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One of the crucial issues in the contemporary finance is the prediction of the volatility of financial assets. In this paper, the authors are interested in modelling the stochastic volatility of the MAD/EURO and MAD/USD exchange rates.

For this purpose, the authors have adopted Bayesian approach based on the MCMC (Monte Carlo Markov Chain) algorithm which permits to reproduce the main stylized empirical facts of the assets studied. The data used in this study are the daily historical series of MAD/EURO and MAD/USD exchange rates covering the period from February 2, 2000, to March 3, 2017, which represent 4,456 observations.

By the aid of this approach, the authors were able to estimate all the random parameters of the stochastic volatility model which permit the prediction of the future exchange rates. The authors also have simulated the histograms, the posterior densities as well as the cumulative averages of the model parameters. The predictive efficiency of the stochastic volatility model for Morocco is capable to facilitate the management of the exchange rate in more flexible exchange regime to ensure better targeting of monetary and exchange policies.

To the best of the authors’ knowledge, the novelty of the paper lies in the production of a tool for predicting the evolution of the Moroccan exchange rate and also the design of a tool for the monetary authorities who are today in a proactive conception of management of the rate of exchange. Cyclical policies such as monetary policy and exchange rate policy will introduce this type of modelling into the decision-making process to achieve a better stabilization of the macroeconomic and financial framework.

This study aims to examine the effects of allocation of audit hours to year-round audits and audit partners on audit quality when a new partner is appointed.

Using proprietary data of partners’ names and audit hours in the year-round context, the authors build a model testing input factors related to audit production and new partner assignment in 1,209 Korean listed firms during the period of 2015–2018.

The results show that in the partner rotation, the more audit hours spent, the more audit hours are allocated to the year-round audit, or more nonpartners’ audit hours are allocated to the year-round audit, the higher the audit quality. Subsample analyses show that these findings are concentrated in firms with longer audit tenure or low audit risk.

The findings may provide regulatory authorities with practical guidelines concerning partner rotation and how to allocate audit hours to different audit stages and ranks (partner vs staff).

To the best of the authors’ knowledge, this study provides the first evidence of the joint effects of partner rotation and audit hour allocation on audit quality.

The present study aims to provide a roadmap for meeting the carbon-free, green energy production target within the stipulated period while also considering climate targets through a sustainable auctioning scheme.

The research outlines the opportunity to design auctions based on qualitative research, the impact of auctions on energy costs and thus the feasibility of suggested auctioning schemes based on country-specific empirical evidence and benefits.

The conclusions show that this may result in various advantages for emerging economies relating to technology-neutral site-specific auctions if designed according to state-specific socio-economic conditions.

The planned addition to the state-of-the-art in the renewable energy (RE) field of this paper is that it intends to bridge the gap between theory and practice. The analysis has concepts for research, practice and/or community. Thus, it can serve as a primary source of literature reference for those willing to learn more about the aspects of cost related to RE.

As a financial policy, dividend policy significantly affects firm value. This chapter analyzes how stock prices react to dividend decisions. First, a dividend payment is an extraction of value; therefore, stock price theoretically drops by the dividend amount on the ex-dividend day. In practice, the price drop and the dividend magnitude are not equal because of tax clientele, short-term trading, and market microstructure. Investors are indifferent in trading stocks before and after stocks go ex-dividend if they obtain equal marginal benefits from the two trading times. The difference in tax rates on dividends and capital gains leads to the gap between the price drop and the dividend amount. Moreover, if transaction costs are considerable, investors have high incentives to short-sell stocks until they cannot obtain more profits. The final outcome of this short-term trading is the difference between the price drop and the dividend amount. Furthermore, market microstructure factors such as limit orders, bid-ask spread, and price discreteness also create this gap. Second, dividend announcements convey valuable information to outsiders. When firms announce increases (decreases) in dividends, their stock prices tend to increase (decrease). Third, dividend policy is negatively related to stock price volatility. This negative relationship is explained by duration effect, rate of return effect, arbitrage realization effect, and information effect. Empirical evidence for this relationship is found in many countries. Finally, dividend smoothing is also considered as a signal about firms' future earnings. Consequently, firms with stable dividends have higher market value. In other words, dividend stability has a positive effect on stock prices.

How to realize social capital “exit from virtual to real” has become not only a hot issue that elicited economists' and the practice field's concern but also a key economic structure problem that the government has to solve urgently. The main purpose of this study is to explore effective methods for social capital to “exit from virtual to real”.

