Out-of-sample earnings forecasting for OLS and Theil–Sen models relative to a na.ı.ve no-change model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rick Neil Francis
Keyword(s):  
Ordinary Least Squares ◽  
Complex Model ◽  
Earnings Forecast ◽  
Change Model ◽  
Elementary Model ◽  
Content Type ◽  
Out Of Sample ◽  
Simple Question ◽  
Earnings Forecasting ◽  
Better Than

PurposeThe purpose of this paper is to enlarge the exposure of the Theil–Sen (TS) methodology to the academic, analyst and practitioner communities using an earnings forecast setting. The study includes an appendix that describes the TS model in very basic terms and SAS code to assist readers in the implementation of the TS model. The study also presents an alternative approach to deflating or scaling variables.Design/methodology/approachArchival in nature using a combination of regression analysis and binomial tests.FindingsThe binomial test results support the hypothesis that the forecasting performance of the naïve no-change model is at least equal to or better than the ordinary least squares (OLS) model when earnings volatility is low. However, the results do not support the same hypothesis for the TS model nor do the results support the hypothesis that the OLS and TS models will outperform the naïve no-change model when cash flow volatility is high. Nevertheless, the study makes notable contributions to the literature, as the results indicate that the performance of the naïve model is at least as good as the OLS and TS models across 18 of the 20 binomial tests. Moreover, the results indicate that the performance of the TS model is always superior to the OLS model.Research limitations/implicationsThe results are generalizable to US firms and may not extend to non-US firms.Practical implicationsThe TS methodology is advantageous to OLS in that the results are robust to outlier observations, and there is no heteroscedasticity. Researchers will find this study to be useful given the use of a model (i.e. TS) which has to date received little attention, and the provision of the details for the mechanics of the model. A bonus for researchers is that the study includes SAS code for implementing the procedure.Social implicationsAwareness of alternative forecast methodologies could lead to improved forecasting results in certain contexts. The study also helps the financial community in general, as improved forecasting abilities are important for all capital market participants as they improve market efficiency.Originality/valueAlthough a healthy literature exists for examining out-of-sample forecasts for earnings, the literature lacks an answer for a simple question before pursuing additional analyses: Are the results any better than those from a naive no-change forecast? The current study emphasizes the idea that the naïve no-change forecast is the most elementary model possible, and the researcher must first establish the superiority of a more complex model before conducting further analyses.

scholarly journals Voluntary intellectual capital disclosure and earnings forecast in Indonesia–Malaysia–Thailand growth triangle's pharmaceuticals sector

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saarce Elsye Hatane ◽  
Jefferson Clarenzo Diandra ◽  
Josua Tarigan ◽  
Ferry Jie
Keyword(s):  
Pharmaceutical Industry ◽  
Intellectual Capital ◽  
Strategic Alliances ◽  
Stock Exchange ◽  
Financial Analysts ◽  
Earnings Forecast ◽  
Relational Capital ◽  
Content Type ◽  
Earnings Forecasting

