The actions associated with business decisions are guided by a range of variables, that include: opportunities, funding types, customer categories, competencies, proposal status, resource feasibility, technical feasibility, capability increase, risk level and commitment. The analysis of these decision variables or more likely the data associated with them is based on using descriptive, predictive, or prescriptive analytics as a means of “searching for answers” to the business problems and issues confronting the enterprise. Cognitive analytics embodies a fourth area of decision support that facilitates the analysis of structured and unstructured data sources and the use of natural language processing, learning and reasoning capabilities to enhance hypothesis generation. In short, cognitive analytics enables the enterprise to “ask the right questions” surrounding the evidence. This research highlights the impact of cognitive analytics in making evidence-based decision actions – specifically by modeling “what if” scenarios concerning the impact of resource and schedule on project risk associated with the development of a new product using IBM SPSS Modeler and IBM Watson Analytics.
{"title":"Cognitive Analytics for Making Better Evidence-Based Decisions","authors":"Chris Asakiewicz","doi":"10.2139/ssrn.2965767","DOIUrl":"https://doi.org/10.2139/ssrn.2965767","url":null,"abstract":"The actions associated with business decisions are guided by a range of variables, that include: opportunities, funding types, customer categories, competencies, proposal status, resource feasibility, technical feasibility, capability increase, risk level and commitment. \u0000The analysis of these decision variables or more likely the data associated with them is based on using descriptive, predictive, or prescriptive analytics as a means of “searching for answers” to the business problems and issues confronting the enterprise. Cognitive analytics embodies a fourth area of decision support that facilitates the analysis of structured and unstructured data sources and the use of natural language processing, learning and reasoning capabilities to enhance hypothesis generation. In short, cognitive analytics enables the enterprise to “ask the right questions” surrounding the evidence. \u0000This research highlights the impact of cognitive analytics in making evidence-based decision actions – specifically by modeling “what if” scenarios concerning the impact of resource and schedule on project risk associated with the development of a new product using IBM SPSS Modeler and IBM Watson Analytics.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84653215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many content websites seek to encourage user participation, which has been shown to increase user satisfaction and propensity to contribute. Yet this study shows that such encouragement can cause users to expose themselves to potentially harmful consequences, by enhancing their trust in the website and leading them to be more willing to reveal personal information. We perform a series of empirical experiments, utilizing a website called VideoBook, a YouTube-like video browsing platform that provides the opportunity to study users’ behaviors and perceptions in a realistic environment and under lab conditions. We find that users who are exposed to prompts that require them to engage with the website (rate videos) subsequently report higher trust in the site and reveal more personal information, compared with users who are not exposed to such prompts. Exposure to prompts does not affect users’ general attitudes regarding privacy. We test alternative scenarios to attempt to identify the sources of the phenomena, and we link our results to previous work on website-initiated participation and self-perception theory. We discuss both theoretical and policy implications.
{"title":"The Dark Side of User Participation - The Effect of Calls to Action on Trust and Information Revelation","authors":"N. Tzur, Lior Zalmanson, Gal Oestreicher-Singer","doi":"10.2139/ssrn.2814903","DOIUrl":"https://doi.org/10.2139/ssrn.2814903","url":null,"abstract":"Many content websites seek to encourage user participation, which has been shown to increase user satisfaction and propensity to contribute. Yet this study shows that such encouragement can cause users to expose themselves to potentially harmful consequences, by enhancing their trust in the website and leading them to be more willing to reveal personal information. We perform a series of empirical experiments, utilizing a website called VideoBook, a YouTube-like video browsing platform that provides the opportunity to study users’ behaviors and perceptions in a realistic environment and under lab conditions. We find that users who are exposed to prompts that require them to engage with the website (rate videos) subsequently report higher trust in the site and reveal more personal information, compared with users who are not exposed to such prompts. Exposure to prompts does not affect users’ general attitudes regarding privacy. We test alternative scenarios to attempt to identify the sources of the phenomena, and we link our results to previous work on website-initiated participation and self-perception theory. We discuss both theoretical and policy implications.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90581461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors. Design/methodology/approach Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors. Findings Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus. Originality/value These refinements were not presented in prior literature and can be useful to financial analysts and investors.
{"title":"Refining Financial Analysts’ Forecasts by Predicting Earnings Forecast Errors","authors":"Tatiana Fedyk","doi":"10.2139/ssrn.2931636","DOIUrl":"https://doi.org/10.2139/ssrn.2931636","url":null,"abstract":"Purpose \u0000 \u0000 \u0000 \u0000 \u0000The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors. \u0000 \u0000 \u0000 \u0000 \u0000Design/methodology/approach \u0000 \u0000 \u0000 \u0000 \u0000Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors. \u0000 \u0000 \u0000 \u0000 \u0000Findings \u0000 \u0000 \u0000 \u0000 \u0000Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus. \u0000 \u0000 \u0000 \u0000 \u0000Originality/value \u0000 \u0000 \u0000 \u0000 \u0000These refinements were not presented in prior literature and can be useful to financial analysts and investors.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73397938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study whether a particular aspect of language structure, the future-time reference (FTR) of a language, explains variation in corporate earnings management behaviors around the world. Based on the Sapir-Whorf hypothesis (Whorf 1956), we predict that grammatically referencing the future, which induces humans to perceive the future more sharply distinct from the present, induces myopic management behavior. In support of this idea, we find that firms headquartered in strong-FTR language countries are more likely to engage in accrual and real activities earnings management to meet short-term earning benchmarks.
