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This study examines the dynamic responses of five different daily energy prices to a pulse shock affecting the daily price of oil.

Daily data for energy prices from the Federal Reserve Economic Data (FRED) database for January 7, 1997, through February 8, 2021, are analyzed. A bivariate structural vector error correction model and generalized autoregressive conditionally heteroscedastic model are combined and extended by adding the volatility of the growth rate of daily oil prices as an explanatory variable for the growth rates of energy prices. This model is estimated and used to generate impulse responses for energy prices.

The empirical results show that the levels of the daily energy prices examined have unit roots, are integrated of order one, are cointegrated, and generally revert slowly to their long-term equilibrium relationships with the price of oil. The growth rates for the daily energy prices have autoregressive conditional heteroscedasticity, generally are positively related to the volatility of daily oil prices, respond quickly to a pulse shock to daily oil prices, and have cumulative responses that last at least one month.

This paper allows for simultaneous estimation of extended bivariate structural vector error correction and generalized autoregressive conditionally heteroscedastic models that include the volatility of oil as an explanatory variable and uses these models to generated cumulative impulse responses for the growth rates of daily energy prices to oil price shocks.

The purpose of this paper is to examine the dynamic relationships among investment, earnings and dividends for US firms. The sample period is 1950-2006.

The authors use a firm-level vector auto-regression (VAR) framework to examine the firm-level dynamics among investment, earnings and dividends. The firm-level VAR yields Granger causality results, impulse response functions, and variance decompositions characterizing the dynamics of these three variables at the firm level.

For the average firm in the sample, Miller and Modigliani dividend policy irrelevance is not supported, even in the long run; the shocks to dividends do have long-run consequences for investment and vice versa. Dividend changes are an ineffective signal of future earnings in both the short and long-term. The cost of an increased dividend is on average an immediate decrease of $3 in investment for every dollar increase in dividends and the effect is persistent up to six years after the increase in dividends.

The firm-level VAR used in the study requires that sample firms have long histories of investment, earnings and dividend data. The study addresses the interaction between dividends and investment and therefore necessitates examining dividend-paying firms. By the nature of the research question, the sample firms will not be representative in all respects to the universe of firms. The most striking difference between the sample and the universe of firms is firm size. As such, the study's conclusions are most applicable to larger, stable, dividend-paying firms. The study is also limited to dividend payout. Alternative payout policies, such as share repurchases, are not considered in this work.

In theory, increases in dividends can signal higher future earnings; however, the evidence does not support this hypothesis. When capital markets are constrained or incomplete, increases in dividends come at a cost to investment. Firms should consider alternative methods of signaling future earnings that have less of an impact on investment. Investors should carefully evaluate the possible impact of an increase in dividends on investment and future earnings growth.

This study is the first to examine the dynamics of earnings, dividends and investment at a firm level and over such a long sample period. By including the dynamics of earnings, the authors emphasize the potential opportunity costs that increasing dividends has on investment when capital markets are imperfect. The dynamic system also allows the authors to consider long-run effects as well as immediate responses to system shocks.

The purpose of this paper is to investigate the impact of a consumer confidence shock on GDP and different types of consumer spending during a slack state as well as a non-slack state of an economy.

The authors use the US quarterly data from 1960Q1 to 2014Q4 and apply Jorda’s (2005) local projection method to compute the impulse responses of macroeconomic variables to a consumer confidence shock. The local projection method allows us to include non-linearities in the response function.

In general, the response of output, following a consumer confidence shock, is similar in slack and non-slack states and indicate that an unfavorable confidence shock is contractionary. However, the intensity and duration of impact of a confidence shock on different components of spending are state dependent. Overall, a negative confidence shock appears to have a stronger impact on non-slack time than on a slack time.

Policy makers should be careful about undertaking a policy action that may affect consumer confidence adversely, particularly during an economic good time. An adverse confidence shock can trigger a downfall in a well-functioning economy and the dampening effect may last for several quarters before the economy rebounds.

US economy is subject to fluctuations; however, the literature on the impact of confidence shock in different economic states is limited. The incremental contribution of this paper is that it investigates how the consumers respond to the confidence shock in a state-dependent model. Furthermore, the authors use a more robust and alternative estimation method that tackles any non-linear problems.