PurposeThis study examines the role of intellectual capital disclosure (ICD) on earnings forecasting by analysts in the pharmaceutical industry in emerging countries, particularly in Indonesia, Malaysia and Thailand. This study specifically examines the role of each component of the ICD on analysts' forecasts, which consists of errors of forecasted earnings, the standard deviation of forecasted earnings and analyst recommendations.Design/methodology/approachPanel data analysis is conducted using a sample of 17 companies from pharmaceuticals industries in Indonesia, Malaysia, Thailand – Growth Triangle (IMT-GT), which are listed in the Indonesia Stock Exchange (IDX), Malaysia Stock Exchange (MYX) and Stock Exchange of Thailand (SET) from 2010 to 2017. Secondary data is obtained from Bloomberg and Annual report, where they are being analyzed to measure the ICD and gather the control variables.FindingsThe results indicate that the three components of ICD, namely human capital disclosure (HCD), structural capital disclosure (SCD) and relational capital disclosure (RCD), insignificantly influence average analysts' consensus recommendation and analysts' earnings forecast dispersion. However, the findings show a significant negative influence of relational capital disclosure (RCD) on analysts' earnings forecast error. In contrast, HCD and SCD have an insignificant impact.Practical implicationsTransparency in disclosing activities related to external parties is essential for the pharmaceutical industry. It is found that relational capital disclosure is the only ICD indicator that can strengthen analysts' profit predictions. Transparency about company activities in maintaining customer satisfaction and activities related to strategic alliances with other organizations are two critical things that can accommodate the accuracy of earnings forecasting from analysts in pharmaceutical companies.Originality/valueThis study contributes to ICD-related research by discussing the financial analyst's response to this voluntary disclosure in the pharmaceutical industry, particularly in Indonesia, Malaysia and Thailand. The selected observation period is seven years, starting one year after the global financial crisis. The results showed that the disclosure of IC is not an exciting thing for financial analysts. In forecasting current earnings, financial analysts are more interested in errors than the previous year's estimates.

An examination of the effects of omni-channel service offerings on retailer performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Angela L. Jones ◽  
Jason W. Miller ◽  
Stanley E. Griffis ◽  
Judith M. Whipple ◽  
Clay M. Voorhees
Keyword(s):  
Ordinary Least Squares ◽  
Sales Growth ◽  
Least Squares Regression ◽  
Order Fulfillment ◽  
Content Type ◽  
Performance Effects ◽  
Brick And Mortar ◽  
Returns Management ◽  
Channel Service ◽  
Better Than

PurposeBoth online and brick and mortar retailers have invested heavily in developing omni-channel service offerings. Though seen as a competitive necessity, these omni-channel service offerings increase costs and complexities. The purpose of this study is to examine the effects of strategies involving bundles of omni-channel services related to order fulfillment and returns management on retailer performance.Design/methodology/approachArchival data were obtained for 152 retailers and analyzed using ordinary least squares regression. Robustness tests using an alternative dependent variable and a model-based classification strategy corroborate our findings.FindingsRetailers offering full sets of high integration omni-channel services (buy online pick up in store, ship from store and in-store returns) have better performance (e.g. sales, growth and competitive position) and web sales than retailers that offer only a partial mix of these high integration services. Retailers offering a partial bundle of high integration services, in turn, have better performance and web sales than retailers that offer none of these services.Originality/valueThe research extends work that has examined the performance effects of omni-channel services on individual retailers. Our results indicate retailers benefit the most when offering a full set of high integration omni-channel services, suggesting retailers who have only adopted a subset of these services could improve performance through broader adoption of services. The results further indicate partial adoption of high integration services is better than no adoption.

A Comparative Analysis of Hedging Effectiveness of Won/Dollar Futures and NDF Contracts

2004 ◽  
Vol 12 (2) ◽  
pp. 73-99
Author(s):  
Won Cheol Yun ◽  
Hyun Jin An
Keyword(s):  
Exchange Rates ◽  
Ordinary Least Squares ◽  
Correction Model ◽  
Futures Contract ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Sample Data ◽  
Out Of Sample ◽  
Spot Exchange Rate ◽  
Better Than

This study compares the hedging effectiveness of domestic won/dollar futures and foreign non-deferable forward (NDF) contracts. We use an ex ante analysis based on out-of-sample data. In addition, the analysis is based on the inventory hedging scenario, adopted in most of previous studies. We estimated hedge ratios by using the various method of 1 : 1 hedging, ordinary least squares (OLS), and error correction model (ECM). The hedging period is expanded to include one to twelve months‘ In every aspect, the hedging effectiveness of won/dollar futures contract turns out to be better than that of NDF contract. However, the differences are not statistically significant at 10% level. This res비t stems from the fact that there exists a high correlation between spot exchange rate and futures or forward exchange rates, implying an evidence of co-movement between them.

