Open Access. Powered by Scholars. Published by Universities.®
Management Sciences and Quantitative Methods Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Finance and Financial Management (9)
- Strategic Management Policy (7)
- Marketing (6)
- Operations and Supply Chain Management (5)
- Physical Sciences and Mathematics (4)
-
- Social and Behavioral Sciences (3)
- Asian Studies (2)
- Business Analytics (2)
- International and Area Studies (2)
- Organizational Behavior and Theory (2)
- Technology and Innovation (2)
- Accounting (1)
- Arts Management (1)
- Business Administration, Management, and Operations (1)
- Business Law, Public Responsibility, and Ethics (1)
- Corporate Finance (1)
- Education (1)
- Environmental Sciences (1)
- Instructional Media Design (1)
- Medicine and Health Sciences (1)
- Psychology (1)
- Public Health (1)
- Statistics and Probability (1)
- Keyword
-
- Reproducibility (3)
- Chaos (2)
- Data (2)
- Forecasting (2)
- Innovation (2)
-
- Machine Learning (2)
- Management research (2)
- Meta-analysis (2)
- Methodology (2)
- Replication (2)
- Sampling (2)
- Singapore (2)
- Airport gate allocation (1)
- Ambiguity (1)
- Article success (1)
- Assembly lines (1)
- Autonomia (1)
- Bayesian updating (1)
- Behavioral decision theory (1)
- Big Data (1)
- Biobargain (1)
- Brand equity (1)
- Brand value (1)
- Brownian motion (1)
- Bucket brigade (1)
- Bucket brigades (1)
- By-product synergy (1)
- CAViaR (1)
- COVID-19 (1)
- CREEP (1)
Articles 1 - 30 of 48
Full-Text Articles in Management Sciences and Quantitative Methods
Heroclix®: A Multiplayer Chess Game For Teaching The Fundamentals Of Human Capital Management, Chin Heng Low, Jiunwen Wang, Paul Lim, Bernie Koh
Heroclix®: A Multiplayer Chess Game For Teaching The Fundamentals Of Human Capital Management, Chin Heng Low, Jiunwen Wang, Paul Lim, Bernie Koh
Research Collection Lee Kong Chian School Of Business
This article describes the adaptation and use of the HeroClix® board game to teach critical real-world principles for effective human capital management within teams. In a HeroClix® game, players pit their team of miniature figurines against other players’ miniatures in combat. This is akin to organizations striving in the business environment today, with well-structured human capital within their teams as a key competitive advantage. In this article, we suggest how the game can be applied in the classroom for undergraduate students to experience, reflect on, and learn more about the prerequisite considerations in proficient people management, the dynamic nature of …
The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou
The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou
Research Collection Lee Kong Chian School Of Business
Over the last decade, there has been an explosion in the use of diverse data sources by management scholars to observe and capture managerial and organizational constructs that have historically been difficult to access. This surge has been driven by the growing availability of rich, multi-modal data—textual, image, and audio (Luo, Jia, Ouyang, & Fang, 2024)—together with advances in analytical techniques to process and analyze data, such as computer-aided text analysis (Harrison, Thurgood, Boivie, & Pfarrer, 2019), machine learning (Choudhury, Wang, Carlson, & Khanna, 2019; Harrison, Josefy, Kalm, & Krause, 2023), and deep learning (Gouvard, Goldberg, & Srivastava, 2023). These …
Nonstandard Errors, Albert J. Menkeld, Shihao Yu, Et Al.
Nonstandard Errors, Albert J. Menkeld, Shihao Yu, Et Al.