The purpose of this paper is to propose a fast, accurate and efficient algorithm for assessment of transient behavior of grounding grids buried in horizontal multilayered earth model considering soil ionization effect.

The purpose of this paper is to develop a numerical simulation method to calculate the lightning impulse response of the grounding grid buried in a horizontal multilayered earth model. The mathematical model about the hybrid method based on PI basic function belonging to time domain is proposed in the paper; the mode can precisely calculate the lightning current distribution and lightning impulse response to grounding grids buried in horizontal multilayered soil model considering soil ionization effect. To increase computing efficiency, quasi-static complex image method (QSCIM) and its time-domain Green’s function closed form are introduced in the model.

The hybrid model is rather stable, with the respect to the number of elements used and with excellent convergence rate. In addition, because this mathematical model belongs to the time domain algorithm, it is very powerful for the simulation of soil ionization caused by high amplitude lightning current.

To increase computing efficiency, QSCIM and its time domain Green's function closed form are introduced in the model.

The mathematical model about the hybrid method based on PI basic function can precisely calculate the lightning current distribution and lightning impulse response to grounding grids buried in horizontal multilayered soil model considering the soil ionization effect.

Considering the soil ionization effect, the simulation calculation of lightning impulse response of substation grounding grid buried in the actual horizontal multilayered earth can effectively support the scientific and efficient design of lightning protection performance of substation grounding grid.

The hybrid model in time domain is originally developed by the authors and used to precisely calculate the lightning current distribution and lightning impulse response to grounding grids buried in horizontal multilayered soil model considering soil ionization effect. It is simple and very efficient and can easily be extended to arbitrary grounding configurations.

This paper aims to examine the effects of fiscal policy associated with increases in government expenditures, tax revenue and budget deficit on the South African economy.

Structural VARs based on the Blanchard‐Quard decomposition identification scheme were used in the empirical analysis. With the aid of quarterly data covering the period 1990:1 to 2008:4, the identified true models are used to estimate various impulse‐response functions. The impulse‐response functions represent the responses of real output and interest rates to shocks from tax revenue, budget deficit and government consumption and investment expenditures.

The results suggest that the fiscal policy instruments have varied effects on output and interest rates. The effect of the fiscal policy on output appears to be quite modest but persistent; however, the response from interest rate is temporary and substantial most cases.

The debate on the efficacy of fiscal policy in stimulating growth seems to have assumed new prominence in the wake of the recent global financial crisis. This paper contributes to the discourse from a South African focused empirical effort. Other fiscal policy authorities may find the paper valuable.

Recently, fractional differential equations have been used to model various physical and engineering problems. One may need a reliable and efficient numerical technique for the solution of these types of differential equations, as sometimes it is not easy to get the analytical solution. However, in general, in the existing investigations, involved parameters and variables are defined exactly, whereas in actual practice it may contain uncertainty because of error in observations, maintenance induced error, etc. Therefore, the purpose of this paper is to find the dynamic response of fractionally damped beam approximately under fuzzy and interval uncertainty.

Here, a semi analytical approach, variational iteration method (VIM), has been considered for the solution. A newly developed form of fuzzy numbers known as double parametric form has been applied to model the uncertainty involved in the system parameters and variables.

VIM has been successfully implemented along with double parametric form of fuzzy number to find the uncertain dynamic responses of the fractionally damped beam. The advantage of this approach is that the solution can be written in power series or compact form. Also, this method converges rapidly to have the accurate solution. The uncertain responses subject to impulse and step loads have also been computed and the behaviours of the responses are analysed. Applying the double parametric form, it reduces the computational cost without separating the fuzzy equation into coupled differential equations as done in traditional approaches.

Uncertain dynamic responses of fuzzy fractionally damped beam using the newly developed double parametric form of fuzzy numbers subject to unit step and impulse loads have been obtained. Gaussian fuzzy numbers are used to model the uncertainties. In the methodology using the alpha cut form, corresponding beam equation is first converted to an interval-based fuzzy equation. Next, it has been transformed to crisp form by applying double parametric form of fuzzy numbers. Finally, VIM has been applied to solve the same for the general fuzzy responses. Various numerical examples have been taken in to consideration.

To provide an efficient and accurate model for interconnect networks characterised by frequency‐domain scattering or admittance parameters. The parameters are derived from measurements or rigorous full‐wave simulation.

