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This paper seeks to demonstrate an application of a methodology, which is based on the integration of three techniques, with the purpose of modelling activity‐based costing (ABC) in restaurants. The proposed methodology serves as a tool for effectively computing values of cost drivers in the restaurant industry, as well as making accurate cost estimations.

The methodology is based on the integration of three techniques: simulation modelling, association rule mining (ARM) and ABC. Simulation modelling is used to model process variability and produce a range of cost values, instead of a point estimate of the cost, by generating a range of values for the simulated cost drivers. The advantage of the proposed methodology lies on the effective utilization of ARM in the ABC model; it extracts dependencies between a cost driver, whose estimation is time‐consuming, with another cost driver, which can easily be calculated. These associations can assist the estimation of the empirical distributions of those cost drivers, which were difficult to calculate.

The extracted associations verify the hypothetical relations between the cost drivers. The output produced is more precise values of the cost drivers that are included in an ABC model and were difficult to estimate. More accurate cost estimate means better pricing decisions for the restaurant managers.

The proposed methodology is an innovative technique that provides more accurate accounting information in the restaurant industry.

The aim of this chapter is to investigate the relationship between the uses of budgets with financial performance in start-ups’ business environment. For this reason, an empirical survey was carried out, using a questionnaire in 134 start-up companies, which are based in 10 different European countries. Results show that there is a positive association between the use of budgets for planning, resource allocation and performance evaluation with financial performance. The CEO’s business educational background, as well as CEO’s beliefs about planning, has a strong influence in the use of budgets in start-up firms. We also concluded that there is a positive association between perceived environmental uncertainty (PEU) and the use of budgets for planning and resource allocation and a negative association between PEU and the use of budgets for performance evaluation.

The main aim of this paper is to examine the mechanism of determining the exchange rate of the US dollar against the Indonesian rupiah (USD/IDR) by market players to manage the USD/IDR exchange rate stability. Thus, this study is expected to provide a better understanding of the determinants of the USD/IDR, given that the data set completely encompasses all the USD/IDR transactions in the Indonesian foreign exchange market. Order flow data used in this study cover all transactions on the USD/IDR conducted by domestic residents including both individuals and corporations and foreign investors in the Indonesian foreign exchange market.

This study covers the data set over the period January 3, 2011 to December 31, 2015, and the vector autoregression and autoregressive distributed lag models are used in examining the research questions. More particularly, in this study, the author examines whether the net total domestic individual transactions (DOVA), net total domestic corporation transactions (KOVA), net total foreign investor transactions (IOVA), Asian Dollar Index (ADXY), non-deliverable forward (NDF) for USD/IDR and Volatility Index (VIX) are statistically significant determinants of the USD/IDR exchange rate.

Overall, this study suggests that in the short run, lag of the USD/IDR exchange rate or inertia level, lag of the IOVA, lag of the NDF of the USD/IDR exchange rate and lag of the ADXY are statistically significant determinants of the USD/IDR. On the other hand, in the long run, DOVA, NDF and ADXY are found to be statistically significant determinants of USD/IDR. This study also found that there is a market leader and asymmetric information among market players in the Indonesian foreign exchange market, and their USD/IDR exchange rate level becomes a reference for other market players when conducting transactions with each other.

The paper is original along two lines. First, the data set used in this study is unique. It encompasses all the USD/IDR transactions in the Indonesian foreign exchange market. The order flow data used in this study cover all transactions on the USD/IDR conducted by domestic residents (includes both individuals and corporations) and foreign investors in the Indonesian foreign exchange market. Such an approach has not been used previously to study the exchange rate behavior in an emerging market. Second, there is limited knowledge on Indonesia’s exchange rate dynamics. This study fills this gap.

The purpose of this paper is to investigate the impact of the global coronavirus (COVID-19) pandemic on stock market liquidity, while taking into account the depth and tightness dimensions.

The author used a panel data regression on stock market dataset, representing 314 listed firms operating in six Middle East and North African (MENA) countries from February to May 2020.

The regression results on the overall sample indicate that the liquidity related to the depth measure was positively correlated with the growth in the confirmed number of cases and deaths and stringency index. Moreover, the market depth was positively related to the confirmed cases of COVID-19. The results also indicate that the liquidity of small cap and big cap firms was significantly impacted by the confirmed number of cases, while the stringency index is only significant for the liquidity depth measure. Moreover, the results regarding sectors and country level analysis confirmed that COVID-19 had a significant and negative impact of stock market liquidity.

This paper confirms that the global coronavirus pandemic has decreased the stock market liquidity in terms of both the depth and the tightness dimensions.

While most empirical papers focused on the impact of the COVID-19 global pandemic on stock market returns, this paper investigated liquidity chock at firm level in the MENA region using both tightness and depth dimensions.

This study aims to examine the relationship between economic policy uncertainty and stock market liquidity in an order-driven emerging stock market.

Empirical estimates are based on vector autoregressive Granger-causality tests, impulse response functions and variance decomposition analysis.

The empirical findings suggest that economic policy uncertainty moderately influences stock market liquidity during normal market conditions. However, the role of economic policy uncertainty for determining stock market liquidity is significant in times of financial crises. The authors have also observed a significant portion of variation in stock market liquidity that is attributed to investor sentiments during financial crises.

This study is original in nature and provides evidence to consider economic policy uncertainty as a possible source of commonality in liquidity in the context of an emerging market.

The purpose of this paper is to examine stock market reactions and liquidity effects following the first bank loan announcement of zero-leverage firms.

The authors use an event studies methodology in both a univariate and multivariate framework. The authors also use regression analysis.

Using a sample of 96 zero-leverage firms listed on the FTSE 350 index over the time period of 2000–2015, the authors find evidence of a significant and permanent stock price increase as a result of the initial debt announcement. The loan announcement results in a sustained increase in trading volume and liquidity. This improvement continues to persist once the authors control for stock price and trading volume effects in both the short and long run. Furthermore, the authors examine the spread decomposition around the same period, and discover the adverse selection of the bid–ask spread is significantly related to the initial bank loan announcement.

The results can be attributed to the information cost/liquidity hypothesis, suggesting that investors demand a lower premium for trading stocks with more available information.

This is the first paper to look at multiple industries, more than one loan and information asymmetry effects.

The purpose of this paper is to evaluate the profitability of investment strategies based on past price changes and trading volumes.

Data are employed from January 1998 to December 2011 for select emerging markets. Portfolios are formed on the basis of past information on prices and/or volumes. Unrestricted and risk adjusted returns for sample portfolios are analyzed. The risk models employed in study are Capital Asset Pricing Model (CAPM), Fama-French (F-F) Model and Fama-French augmented models.

Price momentum patterns are observed for Brazil, India, South Africa and South Korea, while there are reversals in Indonesia and China. Low-volume stocks outperform high-volume stocks for all sample countries except China. Further, volume and price based bivariate strategies do a better job than univariate strategies in case of India, South Africa and South Korea. The past price and volume patterns in stock returns are not fully explained by CAPM as well as the F-F Model. Price and volume momentum factors do play a role in explaining some of these return patterns. Finally, the unexplained returns seem to be an outcome of investor under or overreaction to past information. The sources of price and volume momentum seem to be partly risk based and partly behavioral.

The study analyzes combined role of price and volume in portfolio formation with post holding analysis. The work is useful for global portfolio managers, policy makers, market regulators and the academic community. The study contributes to asset pricing and behavioral finance literature for emerging markets.