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This paper examines the role of illiquidity and duration factor in understanding the momentum profit in the Korean stock market. We find that the foreigner/institutional illiquidity factor explains the momentum effect. In addition, this paper finds that duration factor defined as the difference in returns of short-duration and long-duration stocks captures well the momentum profits. That is, a two-factor model with the market and duration factor performs much better than competing asset pricing models in explaining the momentum effect. Finally, when controlling for the duration factor, the explanatory power of the foreign/institutional illiquidity factor on the momentum profits disappears. In sum, our empirical finding indicates that the duration factor is the most important ingredient in understanding the momentum effect in the Korean stock market.

The purpose of this research is to propose a framework for research on Macaulay duration and establish future research directions.

Thematic, bibliometric and content analyses have been used to review 168 research papers published between 1938 and 2019 taken from ISI Web of Science and Scopus contributed by leading authors, journals and regulatory bodies.

Identification and integration of themes of duration theory, duration model development and duration model implementation leading to unattended research gaps, and framework for research on Macaulay duration.

The study is based on an extensive review of the literature to extract important themes, research gaps and frameworks. It does not empirically investigate significance of Macaulay duration and various sectors.

This research has several aspects that are helpful for practitioners. Macaulay duration has been the subject of empirical research only without any guiding framework. This research provides a platform to initiate profound researches in various areas of finance. Various proposed models are required to be tested under holistic approach in conventional and emerging fields, especially in Islamic settings.

This research highlights, research themes leading to framework, research gaps and factors that are crucial in developing, extending and testing duration models leading to enhancement of theoretical base of Macaulay duration.

This study aims to develop a model which incorporates the impact of both aleatory and epistemic uncertainties into construction duration predictions, in a manner that is consistent with the nature/quality of information available about various factors which bring about uncertainties.

Data relating to 178 completed Tertiary Education Trust Fund (TETfund) building construction projects were obtained from construction firms via questionnaire survey. Using 90% of the data, the model was developed in the form of a hybrid-based algorithm implemented through a suitable user-friendly graphical user interface (GUI) using MATLAB programming language. Bayesian model averaging, Monte Carlo simulation and fuzzy logic were the statistical methods used for the algorithm development, prior to its GUI implementation in MATLAB. Using the remaining 10% data, the model's predictive accuracy was assessed via the independent samples t-test and the mean absolute percentage error (MAPE).

The developed model's predictions were found not statistically different from those of actual duration estimates in the 10% test data, with a MAPE of just 2%. This suggests that the model's ability to incorporate both aleatory and epistemic uncertainties improves accuracy of duration predictions made using it.

The model was developed using a particular type of building projects (TETfund building construction projects), and so its use is limited to projects with characteristics similar to those used for its development.

The developed model's predictions are expected to serve as a useful basis for consultancy firms and contractor organisations to make more realistic schedules and benchmark measures of construction period, thereby facilitating effective planning and successful execution of construction projects.

The study presented a model which permits combined manipulation of aleatory and epistemic uncertainties, hence ensuring a more realistic incorporation of uncertainty into construction duration predictions.

This study aims to develop a building renovation duration prediction model incorporating both scope and non-scope factors.

The study used a questionnaire to obtain basic information relating to identified project scope factors as well as information relating to the impact of the non-scope factors on the duration of building renovation projects. The study retrieved 121 completed questionnaires from construction firms on tertiary education trust fund (TETFund) building renovation projects. Artificial neural network was then used to develop the model using 90% of the data, while mean absolute percentage error was used to validate the model using the remaining 10% of the data.

Two artificial neural network models were developed – a multilayer perceptron (MLP) and a radial basis function (RBF) model. The accuracy of the models was 86% and 80%, respectively. The developed models’ predictions were not statistically different from those of actual duration estimates with less than 20% error margin. Also, the study found that MLP models are more accurate than RBF models.

The developed models are only applicable to projects that suit the characteristics and nature of the data used to develop the models. Hence, models can only predict the duration of building renovation projects.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it; it also helps clients to effectively benchmark projects duration and contractors to accurately estimate duration at tendering stage.

The study presents models that combine both scope and non-scope factors in predicting the duration of building renovation projects so as to ensure more realistic predictions.

The expanded sovereign bond portfolios from the sizeable public interventions in the financial sector during the current crisis need close monitoring and analysis of emerging vulnerabilities. This chapter presents some conventional and new measures of market, credit, and liquidity risks for government bond portfolios, considered from the perspective of a sovereign debt manager. In particular, it examines duration, convexity, and VaR statistics as measures of market exposure; the contingent-claims approach as the most promising measure of credit risk exposure; and a VaR statistic as a measure of liquidity risk.

The purpose of this paper is to demonstrate application of the Taguchi method‐based conceptual signal‐to‐noise (S/N) approach and Pareto analysis of variance (ANOVA) to determine optimum level of three important factors related to mobile phone conversation during driving, namely time of drive (day or night), distance between cars, and mobile phone call duration that minimizes drivers' reaction time (RT) in braking response.

