Iqbal Thonse Hawaldar

Efficient market hypothesis (EMH) states that financial markets are “informationally efficient”, implying that current prices fully reflect all available information. The present study aims at testing the weak form of market efficiency of the individual stocks listed on the Bahrain Bourse for the period 2011 to 2015. Weak form of EMH is tested using the Kolmogorov-Smirnov goodness of fit test, run test and autocorrelation test. The K-S test result concludes that in general the stock price movement does not follow random walk. The results of the runs test reveals that share prices of seven companies do not follow random walk. Autocorrelation tests reveal that share prices exhibit low to moderate correlation varying from negative to positive values. As the study shows mixed results, it is difficult to conclude the weak form of efficiency of Bahrain Bourse.

Semi-monthly effect is a kind of calendar anomalies which is less explored in the financial literature. The main objective of this paper to investigate the presence of semi-monthly effect in selected sectoral indices of Bombay Stock Exchange (BSE). The study uses the daily stock returns of five sectoral indices viz S&P BSE Auto Index, S&P BSE Bankex, S&P BSE Consumer Durables Index, S&P BSE FMCG Index and S&P BSE Health Care Index for the period of 10 years starting from 1st April 2007 to 31st March 2017. The data were analyzed using two approaches namely calendar days approach and trading days approach. To test the equality of mean returns for the two halves of the month, Mann-Whitney U test is used. The empirical results of the study did not provide any evidence for the presence of semi-monthly effect in the selected sectoral indices. Nevertheless, BSE Auto Index showed significant difference in the mean returns of first half and second half of trading month during the study period.

Oil export is the major source of revenue for the countries in the Middle East. Their economies are sensitive to fluctuations in oil prices. The present study examines the impact of oil crisis on the performance of selected banks of Kingdom of Bahrain using profitability, efficiency, capital adequacy and liquidity ratios in the pre-crisis and crisis periods. The study reveals that there is no significant difference in the performance of banks in the pre-crisis and crisis period. The results indicate that there is a significant difference in the performance of conventional banks and Islamic banks in the pre-crisis period. However, there is no significant difference in the performance of conventional banks and Islamic banks during the crisis period.

The paper is based on information which is a combination of store advertisement and consumers’ path inside the store along with product information. With this information, the authors find how advertisement affects the behavior of consumers when making the decision. The findings suggest that advertisement has a small impact on customers inside the stores. Null effect is determined, and one standard deviation in advertising has an impact on store traffic by 1.2%. But the impact at a lower end of the model is observed. One standard deviation in advertisement has impacted the store sales by 8.4%. Based on further data mining, the research has found that there is no significant improvement in the number of customers, but the increase in sales is because of the higher quantity of purchases by the existing consumers. However, the effect of advertisement on products placed in the same or nearby shelf is not found, the impact on product varieties in the same segment is also not found. Based on these research findings, the authors find the right approach towards advertisement.
The research is limited to consumers of retail industry in a Tier 3 Indian city of a developing geographic segment only.

Agricultural credit is required for the development of agriculture scenario in any economy. Commercial, cooperative and regional rural banks have extended agricultural credit to the farmers in Dakshina Kannada district of India. The effectiveness of agricultural credit system depends on the utilization of credit funds by the borrowers. The present study made an attempt to understand the factors influencing the utilization of agricultural credit of banks in Dakshina Kannada. The study used primary and secondary data. Primary data are gathered from the borrowers of banks operating in Dakshina Kannada district. The study found that there is an impact of demographic, agriculture and agricultural credit factors on the purpose of utilization of agricultural credit in Dakshina Kannada district.

Waiting involves both cognition and emotions. It has a bearing on the overall perception of retail service quality. The advancement in retailing has triggered scholarly conversations on the psychological impact of waiting at the retail checkout. Prior studies confirm customers being deeply involved in the passage of time and time estimation during the entire waiting period. This study investigates the customer idle time and its implication on emotional discomfort resulting from crowding stress. The study employed confirmatory sampling wherein specific sample elements are chosen since they are the key respondents to confirm hypotheses being tested. Accordingly, 385 respondents (shoppers) visiting the leading organized retailers located in major localities in Bengaluru were approached. The responses were analyzed using a Chi-squared test and Pearson correlation. The outcome reveals that irrespective of age and gender, customers visiting the offline retail outlets experience emotional discomfort. The young customers aged 18-30 dislike waiting in the queue at the checkout compared to older customers. In contrast, gender did not affect the inclination to wait. The idleness during the checkout waits causes emotional discomfort on most occasions. The findings supplement the growing research in psychology on the actual and perceived consumption of time, focusing on idleness. The study concludes that customers desire to avert an unproductive use of time, thus lowering their emotional discomfort.

