scholarly journals The relationship between the Nasdaq Composite Index and energy futures markets

2018 ◽  
Vol 15 (4) ◽  
pp. 1-16
Author(s):  
Ikhlaas Gurrib

This paper sheds light on the relationship between the Nasdaq Composite Index and a newly proposed Energy Futures Conditions Index (EFCI). While various financial conditions indices provide information about the financial stability of a country, the existence of an energy condition index, using futures markets, is scarce. Using weekly data over the period 1992–2017, this paper introduces an energy futures index using principal component analysis and test its predictability over the Nasdaq Composite Index. The EFCI captures 95% of the variability inherent in crude oil, heating oil and natural gas futures’ total reportable positions. Stability in forecast errors over different lags suggests a one week lag is sufficient to forecast weekly Nasdaq Composite Index. 95% prediction levels support that the estimated model captures actual equity market index values, except for the 2000 technology bubble. Distributions of level data were non-normal, not serially correlated and homoscedastic under the whole sample period, with diagnostics on pre and post technology bubble crisis showing mixed results. While differencing ensured homoscedastic errors in the forecasting model, Granger causality supported non-causality from both energy futures and equity markets, suggesting no evidence of cross market information flows.

2021 ◽  
pp. 001946622110635
Author(s):  
Prabir Kumar Ghosh ◽  
Soumyananda Dinda

This study empirically re-examines the relationship between transport infrastructure and economic growth in India for the period 1990–2017. Multivariate dynamic models are applied to estimate the relationship between economic growth and different modes of transport infrastructure namely road, rail and air transports in the vector error correction model framework. The results reveal that road and air transports have significant positive contribution to economic growth in the long-run while rail transport is insignificant. This study further examines the said issue using unit free index variables and has constructed a composite index of transport infrastructure using principal component analysis to analyse the nexus between aggregate transport infrastructure and economic growth in India in the post globalisation era. The results of the study indicate the bidirectional causality between aggregate transport infrastructure and economic growth. Results of this study suggest incorporating feedback issue in policy formulations. JEL Codes: C22, O18, R4


Author(s):  
Adriana Anamaria Davidescu

Abstract The main objective of the paper was to construct a synthetic measure that can be used as benchmark for measuring the progress toward convergence to the social market economy as specification of the Lisbon Treaty. This kind of approach will enable us to identify the main determinants of the social market economy among EU member states using a principal component analysis technique (PCA) analyzing comparatively different group of countries. The analysis was conducted at the level of the 28 EU countries for the year 2013 using 15 indicators from four categories: efficient market allocation, efficient property rights, economic and ecological sustainability and social inclusion. The empirical results revealed that the key determinants in explaining the social market economy at European level are freedom of contract, open markets, financial stability and effective environmental protection and highlighted Sweden, Finland, Denmark, Estonia and Germany as the main poles of social market economy at European level while at the opposite side Romania, Hungary and Bulgaria registered the smallest level of social market economy. As main contribution brought by the paper there can be mentioned the attempt of measuring the level of social market economy at European level using an aggregate composite index for the level of 2013 highlighting the main poles of social economy.


2003 ◽  
Vol 8 (2) ◽  
pp. 97-100 ◽  
Author(s):  
Maria José Sotelo ◽  
Luis Gimeno

The authors explore an alternative way of analyzing the relationship between human development and individualism. The method is based on the first principal component of Hofstede's individualism index in the Human Development Index rating domain. Results suggest that the general idea that greater wealth brings more individualism is only true for countries with high levels of development, while for middle or low levels of development the inverse is true.


2020 ◽  
Vol 13 (2) ◽  
pp. 112-121
Author(s):  
Sudiyar . ◽  
Okto Supratman ◽  
Indra Ambalika Syari

The destructive fishing feared will give a negative impact on the survival of this organism. This study aims to analyze the density of bivalves, distribution patterns, and to analyze the relationship of bivalves with environmental parameters in Tanjung Pura village. This research was conducted in March 2019. The systematic random system method was used for collecting data of bivalves. The collecting Data retrieval divided into five research stasions. The results obtained 6 types of bivalves from 3 families and the total is 115 individuals. The highest bivalve density is 4.56 ind / m², and the lowest bivalves are located at station 2,1.56 ind / m²,  The pattern of bivalve distribution in the Coastal of Tanjung Pura Village is grouping. The results of principal component analysis (PCA) showed that Anadara granosa species was positively correlated with TSS r = 0.890, Dosinia contusa, Anomalocardia squamosa, Mererix meretrix, Placamen isabellina, and Tellinella spengleri were positively correlated with currents r = 0.933.


2021 ◽  
Vol 11 (3) ◽  
pp. 359
Author(s):  
Katharina Hogrefe ◽  
Georg Goldenberg ◽  
Ralf Glindemann ◽  
Madleen Klonowski ◽  
Wolfram Ziegler

Assessment of semantic processing capacities often relies on verbal tasks which are, however, sensitive to impairments at several language processing levels. Especially for persons with aphasia there is a strong need for a tool that measures semantic processing skills independent of verbal abilities. Furthermore, in order to assess a patient’s potential for using alternative means of communication in cases of severe aphasia, semantic processing should be assessed in different nonverbal conditions. The Nonverbal Semantics Test (NVST) is a tool that captures semantic processing capacities through three tasks—Semantic Sorting, Drawing, and Pantomime. The main aim of the current study was to investigate the relationship between the NVST and measures of standard neurolinguistic assessment. Fifty-one persons with aphasia caused by left hemisphere brain damage were administered the NVST as well as the Aachen Aphasia Test (AAT). A principal component analysis (PCA) was conducted across all AAT and NVST subtests. The analysis resulted in a two-factor model that captured 69% of the variance of the original data, with all linguistic tasks loading high on one factor and the NVST subtests loading high on the other. These findings suggest that nonverbal tasks assessing semantic processing capacities should be administered alongside standard neurolinguistic aphasia tests.


2021 ◽  
Vol 11 (7) ◽  
pp. 3208
Author(s):  
Andrea De Montis ◽  
Vittorio Serra ◽  
Giovanna Calia ◽  
Daniele Trogu ◽  
Antonio Ledda

Composite indicators (CIs), i.e., combinations of many indicators in a unique synthetizing measure, are useful for disentangling multisector phenomena. Prominent questions concern indicators’ weighting, which implies time-consuming activities and should be properly justified. Landscape fragmentation (LF), the subdivision of habitats in smaller and more isolated patches, has been studied through the composite index of landscape fragmentation (CILF). It was originally proposed by us as an unweighted combination of three LF indicators for the study of the phenomenon in Sardinia, Italy. In this paper, we aim at presenting a weighted release of the CILF and at developing the Hamletian question of whether weighting is worthwhile or not. We focus on the sensitivity of the composite to different algorithms combining three weighting patterns (equalization, extraction by principal component analysis, and expert judgment) and three indicators aggregation rules (weighted average mean, weighted geometric mean, and weighted generalized geometric mean). The exercise provides the reader with meaningful results. Higher sensitivity values signal that the effort of weighting leads to more informative composites. Otherwise, high robustness does not mean that weighting was not worthwhile. Weighting per se can be beneficial for more acceptable and viable decisional processes.


Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Yulia Ivanova ◽  
Anton Kovalev ◽  
Vlad Soukhovolsky

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year.


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