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This study aims to highlight potential savings in advertising budgets.

This study uses modern computer-based tools including stochastic dominance to check if advertising expenses are increasing sales by using modern causality assessment tools which allow for nonlinearities and use sophisticated assessment of causal impact of ads on sales.

This study identifies specific media spots where ad budget savings are possible. The marketing managers can take the next step to make small-scale local experiments to reassess this study’s findings.

This study is a statistical observational assessment not based on controlled experiments.

The authors have tools to identify ineffective advertising which can produce huge savings for the organization. The over-the-counter cold remedies have become important due to the pandemic. The tools have wider applicability in marketing research.

Less wasteful expenses always benefit the society.

To the best of the authors’ knowledge, this may be the first such attempt to use sophisticated causal identification tools. Remedies for the common cold sold by seven major US retailers help identify specific retailers and specific media with negative returns on investment.

The relationship between returns and trading volume is central in financial economics because it has both a theoretical interest and important practical implications with regard to the structure of financial markets and the level of speculation activity. The aim of this study is to provide new insights into the association between returns and trading volume by investigating their kernel (instantaneous) causality. The empirical analysis relies on time series data from 22 commodities futures markets (agricultural, energy and metals) in the USA.

Non-parametric (local linear) regressions are applied to daily data on returns and on trading activity; generalized correlation measures are computed and their differences are subjected to formal statistical testing.

The results suggest that raw returns are likely to kernel-cause volume and volume is likely to kernel-cause price volatility. The patterns of causal order are generally in line with what is stipulated by the relevant theory, they provide guidance for model specification and they appear to explain the empirical evidence on temporal (lag-lead) causality between the same pairs of variables obtained in earlier works.

The concept of kernel causality has very recently become a part of the toolkit for econometric/statistical analysis. To the best of the author’s knowledge, this is the first study that relies on the notion of kernel (instantaneous) causality to provide new evidence on a relationship that is of keen interest to investors, professional economists and policymakers.

This article aims to uncover the impact of Google Trends on cryptocurrency markets beyond Bitcoin during the time of increased attention to altcoins, especially during the COVID-19 pandemic.

This paper analyses the nexus among the Google Trends and six cryptocurrencies, namely Bitcoin, New Economy Movement (NEM), Dash, Ethereum, Ripple and Litecoin by utilizing the causality-in-quantiles technique on data comprised of the years January 2016–March 2021.

The findings show that Google Trends cause the Litecoin, Bitcoin, Ripple, Ethereum and NEM prices at majority of the quantiles except for Dash.

The findings will help investors to develop more in-depth understanding of impact of Google Trends on cryptocurrency prices and build successful trading strategies in a more matured digital assets ecosystem.

We investigate whether or not the effects of the subprime financial crisis on 12 Asian economies are similar to those of the Asian financial crisis by examining volatility spillovers and time-varying correlation between the US and Asian stock markets. After pretesting volatility causality and constancy of correlation, we estimate an appropriate smooth-transition correlation VAR-GARCH model for each Asian stock market. First, the empirical evidence indicates stark differences in stock market linkages between the two crises. The volatility causality comes from the crises-originating country. Volatility in Asian stock markets Granger-caused volatility in the US market during the Asian crisis, whereas volatility in the US stock market Granger-caused volatility in Asian stock markets during the subprime crisis. Second, decreased correlations during the period of financial turmoil were observed, especially during the Asian financial crisis. Third, the estimated points of transition in the correlation are indicative of market participants’ awareness of the ensuing stock market crashes in July 1997 and in September 2008.

The cross-quantilogram analysis is employed. The latter can assess the temporal association between two stationary time series at different parts of their joint distribution. Data are daily prices and trading volumes from the futures markets of five agricultural commodities, namely, corn, hard red wheat, oats, rice and soybeans.

The objective to the present work is to investigate for directional predictability between returns and volume (and vice versa) in the futures markets of agricultural commodities.

The empirical results reveal evidence, weak as well as strong, that extreme low values of returns are likely to lead high levels of volume. There is also weak evidence that extreme low values of volume are likely to precede high values of returns, except for the futures markets of oats where there is very strong evidence that low values of volume are likely to lead high values of returns. For the commodity of soybeans, there is very strong evidence that extreme high levels of volume are likely to lead high values of returns, but they are very short lived.