The study investigates the realization path of social capital's “exit from virtual to real” by using firm theory and data from the National Bureau of Statistics in China. Provincial panel data are also utilized to empirically test the impact of social capital's de-realization to virtual (or from virtual to real) on economic development and whether the path of social capital “from virtual to real” is valid.

This study analyzes the development status of social funds serving the real economy and the hazards of social funds' “exit from real to virtual,” which are mainly viewed as eroding the development of the real economy and causing operating difficulties. On the basis of firm theory, the internal motivation for why social funds flow to the real economy is explored from the perspectives of the needs of the real economy, price and profit. Moreover, this study designs a path for returning social capital to the real economy.

Overall, expanding aggregate demand while providing an effective supply and implementing a proactive fiscal policy that focuses on structural tax cuts while keeping margins in the virtual economy are appropriate for promoting the competitiveness of the real economy.

This study explores a topic, namely, social capital “exit from virtual to real,” that has received little attention. It provides an in-depth discussion of the following questions. (1) What is the current situation of social capital serving the real economy? (2) What kind of harm can social capital bring to society? What are the inherent barriers to the flow of social capital to the real economy? (3) At this stage, how can the effective transformation of social capital into the real economy be realized? The findings help in understanding the sustainable entrepreneurship concept, particularly in developing countries.

The provision of fair and remunerative prices to farmers through government intervention is one of the key debates to address the farmers' distress in India. This article identifies how different marketing channels are responsible for higher price realization over the officially announced minimum support price (MSP).

The study uses the NSSO-SAS, 2012–13 and NSSO-SAS, 2018–19 for Aggregate level data and Unit Level Data on the Situation Assessment Survey of Farmers' households. It uses logit regression to determine the factors responsible for better price realization.

Our major findings indicate that two factors importantly determine better price realization than MSP. Firstly, government agencies provide better prices for crops covered by MSP, such as paddy, wheat and cotton. However, the probability of receiving higher prices increases for some crops if the farmers belong to the upper land size classes and upper social category. Secondly, jowar, bajra, maize and ragi, other important crops that don't benefit from government agencies, may require higher levels of procurement at the state level.

The present study only analyzes selected major crops. Distance is an important factor in choosing a marketing channel that is not incorporated due to unavailability in NSS Data.

The study is based on the latest original empirical evidence and sheds light on the variation in price realization in different agricultural marketing channels in India.

Enterprise resource planning (ERP) consultants have the expertise required to understand the specific contextual needs of an ERP client, implement tailored business processes that meet those needs, and ensure that no potential benefit offered by the ERP remains unexplored by the client. However, conflicts between ERP clients and consultants are a significant source of non-benefit realisation, making managing client–consultant agency crucial to ERP post-implementation benefits realisation. This paper aims to elucidate how managing client–consultant agency affects the benefits derived from ERP systems.

This paper uses microfinance institutions in 15 sub-Saharan African countries to explore different paths through which managing client–consultant agency leads to benefit realisation in ERP projects. It uses partial least squares structural equation modelling to analyse data from 127 managers and explains the results using insights from agency theory and the information system (IS) success model.

This paper reveals three routes through which contractual agreements and conflict resolution strategies lead to benefits realisation in ERP projects.

This is the first study that attempts to provide quantitative evidence of how managing the complex relationship between ERP project stakeholders affects ERP project success. It also contributes a novel theoretical model for ERP benefits realisation to complement existing research on ERP agency issues, critical success factors, and benefits realisation.

The purpose of optimal protocol prediction and the benefits offered by quantum key distribution (QKD), including unbreakable security, there is a growing interest in the practical realization of quantum communication. Realization of the optimal protocol predictor in quantum key distribution is a critical step toward commercialization of QKD.

The proposed work designs a machine learning model such as K-nearest neighbor algorithm, convolutional neural networks, decision tree (DT), support vector machine and random forest (RF) for optimal protocol selector for quantum key distribution network (QKDN).

Because of the effectiveness of machine learning methods in predicting effective solutions using data, these models will be the best optimal protocol selectors for achieving high efficiency for QKDN. The results show that the best machine learning method for predicting optimal protocol in QKD is the RF algorithm. It also validates the effectiveness of machine learning in optimal protocol selection.

The proposed work was done using algorithms like the local search algorithm or exhaustive traversal, however the major downside of using these algorithms is that it takes a very long time to revert back results, which is unacceptable for commercial systems. Hence, machine learning methods are proposed to see the effectiveness of prediction for achieving high efficiency.