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IJAREM: Current Issue (Volume 10 - No. 02, 2024)

 

1. Performance of Rural Public Transport on the Gadang-Karangkates Route in Malang District
Dwi Ratnaningsih, Wahiddin Wahiddin, Lailatun Nashiroh
Abstract
Public transport is the most frequently used mode of transportation, both as a means of transporting passengers and goods. The Gadang - Karangkates public transport route is one of the public transport routes in Malang Regency. The route is a connecting route to the market, school, which every day there is density at certain points which causes less efficient travel time to the destination. Rural transport is currently slowly starting to be abandoned, due to the inefficient time taken for each trip and the long waiting time for passengers.
This performance analysis requires two data, namely primary data and secondary data. Primary data includes the number of angkot operating per day and the number of passengers per day. Secondary data includes data on the number of public transport and the route map of the Malang Regency passenger public transport route Gadang - Karangkates. Indicators for performance include load factor, speed, frequency, headway.
Based on the results of the evaluation of the performance of public transport on the Gadang - Karangkates route, the average value of the load factor (Load Factor) is 51%, the average time between (Headway) is 33 minutes, speed 25 km / hour.

 

2. Identification of Emerging Technologies in the Metaverse and Prospective Research on the Development of Emerging Industries
Jing Lei, Jiq-Qing Song, Wei Zhang
Abstract
This project will focus on the development frontier of the new round of scientific and technological revolution, and conduct in-depth research on the emerging technologies of the Metaverse and their profound impact on the development of emerging industries and technological changes in the Metaverse. Firstly, based on the theories and methods of scientometrics and patent metrology, this paper proposes the concepts and characteristics of emerging technologies in the Metaverse from the perspectives of emerging technology management and technology system evolution with the help of information visualization technology, establishes a visualization method for the identification of emerging technologies in the Metaverse, and explores the evolution mechanism of emerging technologies in the Metaverse. Then, combined with the actual situation of our province, systematic research will be carried out around the Metaverse-related scientific and technological fields such as blockchain, cloud computing, artificial intelligence, Internet of Things, extended reality, digital twins, etc., identify the emerging technologies of the Metaverse, construct the evolution path from its technical system to industrial development, and use the methods of scientific measurement and patent measurement, combined with expert consultation, etc., to improve and perfect the research conclusions. This project will draw on advanced experience at home and abroad, put forward the overall idea and development focus of the forward-looking layout of emerging industries in the field of the Metaverse, conduct prediction and analysis of emerging technologies in the Metaverse, and put forward countermeasures and suggestions, so as to provide support for the formulation of subsequent relevant policies. The research results of this project will help enrich and develop the theories and methods of emerging technologies related to the Metaverse, expand the theories, methods and applications of scientometrics, patent metrology, information visualization, etc., and provide decision-making support for the development of emerging industries related to the Metaverse.

 

3. Modeling the Dual Long Memory in the Moroccan Stock Market: ARFIMA-FIGARCH Approach
Eljoumani Najat
Abstract
The purpose of this paper is to test the weak form of the informational efficiency hypothesis on the Moroccan stock market during the period from 03/01/2002 to 15/08/2023, by examining the presence of dual long memory in both returns and volatility of the Casablanca Stock Exchange index (MASI). We initiated our study by testing the random walk hypothesis using various standard statistical tests, such as the normality test, stationarity tests, return autocorrelation tests, and the variance ratio test. The results of these tests strongly rejected the random walk hypothesis for the Moroccan stock market over the examined period, thus concluding that the Casablanca Stock Exchange is not an efficient market in its weak form.
Subsequently, we tested the presence of dual long memory in both the conditional mean and conditional variance of the geometric returns of the MASI index by applying four joint models: ARFIMA-FIGARCH, ARFIMA-FIEGARCH, ARFIMA-FIAPARCH, and ARFIMA-HYGARCH. Various combinations of the parameters for these four models were tested, and we selected the models with the most significant estimations. Empirical results from all these models indicated that both long memory parameters are statistically significant at the 1% or 5% significance level, and most of the other parameters are statistically significant, except occasionally 1 or 2 parameters. These findings robustly confirm that the Moroccan stock market is inefficient in its weak form.

 

4. Modeling the Non-Linearity of the Moroccan Stock Market: Application of the Smooth Transition Autoregressive (STAR) Model
Eljoumani Najat
Abstract
Objective: The aim of this paper is to test the weak form of informational efficiency of the Moroccan stock market using a non-linear approach.
Methodology: For this purpose, we used the daily closing prices of the MASI index from the Casablanca Stock Exchange, covering the period from 03/01/2002 to 08/15/2023, totaling 5393 observations. We applied the Smooth Transition Autoregressive (STAR) model to the series of geometric returns of the MASI index to capture the non-linear property.
Results: Following a four-step specification procedure, our choice favored the Logistic Smooth Transition Autoregressive (LSTAR) model over the Exponential Smooth Transition Autoregressive (ESTAR) model. We estimated the LSTAR model and found that the parameters of the base and alternative parts of both linear and non-linear regimes, the transition parameter, and the transition threshold are all statistically significant at the 1% significance level. It is noteworthy that the estimated LSTAR model's transition parameter value suggests a relatively slow transition from one regime to another.
Conclusion: The conclusions derived from the estimation of the LSTAR model indicate the presence of non-linearity in the series of geometric returns of the MASI index. Thus, it can be concluded that the Moroccan stock market exhibits inefficiency according to the weak form.

 

 

 

 

 

 


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