Initially, Hilbert transform relationships are enforced to ensure causality. A reverse Fourier series representation of the discrete data is then converted to the z‐domain and from this a state‐space formulation is determined. This enables the application of a judiciously chosen model reduction algorithm to obtain an efficient time‐domain representation of the network.

Sample results from both simulated and measured data indicate the efficacy of the proposed modelling strategy. For successful implementation of the strategy, it is necessary to employ the Hilbert transform to ensure that a causal impulse response is obtained.

The method is applicable to the interconnect networks for which the analytical models cannot be obtained due to the complexity and inhomogeneity of the geometries involved.

The work combines in a novel manner aspects from several existing techniques proposed for network simulation and model reduction. The end result is a highly efficient causal, stable and passive representation of the network in question for implementation in a time‐domain circuit simulator.

The purpose of this study is to investigate the interactive relationships between oil price shocks and the Nigeria stock market.

The paper applied the multivariate vector auto‐regression that employed the generalized impulse response function and the forecast variance decomposition error.

Empirical evidence reveals that stock market returns exhibit insignificant positive response to oil price shocks but reverts to negative effects after a period of time depending on the nature of the oil price shocks. The results are similar even with the inclusion of other variables. Also, the asymmetric effect of oil price shocks on the Nigerian stock returns indices is not supported by statistical evidences.

This is the first study to examine the dynamic linkages between stock market behaviour and oil price shocks in Nigeria.

This paper aims to attempt to capture the intertemporal/time-varying risk–return relationship in the Brazil, Russia, India and China (BRIC) equity markets after the global financial crisis (2007-2009), i.e. during a relative calm period. There has been a significant increase in advanced economies’ equity allocations to the emerging markets ever since the financial crisis. So, the present study is an attempt to account for the said relationship, thereby justifying investments made by the international investors.

The study uses non-linear models comprising asymmetric component generalised autoregressive conditional heteroskedastic model in mean (CGARCH-M) (1,1) model, generalised impulse response functions under vector autoregressive framework and Markov regime switching in mean and standard deviation model. The span of data ranges from 1 July 2009 to 31 December 2014.

The ACGARCH-M (1,1) model reports a positive and significant risk-return relationship in the Russian and Chinese equity markets only. There is leverage and volatility feedback effect in the Russian market because falling returns further increase conditional variance making the investors to expect a risk premium in the expected returns. The impulse responses indicate that for all of the BRIC markets, the ex-ante returns respond positively to a shock in the long-term risk component, whereas the response is negative to a shock in the short-term risk component. Finally, the Markov regime switching model confirms the existence of two regimes in all of the BRIC markets, namely, Bull and Bear regimes. Both the regimes exhibit negative relationship between risk and return.

It is an imperative task to comprehend the relationship shared between risk and returns for an investor. The investors in the emerging economies should understand the risk-return dynamics well ahead of time so that the returns justify the investments made under riskier environment.

The present study contributes to the literature in three senses. First, the data relate to a period especially after the global financial crisis (2007-2009). Second, the study has used a relatively newer version of GARCH based model [ACGARCH-M (1,1) model], generalised impulse response functions and Markov regime switching model to account for the relationship between risk and return. Finally, the study provides an insightful understanding of the risk–return relationship in the most promising emerging markets group “BRIC nations”, making the study first of its kind in all the perspectives.

The purpose of this paper is to explore dynamics of stock price movements of an emerging market, Bangladesh with that of USA, Japan and India.

The long‐term relationships among the markets are analyzed using the Johansen and Juselius multivariate cointegration approach. Short‐run dynamics are captured through vector error correction models. Further investigation on short‐run dynamics is carried out through impulse response analysis.

There is evidence of cointegration among the markets demonstrating that stock prices in the countries studied here share a common stochastic trend. Impulse response analysis shows that shocks to the US market do have an impact on the Bangladesh market. The evidence of Bangladesh stock market responding to shocks in the Indian market is weak. Shocks to the Japanese market do not generate a response in the Bangladesh market.

As these markets share a common stochastic trend no diversification benefit is possible from cross‐border investments. Investors could further enhance their understanding of market behaviour by comparing the observations here with those of studies that adopt technical analysis, fundamental analysis and consider financial anomalies.

The evidence of cointegration and the short run dynamic relationship help investors in making efficient investment decisions in the Bangladesh stock market.