Breaking the code: barriers affecting inclusive thinking-HETL Scotland 2017

2018 ◽  
Vol 10 (2) ◽  
pp. 118-129
Author(s):  
Linda Carol Algozzini ◽  
Valencia Lavon Gabay ◽  
Shannon D. Voyles ◽  
Kimberly Bessolo ◽  
Grady Batchelor
Keyword(s):  
Higher Education ◽  
First Century ◽  
Individual Student ◽  
Change Model ◽  
Participatory Action ◽  
Content Type ◽  
Self Regulated Learning ◽  
Group Coaching ◽  
Regulated Learning

Purpose This case study reviews a group coaching and mentoring (GCM) change model and its significance in dissolving barriers and promoting equity in virtual learning environments. The purpose of this paper is to examine the model’s approach to shifting instructor mindsets to align with institutional core values and initiatives that best serve a twenty-first century adult learner. Design/methodology/approach The change model, grounded in GCM, metacognition, self-regulated learning, and community of practice theory, incorporates participatory action research design focusing on cycles of action, reflection, and evaluation. Findings This study illustrates the change model’s success in moving educators toward deeper understanding of self and individual student differences. It further showcases how professionals adapt and improve practices using self-regulated learning and metacognition to better serve the population they teach. Practical implications The GCM framework improved engagement. The design, while implemented in a higher education arena, is applicable to other entities seeking to bridge gaps using metacognition and self-regulated learning to become adaptable and inclusive. Originality/value The change model, recipient of one of this year’s Effective Practice Awards from the Online Learning Consortium (2017), is recognized for innovation and replicability in and beyond higher education.

Nature-inspired hybrid deep learning for race detection by face shape features

2020 ◽  
Vol 13 (3) ◽  
pp. 365-388
Author(s):  
Asha Sukumaran ◽  
Thomas Brindha
Keyword(s):  
Feature Extraction ◽  
Hybrid Algorithm ◽  
Shape Features ◽  
Error Performance ◽  
Color Feature ◽  
Content Type ◽  
Dragonfly Algorithm ◽  
Face Shape ◽  
Race Detection ◽  
Better Than

PurposeThe humans are gifted with the potential of recognizing others by their uniqueness, in addition with more other demographic characteristics such as ethnicity (or race), gender and age, respectively. Over the decades, a vast count of researchers had undergone in the field of psychological, biological and cognitive sciences to explore how the human brain characterizes, perceives and memorizes faces. Moreover, certain computational advancements have been developed to accomplish several insights into this issue.Design/methodology/approachThis paper intends to propose a new race detection model using face shape features. The proposed model includes two key phases, namely. (a) feature extraction (b) detection. The feature extraction is the initial stage, where the face color and shape based features get mined. Specifically, maximally stable extremal regions (MSER) and speeded-up robust transform (SURF) are extracted under shape features and dense color feature are extracted as color feature. Since, the extracted features are huge in dimensions; they are alleviated under principle component analysis (PCA) approach, which is the strongest model for solving “curse of dimensionality”. Then, the dimensional reduced features are subjected to deep belief neural network (DBN), where the race gets detected. Further, to make the proposed framework more effective with respect to prediction, the weight of DBN is fine tuned with a new hybrid algorithm referred as lion mutated and updated dragon algorithm (LMUDA), which is the conceptual hybridization of lion algorithm (LA) and dragonfly algorithm (DA).FindingsThe performance of proposed work is compared over other state-of-the-art models in terms of accuracy and error performance. Moreover, LMUDA attains high accuracy at 100th iteration with 90% of training, which is 11.1, 8.8, 5.5 and 3.3% better than the performance when learning percentage (LP) = 50%, 60%, 70%, and 80%, respectively. More particularly, the performance of proposed DBN + LMUDA is 22.2, 12.5 and 33.3% better than the traditional classifiers DCNN, DBN and LDA, respectively.Originality/valueThis paper achieves the objective detecting the human races from the faces. Particularly, MSER feature and SURF features are extracted under shape features and dense color feature are extracted as color feature. As a novelty, to make the race detection more accurate, the weight of DBN is fine tuned with a new hybrid algorithm referred as LMUDA, which is the conceptual hybridization of LA and DA, respectively.

