decision-making.

Adversarial Meta Sampling For Multilingual Low-Resource Speech Recognition, Yubei Xiao, Ke Gong, Pan Zhou, Guolin Zheng, Xiaodan Liang, Liang Lin

Research Collection School Of Computing and Information Systems

Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledgegrounded dialogue systems often require a large number of dialogue instances to learn as they fail to capture the correlations between different diseases and neglect the diagnostic experience shared among them. To address this issue, we propose a more natural and practical paradigm, i.e., low-resource medical dialogue generation, which can transfer the diagnostic experience from source diseases to target ones with a handful of data for adaptation. It is capitalized on a commonsense knowledge graph to characterize the …

Mitigating Financial Fraud Risk With Data Analytics, Clarence Goh, Gary Pan

Research Collection School Of Accountancy

The risks associated with financial fraud that modern CFOs face today is particularly high. The same report examined Accounting and Auditing Enforcement Releases (AAERs) issued by the Securities and Exchange Commission (SEC) in the US from 2014 to 2019 and found that while the SEC frequently charged the person directly responsible for perpetuating the financial fraud, the CFO was among the most commonly charged employees. Data analytics techniques can play an important role in mitigating the risk of financial fraud for CFOs.

A Rule-Based Solution To The Appellate Body Crisis And Why The Mpia Would Not Work, Henry Gao

Research Collection Yong Pung How School Of Law

Over the past three years, the United States have been persistently blocking the appointment of members to the WTO Appellate Body, citing various concerns with its alleged “failure to follow the agreed rules”. The US blockage has resulted in an unprecedented crisis of the WTO dispute settlement system, which finally led to the paralysis of the Appellate Body in December 2019 when its member was reduced to the last one.

Initially focusing on the minor procedural errors of specific Appellate Body members, the US criticisms on the Appellate Body has morphed into broader attacks on the substantive jurisprudence and judicial …

Fault Analysis And Debugging Of Microservice Systems: Industrial Survey, Benchmark System, And Empirical Study, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, Dan Ding

Research Collection School Of Computing and Information Systems

The complexity and dynamism of microservice systems pose unique challenges to a variety of software engineering tasks such as fault analysis and debugging. In spite of the prevalence and importance of microservices in industry, there is limited research on the fault analysis and debugging of microservice systems. To fill this gap, we conduct an industrial survey to learn typical faults of microservice systems, current practice of debugging, and the challenges faced by developers in practice. We then develop a medium-size benchmark microservice system (being the largest and most complex open source microservice system within our knowledge) and replicate 22 industrial …

Graph-Evolving Meta-Learning For Low-Resource Medical Dialogue Generation, Shuai Lin, Pan Zhou, Xiaodan Liang, Jianheng Tang, Ruihui Zhao, Ziliang Chen, Liang Lin

Research Collection School Of Computing and Information Systems

Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledge-grounded dialogue systems often require a large number of dialogue instances to learn as they fail to capture the correlations between different diseases and neglect the diagnostic experience shared among them. To address this issue, we propose a more natural and practical paradigm, i.e., low-resource medical dialogue generation, which can transfer the diagnostic experience from source diseases to target ones with a handful of data for adaptation. It is capitalized on a commonsense knowledge graph to characterize the …

Scalable Verification Of Quantized Neural Networks, Thomas A. Henzinger, Mathias Lechner, Dorde Zikelic

Research Collection School Of Computing and Information Systems

Formal verification of neural networks is an active topic of research, and recent advances have significantly increased the size of the networks that verification tools can handle. However, most methods are designed for verification of an idealized model of the actual network which works over real arithmetic and ignores rounding imprecisions. This idealization is in stark contrast to network quantization, which is a technique that trades numerical precision for computational efficiency and is, therefore, often applied in practice. Neglecting rounding errors of such low-bit quantized neural networks has been shown to lead to wrong conclusions about the network’s correctness. Thus, …

An Exploratory Study On The Introduction And Removal Of Different Types Of Technical Debt In Deep Learning Frameworks, Jiakun Liu, Qiao Huang, Xin Xia, Emad Shihab, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

To complete tasks faster, developers often have to sacrifice the quality of the software. Such compromised practice results in the increasing burden to developers in future development. The metaphor, technical debt, describes such practice. Prior research has illustrated the negative impact of technical debt, and many researchers investigated how developers deal with a certain type of technical debt. However, few studies focused on the removal of different types of technical debt in practice. To fill this gap, we use the introduction and removal of different types of self-admitted technical debt (i.e., SATD) in 7 deep learning frameworks as an example. …

Norm-Based Generalisation Bounds For Deep Multi-Class Convolutional Neural Networks, Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

Research Collection School Of Computing and Information Systems

We show generalisation error bounds for deep learning with two main improvements over the state of the art. (1) Our bounds have no explicit dependence on the number of classes except for logarithmic factors. This holds even when formulating the bounds in terms of the Frobenius-norm of the weight matrices, where previous bounds exhibit at least a squareroot dependence on the number of classes. (2) We adapt the classic Rademacher analysis of DNNs to incorporate weight sharing—a task of fundamental theoretical importance which was previously attempted only under very restrictive assumptions. In our results, each convolutional filter contributes only once …

Fine-Grained Generalization Analysis Of Vector-Valued Learning, Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

Research Collection School Of Computing and Information Systems

Many fundamental machine learning tasks can be formulated as a problem of learning with vector-valued functions, where we learn multiple scalar-valued functions together. Although there is some generalization analysis on different specific algorithms under the empirical risk minimization principle, a unifying analysis of vector-valued learning under a regularization framework is still lacking. In this paper, we initiate the generalization analysis of regularized vector-valued learning algorithms by presenting bounds with a mild dependency on the output dimension and a fast rate on the sample size. Our discussions relax the existing assumptions on the restrictive constraint of hypothesis spaces, smoothness of loss …