Agricultural futures have been recently characterized by increased volatility leading hedgers to be looking for diversification. The present findings suggest that when price crashes occur, investors who suffer losses wish to sell, increasing this way the trading activity. Concurrently, the results reveal that extreme low levels of trading volume might signal a possible price turn around for traders.

This is the first study that employs the quantilogram approach in order to investigate for potential predictability from returns to volume and from volume to returns, in the futures markets of agricultural commodities.

The purpose of this paper is to investigate for symmetries – in sign and size – between spot and futures prices in the markets of energy commodities.

The aforementioned objective is pursued using daily observations of spot and futures prices for the commodities of crude oil, Brent, heating oil, gasoline and natural gas, along with local nonlinear regression.

Symmetry in sign and size cannot be rejected. This means that, shocks of the same absolute magnitude, but of different sign, are transmitted from futures prices to spot prices with the same intensity. In addition, larger absolute value price shocks in the futures are transmitted to the spot markets with the same intensity compared with smaller ones. The findings of symmetry in the comovements among prices reveal a lack of those commodities on diversifying the investors’ investment risk.

To the best of the authors’ knowledge, this is the first study to use local nonlinear regression to test for sign and size symmetry between futures and spot prices in the energy commodities markets.

Aims to analyse the influence of Norbert Wiener’s ideas on the social sciences and on social systems, including society as a whole. Describes Wiener’s own attitudes regarding the applicability of cybernetics to social systems and his vision on the development of modern society. Highlights sociologists and political scientists who were inspired by his ideas and deals with researchers who tried to apply his ideas to social systems. Concludes by evaluating to what extent specific ideas of Wiener have impacted on the social sciences.

The purpose of this paper is to investigate whether management strategies implemented by non-commercial traders may be identified as a key factor in affecting oil price paths in the conventional pre- and post-financialization periods.

By using a vector autoregressive approach the dynamic analysis of the daily stock indexes for some of the most important world economies and the oil prices is conducted starting from 1992 to the end of 2020.

The findings do not support the idea that the financial markets act as a privileged conduit in transmitting the shocks to the oil spot quotations.

Such a direct assessment has not been previously proposed in literature wherein – under a financial perspective – the returns are generally taken into consideration.

The authors propose a semiparametric approach for testing independence between two infinite-order cointegrated vector autoregressive series (IVAR(∞)). The procedures considered can be viewed as extensions of classical methods proposed by Haugh (1976, JASA) and Hong (1996b, Biometrika) for testing independence between stationary univariate time series. The tests are based on the residuals of long autoregressions, hence allowing for computational simplicity, weak assumptions on the form of the underlying process, and a direct interpretation of the results in terms of innovations (or shocks). The test statistics are standardized versions of the sum of weighted squares of residual cross-correlation matrices. The weights depend on a kernel function and a truncation parameter. Multivariate portmanteau statistics can be viewed as a special case of our procedure based on the truncated uniform kernel. The asymptotic distributions of the test statistics under the null hypothesis are derived, and consistency is established against fixed alternatives of serial cross-correlation of unknown form. A simulation study is presented which indicates that the proposed tests have good size and power properties in finite samples.

This study attempts to come in help for Morocco by investigating rigorously the linkage between environmental degradation, measured by ecological footprint (EF), and the gross domestic product growth (EG), the human capital (HC) index and the natural resources (NR) depletion over the period of 1980:Q1 to 2021:Q1. The paper examines the validity of environmental Kuznets curve (EKC) hypothesis in the Moroccan context.

Unlike previous studies, which are based only on the autoregressif dynamic linear (ARDL) model, this paper investigates two recent models: the novel DYNARDL simulation approach and the Kernel-based regularized least squares (KRLS) technics and uses in addition the frequency domain causality (FDC) test.

Models output say a significant and negative association between HC and the EF and a significant and positive interplay between economic growth and environmental quality in the long term. In the short term, findings reveal a significant and negative association between NR and the EF. Based on the FDC test, results conclude about a unidirectional causality from NR to the EF in short-, medium-, and long-term. Moreover, results validate the EKC hypothesis for the Moroccan environment sustainability.

In this study, the researchers use the “ecological footprint” as dependent variable to obtain more accurate and comprehensive assessment of environmental deterioration. Based on time series data investigations, this study is the first paper, which validates the EKC hypothesis and develops important policy implications for Morocco context to achieve sustainable development targets.