Three levels of each factor based on the experience, are considered in the present study. The design of experiment, in the form of an L₁₈ orthogonal array, as proposed by Genichi Taguchi is used to conduct 18 experiments. A total of 27 young male subjects participated in the experimental study. The experimental task involved pressing the brake pedal of the car by the driver upon seeing another car in front while the driver is talking on a mobile phone. Drivers' performance, measured in terms of RT in braking response, is recorded. Conceptual S/N ratio and Pareto ANOVA are employed to investigate the drivers' performance.

Results show that within the test range, drivers' performance, i.e. RT in braking response is optimum (minimum) when they performed the driving task at day time, distance between cars is long (20 meters), and mobile phone call duration is short (30 seconds). Mobile call duration is found to be the dominant parameter with a percentage contribution ratio of 41.882 percent towards the laid down objective followed by time of driving, 32.003 percent and distance between cars, 1.353 percent.

This paper provides valuable information to the drivers with respect to the use of optimum level of these factors in order to minimize their RT in braking response.

To the best of the authors' knowledge, no study has been conducted in the past to investigate the effect of these factors on the performance of drivers when they use mobile phones for conversation during driving. In addition, no attempt has yet been made to find the optimal level of these factors from drivers' performance in braking response view point. This paper is an original research work of authors and in the opinion it carries significantly important values as it provides new information to the persons who talk on mobile phones during driving.

This article will select 25 years of subdivided data to perform Kaplan–Meier survival analysis on the export trade relations of Chinese wooden flooring, use discrete-time cloglog models to analyze influencing factors, use logit and probit models to test the robustness, and try to systematically reveal the duration of China's wood flooring export trade and its influencing factors.

This study used Kaplan–Meier survival function estimation method. In the survival analysis, survival function and hazard rate function are often used to characterize the distribution of survival time.

The continuous average export time of China's wooden flooring is relatively long, about 14 years. China's wooden flooring has a negative time dependency. After the export trade exceeds the threshold value of 15 years, the failure rate of trade greatly decreases, which has a “threshold effect.” Gravity model variables have a significant impact on the duration of China's wooden floor export.

Studying the duration of forest products trade is of great significance for clearing deep-level trade relations and promoting sustainable development of forest products trade.

Determining the duration for road construction projects represents a problem for construction professionals in Ghana. The purpose of this paper is to develop an artificial neural network (ANN) model for determining the duration for rural bituminous surfaced road projects.

Data for 22 completed bituminous surfaced road projects from the Department of Feeder Roads (rural road agency) were collected and analyzed using the principal component analysis (PCA) and ANN techniques. The data collected were final payment certificates which contained payment bill of quantities (BOQ) of work items executed for the selected completed road projects. The executed quantities in the BOQ were the total quantities of work items for site clearance, earthworks, in-situ concrete, reinforcement, formwork, gravel sub-base/base, bitumen, road line markings and furniture, length of road and actual durations for each of the completed projects. The PCA was first employed to reduce the data in order to identify a smaller number of variables (or significant quantities) that constitute 81.58 percent of the total variance of the collected data. The ANN was then used to develop the network using the identified significant quantities as input variables and the actual durations as output variables.

The coefficient of correlation (R) and determination (R²) as well as the mean absolute percentage error (MAPE) obtained show that construction professionals can use the developed ANN model for determining duration. The study shows that the best neural network is the multi-layer perceptron with a structure 3-38-1 based on a back propagation feed forward algorithm. The developed network produces good results with an MAPE of 17.56 percent or an average accuracy of 82.44 percent.

Apart from the fact that the sample size was small, the developed model does not incorporate the implications of other likely factors that may affect contract duration.

The outcome of this study is to help construction professionals to fix realistic contract duration for road construction projects before signing a contract. Such realistic contract duration would help reduce time overruns as well as the payment of liquidated and ascertained damages by contractors for late completion.

This paper proposes an alternative way of determining the duration for road construction projects using the total quantities of work items in a final payment BOQ. The approach is based on the PCA and ANN model of quantities of work items of completed road projects.

The first paper of this two‐paper series has developed an understanding of neurofuzzy concept modelling techniques. This second paper demonstrates the power and versatility of neurofuzzy methods when applied to the determination of construction project duration. The paper explains data selection and preprocessing, the modelling process and optimization of developed models. The paper also presents and discusses the results generated by the developed model.

The purpose of this study is to develop, test and examine econometric methodology for Sharīʿah-compliant duration models of Islamic banks.

The research evaluates all existing duration models from Sharīʿah’s perspective and develops a four-stage framework for testing Sharīʿah-compliant duration models. The econometric methodology consists of multiple regression, Johansen co-integration, error correction model, vector error correction model (VECM) and threshold vector error models (TVECM).

Regressions analysis suggests that returns on earning assets and interbank offered rates are significant factors for calculating the duration of earning assets, whereas returns paid on return bearing liabilities and average interbank rates of deposits are significant factors for duration of return bearing liabilities. VECM suggests that short run duration converges into long run duration and TVECM suggests that management of assets and liabilities also plays a significant role that can bring about a change of about 15% in respective durations.

Sharīʿah-compliant duration models will improve risk and Sharīʿah efficiency, which will ultimately improve market capitalization and returns stability of Islamic banks in the long run.

Sharīʿah-compliant duration models testing provides insight into how various factors, namely, rates of return, benchmark rates and managerial skills of Islamic bank risk managers impact durations of assets and liabilities. It also explains the future course of action for Sharīʿah-compliant duration model testing.