The Capital Asset Pricing Model (henceforth, CAPM) is considered an extensively used technique to approximate asset pricing in the field of finance. The CAPM holds the power to explicate stock movements by means of its sole factor that is beta co-efficient. This study focuses on the application of rolling regression and cross-sectional regression techniques on Indian BSE 30 stocks. The study examines the risk-return analysis by using this modern technique. The applicability of these techniques is being viewed in changing business environments. These techniques help to find the effect of selected variables on average stock returns. A rolling regression study rolls the data for changing the windows for every 3-month period for three years. The study modifies the model with and without intercept values. This has been applied to the monthly prices of 30 BSE stocks. The study period is from January 2009 to December 2018. The study revealed that beta is a good predictor for analyzing stock returns, but not the intercept values in the developed model. On the other hand, applying cross-section regression accepts the null hypothesis. α, β, β2 ≠ 0. Therefore, a researcher is faced with the task of finding limitations of each methodology and bringing the best output in the model.

The study aims to determine the impact of Capital Adequacy Ratio, Credit Losses Ratio and Efficiency Ratio on the two significant profitability ratios, namely Return on Assets (ROA) and Return on Equity (ROE), during the pandemic. Panel Data Regression is used to model the effects of Capital Adequacy, Credit Losses and Efficiency Ratio on Return on Assets and Return on Equity of Indian banks. A suitable model has been developed by analyzing the results of the Hausman test and the p-values. It has been found that Capital Adequacy Ratio (CAR) with coefficient value of –0.664, CET1 with coefficient value of 1.83 and efficiency ratio with coefficient value of 1.825 have significantly affected the return on assets as their p-values are less than 0.05. However, the accepted relationship between CAR and ROA, efficiency ratio and ROA were inverse, but their coefficients were significant. The provision for credit losses (PCL) was not affecting the ROA significantly during the pandemic and hence was not considered while framing the model. Again, the dependent variable is the return on equity, except CAR. Other ratios, i.e., CET1, efficiency ratio, and PCL ratio have unacceptable correlations and are even non-significant as their p-values are less than 0.05.

This paper investigates volatility spillovers in the stock market in Japan during the COVID-19 pandemic by using GARCH family models. The empirical analysis is focused on the dynamics of the NIKKEI 225 stock market index during the sample period from July 30, 1998, to January 24, 2022. In other words, the sample period covers both the period of the global financial crisis (GFC) and the COVID-19 pandemic. The econometrics includes GARCH (1,1), GJR (1,1), and EGARCH (1,1) models. By applying GARCH family models, this empirical study also examines the long-term behavior of the Japanese stock market.
The Japanese stock market is much more stable and efficient than emerging or frontier markets characterized by higher volatility and lower liquidity. The paper establishes that NIKKEI 225 index dynamics is different in intensity in the case of the two most recent extreme events analyzed, namely the global financial crisis (GFC)of 2007–2008 and the COVID-19 pandemic. The findings confirmed the presence of the leverage effect during the sample period. Moreover, the empirical results identified the presence of high volatility in the sample returns of the selected stock market. Nevertheless, the econometric framework showed that the negative implications of the GFC were much more severe and caused more significant contractions compared to the COVID-19 pandemic for the Japanese stock market. This study contributes to the existing literature by providing additional empirical evidence on the long-term behavior of the stock market in Japan, especially in the context of extreme events.

Retail customers often wait to complete their purchases during the checkout process. Prior research suggests that long checkout lines and service delays negatively affect customers’ evaluation of store services. The present study investigates the potential customer and in-store distractions and their implication for emotional discomfort due to crowding stress. This study employed a cross-sectional research design and surveyed 385 respondents visiting the target retail outlets in Bengaluru, India. Correlation analysis explored the relationship between self-distraction, in-store distractions, and emotional discomfort. The study found that self-distraction negatively correlates with discomfort while in the queue (r = –0.119) and discomfort during the billing (r = –0.119). In contrast, in-store distractions (r = –0.161) and video displays near the checkout area (r = 0.116) effectively reduce emotional discomfort while in the queue. Additionally, point-of-purchase (POP) display (r = –0.265) and availability of refreshments near the billing counter (r = –0.175) are effective in reducing emotional discomfort during the billing. This study thus offers viable and affordable methods of improving the customer’s waiting experience while contributing to store profits.

The Indian IPO market showcased resilience during the global stock market downturn in 2022, emerging as a notable bright spot in regions such as Europe, the Middle East, India, and Africa. As the bullish rally of 2022 persists, Indian stock markets remain enticing for foreign institutional investors in 2023. A resurgence in IPO activity is anticipated, driven by increasing momentum and larger deals that are poised to overcome the constraints of subdued global sentiments and liquidity pressures, addressing the challenges posed by these factors. The study offers insights into factors influencing IPO subscriptions, capitalizing on the context of heightened stock market volatility and optimistic trends in the Indian stock market. A total of 132 IPOs listed on the Indian stock market between April 2019 and March 2023 were analyzed in this study. Multiple Linear Regression was used to assess the strength of the association between several factors outlined in the literature, and the overall subscription. Among the ten variables investigated in the study, it was observed that three variables under the external factors, specifically Grey Market Premium, IPO Rating, and Broker Recommendations, exerted a significant influence on the overall subscription. While other factors such as allocation proportion and issue attributes, were found to have no discernible influence on the overall subscription. The results indicate that the Indian IPO market demonstrates a prevalence of speculative behavior and a stronger reliance on expert recommendations, rather than being primarily driven by IPO characteristics.