Research Collection Lee Kong Chian School Of Business
Duplicate record, see https://ink.library.smu.edu.sg/lkcsb_research/7633/. In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty - nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by …
Nonstandard Errors, Albert J. Menkvelt, Anna Dreber, Et Al., Shihao Yu, Bart Zhou Yueshen, Emiliano Sebastian Pagnotta
Nonstandard Errors, Albert J. Menkvelt, Anna Dreber, Et Al., Shihao Yu, Bart Zhou Yueshen, Emiliano Sebastian Pagnotta
Research Collection Lee Kong Chian School Of Business
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
Covid-19 And Management Scholarship: Lessons For Conducting Impactful Research, Gerard George, Gokhan Ertug, Jonathan P. Doh, Johanna Mair, Ajnesh Prasad
Covid-19 And Management Scholarship: Lessons For Conducting Impactful Research, Gerard George, Gokhan Ertug, Jonathan P. Doh, Johanna Mair, Ajnesh Prasad
Research Collection Lee Kong Chian School Of Business
The COVID-19 pandemic provided an opportunity for management scholars to address large-scale and complex societal problems and strive for greater practical and policy impact. A brief overview of the most-cited work on COVID-19 reveals that, compared with their counterparts in other disciplines, leading management journals and professional associations lagged in providing a platform for high-impact research on COVID-19. To help management research play a more active role in responding to similar global challenges in the future, we propose an integrative framework that emphasizes a phenomenon’s impact, the conditions that the phenomenon creates at multiple levels, and the responses of actors …
From The Editors: Mobilizing New Sources Of Data: Opportunities And Recommendations, Denis A. Gregoire, Anne L. J. Ter Wal, Laura M. Little, Sekou Bermiss, Reddi Kotha, Marc Gruber
From The Editors: Mobilizing New Sources Of Data: Opportunities And Recommendations, Denis A. Gregoire, Anne L. J. Ter Wal, Laura M. Little, Sekou Bermiss, Reddi Kotha, Marc Gruber
Research Collection Lee Kong Chian School Of Business
In June 2008, the U.S.-based website Glassdoor.com began posting anonymous company reviews and salary data from current and former employees of various organizations. Doing so not only brought to the world information that had hitherto been restricted to private circles, it spontaneously prompted some organizations to alter their workplace practices (Dineen & Allen, 2016; Dube & Zhu, 2021). At the same time, Glassdoor’s very activities gave rise to a completely new source of data for exploring a wealth of management and organizational phenomena (e.g., Bermiss & McDonald, 2018; Rhee, 2024). As this example illustrates, new data sources can not only …
Reproducibility In Management Science, MiloˇS Fišar, Ben Greiner, Christoph Huber, Elena Katok, Ali I. Ozkes, Hannah H. Chang
Reproducibility In Management Science, MiloˇS Fišar, Ben Greiner, Christoph Huber, Elena Katok, Ali I. Ozkes, Hannah H. Chang
Research Collection Lee Kong Chian School Of Business
With the help of more than 700 reviewers, we assess the reproducibility of nearly 500 articles published in the journal Management Science before and after the introduction of a new Data and Code Disclosure policy in 2019. When considering only articles for which data accessibility and hardware and software requirements were not an obstacle for reviewers, the results of more than 95% of articles under the new disclosure policy could be fully or largely computationally reproduced. However, for 29% of articles, at least part of the data set was not accessible to the reviewer. Considering all articles in our sample …
Correcting For Range Restriction In Meta-Analysis: A Reply To Oh Et Al. (2023), Paul R. Sackett, Christopher M. Berry, Filip Lievens, Charlene Zhang
Correcting For Range Restriction In Meta-Analysis: A Reply To Oh Et Al. (2023), Paul R. Sackett, Christopher M. Berry, Filip Lievens, Charlene Zhang
Research Collection Lee Kong Chian School Of Business
Oh et al. (2023) question a number of choices made in our article (Sackett et al., 2022); here we respond. They interpret our article as recommending against correcting for range restriction in general in concurrent validation studies; yet, we emphasize that we endorse correction when one has access to the information needed to do so. Our focus was on making range restriction corrections when conducting meta-analyses, where it is common for primary studies to be silent as to the prior basis for selection of the employees later participating in the concurrent validation study. As such, the applicant pool information needed …
Scaled Pca: A New Approach To Dimension Reduction, Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou
Scaled Pca: A New Approach To Dimension Reduction, Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou
Research Collection Lee Kong Chian School Of Business
This paper proposes a novel supervised learning technique for forecasting: scaled principal component analysis (sPCA). The sPCA improves the traditional principal component analysis (PCA) by scaling each predictor with its predictive slope on the target to be forecasted. Unlike the PCA that maximizes the common variation of the predictors, the sPCA assigns more weight to those predictors with stronger forecasting power. In a general factor framework, we show that, under some appropriate conditions on data, the sPCA forecast beats the PCA forecast, and when these conditions break down, extensive simulations indicate that the sPCA still has a large chance to …
Smart Manufacturing And Its Implications For Singapore's Smes, Thomas Menkhoff, Surianarayanan Gopalakrishnan
Smart Manufacturing And Its Implications For Singapore's Smes, Thomas Menkhoff, Surianarayanan Gopalakrishnan
Research Collection Lee Kong Chian School Of Business
While Covid-19 and the climate catastrophe continue to make headlines, local small and medium-sized enterprises (SMEs) are quietly setting the gears of Smart Manufacturing in motion with a strategic focus on digitising and automating production processes powered by "Industry 4.0" (I4.0) ready business models. A shared view among several interviewees we talked to recently in the context of an ongoing study on the impact of I4.0 on the business models of local manufacturers is that Industrial Internet-of-Things (IIoT), machine learning, visual computing, automation and digital twining are deemed of great importance for the long-term competitiveness of Singapore's manufacturing ecosystem on …
A Review Study Of Functional Autoregressive Models With Application To Energy Forecasting, Ying Chen, Thorsten Koch, Kian Guan Lim, Xiaofei Xu, Nazgul Zakiyeva
A Review Study Of Functional Autoregressive Models With Application To Energy Forecasting, Ying Chen, Thorsten Koch, Kian Guan Lim, Xiaofei Xu, Nazgul Zakiyeva
Research Collection Lee Kong Chian School Of Business
In this data‐rich era, it is essential to develop advanced techniques to analyze and understand large amounts of data and extract the underlying information in a flexible way. We provide a review study on the state‐of‐the‐art statistical time series models for univariate and multivariate functional data with serial dependence. In particular, we review functional autoregressive (FAR) models and their variations under different scenarios. The models include the classic FAR model under stationarity; the FARX and pFAR model dealing with multiple exogenous functional variables and large‐scale mixed‐type exogenous variables; the vector FAR model and common functional principal component technique to handle …
From Actions To Paths To Patterning: Toward A Dynamic Theory Of Patterning In Routines, Kenneth T. Goh, Brian T. Pentland
From Actions To Paths To Patterning: Toward A Dynamic Theory Of Patterning In Routines, Kenneth T. Goh, Brian T. Pentland
Research Collection Lee Kong Chian School Of Business
This paper demonstrates a new way of seeing and theorizing about the dynamics of organizational routines through the concept of paths – time-ordered sequences of actions or events in performing work. Empirically and conceptually, paths provide the missing link between specific actions and patterns of action. When routines are represented as a narrative network, tracing the formation and dissolution of action paths can generate new insights about the dynamic patterning of actions in routine performances. We traced action paths using longitudinal field data from a videogame development project and found that action patterns change dramatically over time based on the …
Machine Learning Using Instruments For Text Selection: Predicting Innovation Performance, Kian Guan Lim, Michelle S. J. Lim
Machine Learning Using Instruments For Text Selection: Predicting Innovation Performance, Kian Guan Lim, Michelle S. J. Lim
Research Collection Lee Kong Chian School Of Business
In machine learning we utilize the idea of employing instrumental variable such as patent records to train the texts. Patent records are highly correlated with R&D expenditures, but are not necessarily correlated with performance residuals not linked to R&D. Thus, using instrumental patent records to train word counts of selected texts to serve as a proxy for firm R&D expenditure, we show that the texts and associated word counts provide effective prediction of firm innovation performances such as firm market value and total sales growth.