Racial dissimilarity and diversity climate effect organizational identification

2016 ◽  
Vol 35 (5/6) ◽  
pp. 314-327 ◽  
Author(s):  
Brooklyn Cole ◽  
Raymond J. Jones ◽  
Lisa M. Russell
Keyword(s):  
Organizational Identification ◽  
Turnover Intentions ◽  
Ordinary Least Squares ◽  
Important Variable ◽  
Hierarchical Regression ◽  
Diversity Climate ◽  
Climate Effect ◽  
Content Type ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to empirically examine the relationship between psychological diversity climate (PDC) and organizational identification (OID) when influenced by racial dissimilarity between the subordinate and supervisor. Design/methodology/approach Ordinary least squares hierarchical regression analysis was run for hypotheses testing. Findings Three of the four hypothesized relationships were supported. Support was found for the direct relationship between PDC and OID. The moderator race was significant thus also supported. The moderator of dissimilarity was not supported. Finally the three-way interaction with race and dissimilarity was supported. Practical implications OID is an important variable for overall organizational success. OID influences a wealth of organizationally relevant outcomes including turnover intentions. Considering higher turnover exists for minority employees, understanding how diversity climate perceptions vary by employee race and therefore impact OID differently, helps managers when making decisions about various initiatives. Originality/value This study is the first the authors know of to investigate the impact of dissimilarity on the PDC-OID relationship.

The impact of executives’ perceptions of environmental threats and organizational slack on innovation strategies

2016 ◽  
Vol 7 (2) ◽  
pp. 216-230 ◽  
Author(s):  
Chengyuan Wang ◽  
Biao Luo ◽  
Yong Liu ◽  
Zhengyun Wei
Keyword(s):  
Cognitive Theory ◽  
Environmental Changes ◽  
Ordinary Least Squares ◽  
Organizational Slack ◽  
Least Squares Regression ◽  
Content Type ◽  
Environmental Threats ◽  
Innovation Strategies ◽  
The Impact ◽  
The Relationship

Purpose The paper aims to study the relationship between executives’ perceptions of environmental threats and innovation strategies and investigate the moderating effect of contextual factor (i.e. organizational slack) on such relations. It proposes a dualistic relationship between executives’ perceptions of environmental threats and innovation strategies, in which different perceptions of environmental threats will lead to corresponding innovation strategies, and dyadic organizational slack can promote such processes. Design/methodology/approach The paper is based on a survey with 163 valid questionnaires, which were all completed by executives. Hierarchical ordinary least-squares regression analysis is used to test the hypotheses proposed in this paper. Findings The paper provides empirical insights about that executives tend to choose exploratory innovation when they perceive environmental changes as likely loss threats, yet adopt exploitative innovation when perceiving control-reducing threats. Furthermore, unabsorbed slack (e.g. financial redundancy) positively moderates both relationships, while absorbed slack (e.g. operational redundancy) merely positively influences the relationship between the perception of control-reducing threats and exploitative innovation. Originality/value The paper bridges the gap between organizational innovation and cognitive theory by proposing a dualistic relationship between executives’ perceptions of environmental threats and innovation strategies. The paper further enriches innovation studies by jointly considering both subjective and objective influence factors of innovation and argues that organizational slack can moderate such dualistic relationship.