Project Coolbit: Can Your Watch Predict Heat Stress And Thermal Comfort Sensation?, Negin Nazarian, Sijie Liu, Manon Kohler, Jason Lee, Clayton Miller, Winston T. L. Chow, S. B. B. Alhadad, Alberto Martilli, Matias Quintana, Lindsey Sunden, Lindsey Norford

Research Collection School of Social Sciences

Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laboratory experiments), however, present several limitations: measurements are scattered in time and space and data gathered on outdoor thermal stress and comfort often does not include physiological and behavioral parameters. To address these shortcomings, Project Coolbit aims to introduce a human-centric approach to thermal comfort assessments. In this study, we propose and evaluate …

Seeking Control During Uncontrollable Times: Control Abilities And Religiosity Predict Stress During Covid-19, Shi Ann Shuna Khoo, Wei Xing Toh, Hwajin Yang

Research Collection School of Social Sciences

The COVID-19 pandemic has created an urgent need to understand the protective factors that can buffer individuals against psychological distress. We employed a latent-variable approach to examine how control-related factors such as religiosity, self-control, cognitive control, and health locus of control can act as resilience resources during stressful periods. We found that cognitive control emerged as a protective factor against COVID-19-related stress, whereas religiosity predicted a heightened level of stress. These results provide novel insights into control factors that can safeguard individuals' psychological well-being during crises such as a pandemic.

Brief Mindfulness Breathing Exercises And Working Memory Capacity: Findings From Two Experimental Approaches, Frosch Y. X. Quek, Nadyanna M. Majeed, Meenakshi Kothari, Verity Y. Q. Lua, Hee Seng Ong, Andree Hartanto

Research Collection School of Social Sciences

Mindfulness training has been extensively researched and found to elicit positive effects on cognitive performance, including working memory capacity. Benefits to cognitive function have been extended to brief mindfulness training as well. However, not much is known about its effect on working memory capacity. The current study examined the effects of a single 15-min session of mindful attention to breathing compared to a 15-min session of mind-wandering exercise in a within-subjects experimental design (Study 1; N = 82) and a between-subjects experimental design (Study 2; N = 424). Contrary to our hypotheses, in both experiments, we did not find any …

Financial Literacy And Financial Decision-Making At Older Ages, Joelle H. Fong, Seng Kee Benedict Koh, Olivia S. Mitchell, Susann Rohwedder

Research Collection Lee Kong Chian School Of Business

How well older households manage their wealth holdings is an important determinant of their financial security during retirement, yet little is known about their financial decision-making and how this relates to their financial literacy. Our paper fills this gap by measuring financial literacy among older persons in the Singapore Life Panel and examining its association with timely credit card debt repayment, stock market participation, and age-based investment risk diversification. Most older respondents understand interest compounding and inflation, but fewer than half know about risk diversification. Almost all older credit card holders pay off their balances in a timely manner, but …

Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su

Research Collection School Of Economics

We propose a procedure to identify latent group structures in nonlinear panel data models where some regression coefficients are heterogeneous across groups but homogeneous within a group and the group number and membership are unknown. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method is able to identify …

Treecaps: Tree-Based Capsule Networks For Source Code Processing, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Recently program learning techniques have been proposed to process source code based on syntactical structures (e.g., Abstract Syntax Trees) and/or semantic information (e.g., Dependency Graphs). While graphs may be better at capturing various viewpoints of code semantics than trees, constructing graph inputs from code need static code semantic analysis that may not be accurate and introduces noise during learning. On the other hand, syntax trees are precisely defined according to the language grammar and easier to construct and process than graphs. We propose a new tree-based learning technique, named TreeCaps, by fusing capsule networks with tree-based convolutional neural networks, to …

Culturally Diverse Expert Teams Have Yet To Bring Comprehensive Linguistic Diversity To Intergovernmental Ecosystem Assessments, Abigail J. Lynch, Fernández-Llamazares Álvaro, Ignacio Palomo, Pedro Jaureguiberry, Amano Tatsuya, Zeenatul Basher, Michelle Lim, Tuyeni Heita Mwampamba, Aibek Samakov, Odirilwe Selomane, Michelle Mei Ling Lim

Research Collection Yong Pung How School Of Law

Multicultural representation is a stated goal of many global scientific assessment processes. These processes aim to mobilize a broader, more diverse knowledge base and increase legitimacy and inclusiveness of these assessment processes. Often, enhancing cultural diversity is encouraged through involvement of diverse expert teams and sources of knowledge in different languages. In this article, we examine linguistic diversity, as one representation of cultural diversity, in the eight published assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). Our results show that the IPBES assessment outputs are disproportionately filtered through English-language literature and authors from Anglophone countries. To …

Hurricane Harvey: Equal Opportunity Storm Or Disparate Disaster?, Katherine Lieberknecht, Deidre Zoll, Junfeng Jiao, Katherine Castles

Research Collection College of Integrative Studies

In the wake of Hurricane Harvey, multiple media sources claimed the event was an “equal opportunity” storm. These claims challenge existing social vulnerability research that finds marginalised groups have both unequal risk exposure and subsequent differential impacts from disasters (Cutter, Boruff, and Shirley 2003, “Assessing Current and Future Freshwater Flood Risk from North Atlantic Tropical Cyclones via Insurance Claims.” Scientific Reports 7 (February): 41609; Faber 2015, “Superstorm Sandy and the Demographics of Flood Risk in New York City.” Human Ecology 43 (3): 363–378. https://doi.org/10.1007/s10745-015-9757-x; Thomas et al. 2013, Social Vulnerability to Disasters. Boca Raton, FL: CRC Press). To understand the …