{"title":"Language FTR and Earnings Management: International Evidence","authors":"Marco Fasan, G. Gotti, Tony Kang, Yi Liu","doi":"10.2139/ssrn.2763922","DOIUrl":"https://doi.org/10.2139/ssrn.2763922","url":null,"abstract":"We study whether a particular aspect of language structure, the future-time reference (FTR) of a language, explains variation in corporate earnings management behaviors around the world. Based on the Sapir-Whorf hypothesis (Whorf 1956), we predict that grammatically referencing the future, which induces humans to perceive the future more sharply distinct from the present, induces myopic management behavior. In support of this idea, we find that firms headquartered in strong-FTR language countries are more likely to engage in accrual and real activities earnings management to meet short-term earning benchmarks.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82590571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, massive foreign bank exits have begun to be observed around the world. What is the effect of such trend on the market power of the domestic banks and on competition between them? How do the MA however, in normal times, all banks participate in a horserace.
{"title":"A Horserace or Boost in Market Power? Banking Sector Competition after Foreign Bank Exits","authors":"Aneta Hryckiewicz, Lukasz Kozłowski","doi":"10.2139/ssrn.2707123","DOIUrl":"https://doi.org/10.2139/ssrn.2707123","url":null,"abstract":"Recently, massive foreign bank exits have begun to be observed around the world. What is the effect of such trend on the market power of the domestic banks and on competition between them? How do the MA however, in normal times, all banks participate in a horserace.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75046634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study evaluates the profitability of dynamic pairs trading strategies using a proposed 3-step pairs selection approach. We extend the pairs trading methodology employed by Miao (2014) to the broad-based exchange traded funds (ETFs) listed on the Australian Securities Exchange (ASX). The 3-step approach incorporates the correlation, cointegration and error correction coefficient as the pre-selection criteria during the formation period. In the subsequent trading period, we employ a daily re-calibration of the parameters using a 252-day rolling window from January 1, 2013 to September 30, 2015. We developed a real-time trading system using the Java programming language and KDB database, and back test the strategies using tick-by-tick historical quotes during the trading period. The back testing of the top five ETF pairs: ISO-SSO, IOZ-VAS, IOZ-STW, STW-VAS and STW-SFY yield cumulative returns of 10.08%, 4.41%, 19.70%, 62.27%, 46.60% and Sharpe ratios of 2.21, 1.00, 9.29, 15.12, 11.17 respectively. The maximum draw down is -32.47% over the trading period.
{"title":"Dynamic ETF Pairs Trading System. Evidence From Australia","authors":"N. Robert Enemuwe","doi":"10.2139/ssrn.2662258","DOIUrl":"https://doi.org/10.2139/ssrn.2662258","url":null,"abstract":"This study evaluates the profitability of dynamic pairs trading strategies using a proposed 3-step pairs selection approach. We extend the pairs trading methodology employed by Miao (2014) to the broad-based exchange traded funds (ETFs) listed on the Australian Securities Exchange (ASX). The 3-step approach incorporates the correlation, cointegration and error correction coefficient as the pre-selection criteria during the formation period. In the subsequent trading period, we employ a daily re-calibration of the parameters using a 252-day rolling window from January 1, 2013 to September 30, 2015. We developed a real-time trading system using the Java programming language and KDB database, and back test the strategies using tick-by-tick historical quotes during the trading period. The back testing of the top five ETF pairs: ISO-SSO, IOZ-VAS, IOZ-STW, STW-VAS and STW-SFY yield cumulative returns of 10.08%, 4.41%, 19.70%, 62.27%, 46.60% and Sharpe ratios of 2.21, 1.00, 9.29, 15.12, 11.17 respectively. The maximum draw down is -32.47% over the trading period.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82329381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper addresses one of the main challenges faced by insurance companies and risk management departments, namely, how to develop standardised framework for measuring risks of underlying portfolios and in particular, how to most reliably estimate loss severity distribution from historical data. This paper investigates tail conditional expectation (TCE) and tail variance premium (TVP) risk measures for the family of symmetric generalised hyperbolic (SGH) distributions. In contrast to a widely used Value-at-Risk (VaR) measure, TCE satisfies the requirement of the “coherent” risk measure taking into account the expected loss in the tail of the distribution while TVP incorporates variability in the tail, providing the most conservative estimator of risk. We examine various distributions from the class of SGH distributions, which turn out to fit well financial data returns and allow for explicit formulas for TCE and TVP risk measures. In parallel, we obtain asymptotic behaviour for TCE and TVP risk measures for large quantile levels. Furthermore, we extend our analysis to the multivariate framework, allowing multivariate distributions to model combinations of correlated risks, and demonstrate how TCE can be decomposed into individual components, representing contribution of individual risks to the aggregate portfolio risk.