Bridging The Data Divide Between Practitioners And Academics: Approaches To Collaborating Better To Leverage Each Other's Resources, Sabine Benoit, Sonja Klose, Jochen Wirtz, Tor Wallin Andreassen, Timothy L. Keininghas
Bridging The Data Divide Between Practitioners And Academics: Approaches To Collaborating Better To Leverage Each Other's Resources, Sabine Benoit, Sonja Klose, Jochen Wirtz, Tor Wallin Andreassen, Timothy L. Keininghas
Research Collection Lee Kong Chian School Of Business
Purpose: Organizations (data gatherers in the context) drown in data while at the same time seeking managerially relevant insights. Academics (data hunters) have to deal with decreasing respondent participation and escalating costs of data collection while at the same time seeking to increase the managerial relevance of their research. The purpose of this paper is to provide a framework on how, managers and academics can collaborate better to leverage each other's resources. Design/methodology/approach: This research synthesizes the academic and the managerial literature on the realities and priorities of practitioners and academics with regard to data. Based on the literature, reflections …
Optimal Control And Cooperative Game Theory Based Analysis Of A By-Product Synergy System, Mahmut Parlar, Sharafali Moosa, Mark Goh
Optimal Control And Cooperative Game Theory Based Analysis Of A By-Product Synergy System, Mahmut Parlar, Sharafali Moosa, Mark Goh
Research Collection Lee Kong Chian School Of Business
In this paper, we propose a framework to analyse the setting up of an industrial symbiosis system. The establishment of such a system entails implementation of expensive technologies by the companies so as to convert wastes into energy and other mutually beneficial materials. Much of the literature on modeling industrial symbiosis do not consider this important aspect of high conversion costs. Further, such a cooperative effort will be sustainable only if the high cost of implementing technologies is compensated by sharing of the benefits in a fair and satisfactory manner. Towards this end, first at a general level, we addres …
Balancing Machine And Human Skill Sets, Richard Raymond Smith
Balancing Machine And Human Skill Sets, Richard Raymond Smith
Research Collection Lee Kong Chian School Of Business
How do we navigate in this fourth industrial revolution that blurs the lines between the physical and digital worlds?
To Give Or Not To Give? Choosing Chance Under Moral Conflict, Stephanie C. Lin, Taly Reich
To Give Or Not To Give? Choosing Chance Under Moral Conflict, Stephanie C. Lin, Taly Reich
Research Collection Lee Kong Chian School Of Business
Although prior research suggests that people should not prefer random chance to determine their outcomes, we propose that in the context of prosocial requests, a contingent of people prefer to rely on chance. We argue that this is because they are conflicted between losing resources (e.g., time, money) and losing moral selfregard. Across five studies, in both choices with binary outcomes (whether to volunteer) and ranges of outcomes (how much to donate), some people preferred to be randomly assigned an outcome rather than to make their own choices. This did not negatively affect prosocial behavior in binary choices and improved …
Projecting Lower Competence To Maintain Moral Warmth In The Avoidance Of Prosocial Requests, Peggy J. Liu, Stephanie C. Lin
Projecting Lower Competence To Maintain Moral Warmth In The Avoidance Of Prosocial Requests, Peggy J. Liu, Stephanie C. Lin
Research Collection Lee Kong Chian School Of Business
When faced with prosocial requests, consumers face a difficult decision between taking on the request’s burden or appearing unwarm (unkind, uncaring). We propose that the desire to refuse such requests while protecting a morally warm image leads consumers to under-represent their competence. Although consumers care strongly about being viewed as competent, five studies showed that they downplayed their competence to sidestep a prosocial request. This effect occurred across both self-reported and behavioral displays of competence. Further, the downplaying competence effect only occurred when facing an undesirable prosocial request, not a similarly undesirable proself request. The final studies showed that people …
Showcasing The Diversity Of Service Research: Theories, Methods, And Success Of Service Articles, Sabine Benoit, Katrin Scherschel, Zelal Ates, Linda Nasr, Jay Kandampully
Showcasing The Diversity Of Service Research: Theories, Methods, And Success Of Service Articles, Sabine Benoit, Katrin Scherschel, Zelal Ates, Linda Nasr, Jay Kandampully
Research Collection Lee Kong Chian School Of Business
Purpose: The purpose of this paper is to make two main contributions: first, showcase the diversity of service research in terms of the variety of used theories and methods, and second, explain (post-publication) success of articles operationalized as interest in an article (downloads), usage (citations), and awards (best paper nomination). From there, three sub-contributions are derived: stimulate a dialogue about existing norms and practices in the service field, enable and encourage openness amongst service scholars, and motivate scholars to join the field. Design/methodology/approach: A mixed method approach is used in combining quantitative and qualitative research methods while analyzing 158 Journal …
Revisiting The Small-World Phenomenon: Efficiency Variation And Classification Of Small-World Networks, Tore Opsahl, Antoine Vernet, Tufool Alnuaimi, Gerard George