On portfolio optimization

2016 ◽  
Vol 17 (3) ◽  
pp. 295-309 ◽  
Author(s):  
Theo Berger ◽  
Christian Fieberg
Keyword(s):  
Minimum Variance ◽  
Factor Models ◽  
Scale Factor ◽  
Covariance Matrices ◽  
Portfolio Performance ◽  
Content Type ◽  
Portfolio Decisions ◽  
Multi Scale ◽  
Out Of Sample ◽  
Factor Returns

Purpose The purpose of this paper is to show how investors can incorporate the multi-scale nature of asset and factor returns into their portfolio decisions and to evaluate the out-of-sample performance of such strategies. Design/methodology/approach The authors decompose daily return series of common risk factors and of all stocks listed in the Dow Jones Industrial Index (DJI) from 2000 to 2015 into different time scales to separate short-term noise from long-run trends. Then, the authors apply various (multi-scale) factor models to determine variance-covariance matrices which are used for minimum variance portfolio selection. Finally, the portfolios are evaluated by their out-of-sample performance. Findings The authors find that portfolios which are constructed on variance-covariance matrices stemming from multi-scale factor models outperform portfolio allocations which do not take the multi-scale nature of asset and factor returns into account. Practical implications The results of this paper provide evidence that accounting for the multi-scale nature of return distributions in portfolio decisions might be a promising approach from a portfolio performance perspective. Originality/value The authors demonstrate how investors can incorporate the multi-scale nature of returns into their portfolio decisions by applying wavelet filter techniques.

Estimating defaults in organized security lending markets

2016 ◽  
Vol 24 (3) ◽  
pp. 343-362
Author(s):  
Latif Cem Osken ◽  
Ceylan Onay ◽  
Gözde Unal
Keyword(s):  
Credit Risk ◽  
Stock Returns ◽  
Stock Price ◽  
Price Volatility ◽  
Equity Market ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Content Type ◽  
Central Counterparties ◽  
Risk Determinants

Purpose This paper aims to analyze the dynamics of the security lending process and lending markets to identify the market-wide variables reflecting the characteristics of the stock borrowed and to measure the credit risk arising from lending contracts. Design/methodology/approach Using the data provided by Istanbul Settlement and Custody Bank on the equity lending contracts of Securities Lending and Borrowing Market between 2010 and 2012 and the data provided by Borsa Istanbul on Equity Market transactions for the same timeframe, this paper analyzes whether stock price volatility, stock returns, return per unit amount of risk and relative liquidity of lending market and equity market affect the defaults of lending contracts by using both linear regression and ordinary least squares regression for robustness and proxying the concepts of relative liquidity, volatility and return constructs by more than variable to correlate findings. Findings The results illustrate a statistically significant relationship between volatility and the default state of the lending contracts but fail to establish a connection between default states and stock returns or relative liquidity of markets. Research limitations/implications With the increasing pressure for clearing security lending contracts in central counterparties, it is imperative for both central counterparties and regulators to be able to precisely measure the risk exposure due to security lending transactions. The results gained from a limited set of lending transactions merit further studies to identify non-borrower and non-systemic credit risk determinants. Originality/value This is the first study to analyze the non-borrower and non-systemic credit risk determinants in security lending markets.

Current CITE-ings from the popular and trade computing press: telework and telecommuting

2016 ◽  
Vol 33 (1) ◽  
pp. 21-22 ◽  
Author(s):  
Martin Kesselman
Keyword(s):  
Literature Review ◽  
Design Methodology ◽  
Virtual Reference ◽  
Content Type ◽  
Advantages And Disadvantages ◽  
Better Than

Purpose – This article examines Current CITE-ings from the Popular and Trade Computing Press, Telework and Telecommuting Design/methodology/approach – The methodology adopted is a literature review. Findings – Readily available technologies now allow librarians to perform most of their work-offsite. Some traditional building-based services such as reference, have been taken over by virtual reference and now even instruction offers options on par with or even better than classroombased questions such as a webinar that can be viewed and reviewed at any time or by having librarians embedded into various courseware packages. Researchlimitations/implications – Librarians no longer need be limited to a single library; groups of subject librarians can work together in the cloud to provide services to multiple universities. Originality/value – This article collates some articles from the non-library literature that mayprovide some ideas and review advantages and disadvantages for both the library and employee

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