{"title":"Estimating the Tails of Loss Severity via Conditional Risk Measures for the Family of Symmetric Generalised Hyperbolic Family","authors":"Katja Ignatieva, Z. Landsman","doi":"10.2139/ssrn.2577063","DOIUrl":"https://doi.org/10.2139/ssrn.2577063","url":null,"abstract":"This paper addresses one of the main challenges faced by insurance companies and risk management departments, namely, how to develop standardised framework for measuring risks of underlying portfolios and in particular, how to most reliably estimate loss severity distribution from historical data. This paper investigates tail conditional expectation (TCE) and tail variance premium (TVP) risk measures for the family of symmetric generalised hyperbolic (SGH) distributions. In contrast to a widely used Value-at-Risk (VaR) measure, TCE satisfies the requirement of the “coherent” risk measure taking into account the expected loss in the tail of the distribution while TVP incorporates variability in the tail, providing the most conservative estimator of risk. We examine various distributions from the class of SGH distributions, which turn out to fit well financial data returns and allow for explicit formulas for TCE and TVP risk measures. In parallel, we obtain asymptotic behaviour for TCE and TVP risk measures for large quantile levels. Furthermore, we extend our analysis to the multivariate framework, allowing multivariate distributions to model combinations of correlated risks, and demonstrate how TCE can be decomposed into individual components, representing contribution of individual risks to the aggregate portfolio risk.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75124381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article focuses on how to effectively cope with the open source software (OSS) adoption in the enterprise context. Based on the Linux in Munich case study and the identified technological risks of OSS we show challenges and risks for CIOs and propose recommendations to follow when evaluating and calculating risks of OSS adoption.
{"title":"Technological Risks of Open Source Software Adoption in the Organizational Context – Linux in Munich (LiMux) Case","authors":"M. Silic, A. Back","doi":"10.2139/ssrn.2633005","DOIUrl":"https://doi.org/10.2139/ssrn.2633005","url":null,"abstract":"This article focuses on how to effectively cope with the open source software (OSS) adoption in the enterprise context. Based on the Linux in Munich case study and the identified technological risks of OSS we show challenges and risks for CIOs and propose recommendations to follow when evaluating and calculating risks of OSS adoption.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84606816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A previously overlooked source of potential bias in the Consumer Price Index (CPI) is described. We find that unit value (average) prices, commonly used for construction of the CPI should be constructed over the same period as the index to be constructed, rather than over an incomplete sub-period. The latter approach can lead to an upward bias in the CPI.
{"title":"Weekly versus Monthly Unit Value Price Indexes","authors":"W. Diewert, Kevin J. Fox, J. Haan","doi":"10.2139/SSRN.2634256","DOIUrl":"https://doi.org/10.2139/SSRN.2634256","url":null,"abstract":"A previously overlooked source of potential bias in the Consumer Price Index (CPI) is described. We find that unit value (average) prices, commonly used for construction of the CPI should be constructed over the same period as the index to be constructed, rather than over an incomplete sub-period. The latter approach can lead to an upward bias in the CPI.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87674247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
At an exogenous deadline, Receiver must take an action, the payoff of which depends on Sender’s private binary type. Sender privately observes whether and when an opportunity to start a public flow of information about her type arrives. She then chooses when to seize this opportunity. Starting the information flow earlier exposes to greater scrutiny but signals credibility. We characterize the set of equilibria and show that Sender always delays the information flow and completely withholds it with strictly positive probability. Focusing on the stable equilibrium, we derive comparative statics, and discuss implications for organizations, politics, and financial markets.
{"title":"Timing Information Flows","authors":"Gabriele Gratton, Richard Holden, A. Kolotilin","doi":"10.2139/ssrn.2636122","DOIUrl":"https://doi.org/10.2139/ssrn.2636122","url":null,"abstract":"At an exogenous deadline, Receiver must take an action, the payoff of which depends on Sender’s private binary type. Sender privately observes whether and when an opportunity to start a public flow of information about her type arrives. She then chooses when to seize this opportunity. Starting the information flow earlier exposes to greater scrutiny but signals credibility. We characterize the set of equilibria and show that Sender always delays the information flow and completely withholds it with strictly positive probability. Focusing on the stable equilibrium, we derive comparative statics, and discuss implications for organizations, politics, and financial markets.","PeriodicalId":23435,"journal":{"name":"UNSW Business School Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80148940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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