Revisiting The Small-World Phenomenon: Efficiency Variation And Classification Of Small-World Networks, Tore Opsahl, Antoine Vernet, Tufool Alnuaimi, Gerard George
Research Collection Lee Kong Chian School Of Business
Research has explored how embeddedness in small-world networks influences individual and firm outcomes. We show that there remains significant heterogeneity among networks classified as small-world networks. We develop measures of the efficiency of a network, which allow us to refine predictions associated with small-world networks. A network is classified as a small-world network if it exhibits a distance between nodes that is comparable to the distance found in random networks of similar sizeswith ties randomly allocated among nodesin addition to containing dense clusters. To assess how efficient a network is, there are two questions worth asking: (a) What is a …
Big Data And Data Science Methods For Management Research: From The Editors, Gerard George, Ernst C. Osinga, Dovev Lavie, Brent A. Scott
Big Data And Data Science Methods For Management Research: From The Editors, Gerard George, Ernst C. Osinga, Dovev Lavie, Brent A. Scott
Research Collection Lee Kong Chian School Of Business
The recent advent of remote sensing, mobile technologies, novel transaction systems, and high performance computing offers opportunities to understand trends, behaviors, and actions in a manner that has not been previously possible. Researchers can thus leverage 'big data' that are generated from a plurality of sources including mobile transactions, wearable technologies, social media, ambient networks, and business transactions. An earlier AMJ editorial explored the potential implications for data science in management research and highlighted questions for management scholarship, and the attendant challenges of data sharing and privacy (George, Haas & Pentland, 2014). This nascent field is evolving rapidly and at …
The Pipeline Project: Pre-Publication Independent Replications Of A Single Laboratory's Research Pipeline, Martin Schweinsberg, Nikhil Madan, Michelangelo Vianello, S.Amy Sommer, Jennifer Jordan, Et Al, Michael Schaerer
The Pipeline Project: Pre-Publication Independent Replications Of A Single Laboratory's Research Pipeline, Martin Schweinsberg, Nikhil Madan, Michelangelo Vianello, S.Amy Sommer, Jennifer Jordan, Et Al, Michael Schaerer
Research Collection Lee Kong Chian School Of Business
This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had “in the pipeline” as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one …
Portfolio Manager Compensation And Mutual Fund Performance, Linlin Ma, Yuehua Tang, Juan-Pedro Gomez
Portfolio Manager Compensation And Mutual Fund Performance, Linlin Ma, Yuehua Tang, Juan-Pedro Gomez
Research Collection Lee Kong Chian School Of Business
We use a novel dataset to study the relation between individual portfolio manager compensation and mutual fund performance. Managers with explicit performance-based pay exhibit superior subsequent fund performance, especially when investment advisors link pay to performance over a longer time period. In contrast, alternative compensation arrangements, such as fixed salary, assets-based pay, or advisor-profits-based pay are not associated with superior performance. Our tests further show that the positive relation between performance-based contracts and fund performance is not driven by the selection of talented managers proxied by education background. Lastly, managers with performance-based pay engage less in risk-shifting activities.
New Approach To Density Estimation And Application To Value-At-Risk, Kian Guan Lim, Hao Cheng, Nelson K. L. Yap
New Approach To Density Estimation And Application To Value-At-Risk, Kian Guan Lim, Hao Cheng, Nelson K. L. Yap
Research Collection Lee Kong Chian School Of Business
The key contribution in this paper is to provide a new approach in estimating the physical distribution of the underlying asset return by using a quadratic Radon-Nikodym derivative function. The latter function transforms a fitted Variance Gamma risk-neutral distribution that is obtained from traded option prices. The generality of the VG distribution helps to avoid unnecessary mis-specification bias. The estimated empirical distribution is then used to find the risk measure of VaR. We show that possible underestimation of VaR risk using existing methods is largely not due to VaR itself but perhaps due to mis-specification errors which we minimize in …
Estimating The Reproducibility Of Psychological Science, Alexander A. Aarts, Et Al, Stephanie C. Lin
Estimating The Reproducibility Of Psychological Science, Alexander A. Aarts, Et Al, Stephanie C. Lin
Research Collection Lee Kong Chian School Of Business
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if …
Big Data And Management: From The Editors, Gerard George, Martine R. Haas, Alex Pentland
Big Data And Management: From The Editors, Gerard George, Martine R. Haas, Alex Pentland
Research Collection Lee Kong Chian School Of Business
Big data is everywhere. In recent years, there has been an increasing emphasis on big data, business analytics, and "smart" living and work environments. Though these conversations are predominantly practice driven, organizations are exploring how large-volume data can usefully be deployed to create and capture value for individuals, businesses, communities, and governments (McKinsey Global Institute, 2011). Whether it is machine learning and web analytics to predict individual action, consumer choice, search behavior, traffic patterns, or disease outbreaks, big data is fast becoming a tool that not only analyzes patterns, but can also provide the predictive likelihood of an event.
Global Warming, Extreme Weather Events, And Forecasting Tropical Cyclones: A Market-Based Forward-Looking Approach, Carolyn W. Chang, Jack S. K. Chang, Kian Guan Lim
Global Warming, Extreme Weather Events, And Forecasting Tropical Cyclones: A Market-Based Forward-Looking Approach, Carolyn W. Chang, Jack S. K. Chang, Kian Guan Lim
Research Collection Lee Kong Chian School Of Business
Global warming has more than doubled the likelihood of extreme weather events, e.g. the 2003 European heat wave, the growing intensity of rain and snow in the Northern Hemisphere, and the increasing risk of flooding in the United Kingdom. It has also induced an increasing number of deadly tropical cyclones with a continuing trend. Many individual meteorological dynamic simulations and statistical models are available for forecasting hurricanes but they neither forecast well hurricane intensity nor produce clear-cut consensus. We develop a novel hurricane forecasting model by straddling two seemingly unrelated disciplines — physical science and finance — based on the …
Asset Performance Evaluation With Mean-Variance Ratio, Zhidong Bai, Kok Fai Phoon, Keyan Wang, Wing-Keung Wong
Asset Performance Evaluation With Mean-Variance Ratio, Zhidong Bai, Kok Fai Phoon, Keyan Wang, Wing-Keung Wong
Research Collection Lee Kong Chian School Of Business
Bai, et al. (2011c) develop the mean-variance-ratio (MVR) statistic to test the performance among assets for small samples. They provide theoretical reasoning to use MVR and prove that our proposed statistic is uniformly most powerful unbiased. In this paper we illustrate the superiority of our proposed test over the Sharpe ratio (SR) test by applying both tests to analyze the performance of Commodity Trading Advisors (CTAs). Our findings show that while the SR test concludes most of the CTA funds being analyzed as being indistinguishable in their performance, our proposed statistics show that some funds outperform the others. On the …
Index-Exciting Caviar: A New Empirical Time-Varying Risk Model, Dashan Huang, Baimin Yu, Zudi Lu, Sergio Focardi, Frank Fabozzi, Masao Fukushima
Index-Exciting Caviar: A New Empirical Time-Varying Risk Model, Dashan Huang, Baimin Yu, Zudi Lu, Sergio Focardi, Frank Fabozzi, Masao Fukushima
Research Collection Lee Kong Chian School Of Business
Instead of assuming the distribution of return series, Engle and Manganelli (2004) propose a new Value-at-Risk (VaR) modeling approach, Conditional Autoregressive Value-at-Risk (CAViaR), to directly compute the quantile of an individual asset's returns which performs better in many cases than those that invert a return distribution. In this paper we explore more flexible CAViaR models that allow VaR prediction to depend upon a richer information set involving returns on an index. Specifically, we formulate a time-varying CAViaR model whose parameters vary according to the evolution of the index. The empirical evidence reported in this paper suggests that our time-varying CAViaR …
An Investigation Of Value Updating Bidders In Simultaneous Online Art Auctions, Mayukh Dass, Lynne Seymour, Srinivas K. Reddy
An Investigation Of Value Updating Bidders In Simultaneous Online Art Auctions, Mayukh Dass, Lynne Seymour, Srinivas K. Reddy
Research Collection Lee Kong Chian School Of Business
Simultaneous online auctions, in which the auction of all items being sold starts at the same time and ends at the same time, are becoming popular especially in selling items such as collectables and art pieces. In this paper, we analyze the characteristics of bidders (Reactors) in simultaneous auctions who update their pre-auction value of an item in the presence of influencing bidders (Influencers). We represent an auction as a network of bidders where the nodes represent the bidders participating in the auction and the ties between them represent an Influencer?Reactor relationship. We further develop a random effects bilinear model …