Acknowledgment
Authors acknowledge that the publication fee is funded by Kingdom University, Bahrain.

This paper intends to analyze the impact of store layout, ambient factors, and employees on impulsive decision-making among female customers visiting the apparel outlets. The responses were collected through a single-stage mall intercept survey method using a structured questionnaire from 385 respondents in leading apparel stores in selected Tier I and Tier II cities in the state of Karnataka, India. The responses were analyzed using multiple regression analysis. Constructs such as store layout, ambience and employees were found to be significantly positively correlated with impulse buying behavior. The variables largely explain the variation in impulse buying under store ambiance. Except ‘attention to the window display’ and ‘friendly staff’ all other twelve variables considered in the study were found to have significant impact on the impulse buying behavior. Though store ambiance, well-structured layout, and pleasant shopping experience are essential determinants of customer satisfaction, the study results imply that the number of store staff and sales skills are critical aspects of impulse buying in the apparel business and true assets to the retail organization. Additionally, poor customer interaction, staff shortage, and high employee attrition could discourage the store’s revenue generation.

Many investors in order to predict stock prices use various techniques like fundamental analysis and technical analysis and sometimes rely on the discussions provided by various stock market analysts. ARIMA is a part of time-series analysis under prediction algorithms, and this paper attempts to predict the share prices of selected pharmaceutical companies in India, listed under NIFTY100, using the ARIMA model. A sample size of 782 time-series observations from January 1, 2017 to December 31, 2019 for each selected pharmaceutical firm has been considered to frame the ARIMA model. ADF test is used to verify whether the data are stationary or not. For ARIMA model estimation, significant spikes in the correlogram of ACF and PACF have been observed, and many models have been framed taking different AR and MA terms for each selected company. After that, 5 best models have been selected, and necessary inculcation of various AR and MA terms has been made to adjust the models and choose the best adjusted ARIMA model for each firm based on Volatility, adjusted R-squared, and Akaike Information Criterion. The results could be used to analyze the stock prices and their prediction in-depth in future research efforts.

Performance appraisal is the bedrock of talent management and has received much attention from scholars and researchers alike in their pursuit to develop accurate, objective, and robust Performance Management Systems (PMS). Through survey questionnaire the present study examines the prevalence of idiosyncratic rater biases on the performance appraisal systems and evaluates the measure of its impact. The correlations between the personality traits and the similarities of the raters’ workplace characteristics with the raters’ performance ratings are also determined. The study has provided empirical evidence of the manifestation of idiosyncratic rater bias in the company under study. The idiosyncratic rater tendencies showed a significant impact on performance ratings. It was seen that about one-third of the variations in the ratings were resultant of the idiosyncratic factors, such as similarities in the personality traits and workplace identities. It is also found that there exists a positive correlation between the similarities in the identities, as well as the personality traits of the raters and the ratees, and the way the rating awarded by the rater.

Investors invest in a foreign market to reap the benefits of currency differences. The change in the value of underlying assets affects these hedged funds and, at the same time, restricts investors from higher return possible in unhedged funds. This study aims to examine the performance of most actively traded shares in Exchange Traded Fund and any influence, along with tracking the information from the index. This study also analyzes the currency fluctuation and its impact on returns and volatility of ETF and index. The equity ETF, which tracks NASDAQ (NDX 100), is chosen for the study, and the data analysis is carried out using statistical methods such as correlation, regression, and GARCH model. The study utilizes the currency rate data from 2013 to 2018 of USD, GBP, and INR and examines its effect on the NDX (NASDAQ). The study emphasizes whether the ETF as a basket of securities is insensitive to currency rate fluctuations. It is found that the response of ETF to the currency movements is likely due to its underlying index. The study concludes that Motilal Oswal shares in NASDAQ 100 ETF are highly sensitive to the NDX 100 movements; thus, there is no direct impact between ETF and index performance through exchange rate fluctuation.

The online food delivery market in India perseveres to grow at a sustained pace. The business has unique dynamics and challenges with the spike in orders during weekends, meeting delivery schedules during peak demand, offering deep discounts to address wavering customer loyalty, reducing cash burns, and managing food quality inconsistency. In contrast, the fast-paced life and the rise of millennials in the workforce is likely to assure a promising future for the food aggregators. The above backdrop has led the researchers to pursue this study. An empirical study was carried out to explore the consumption occasion and the antecedents of online food ordering in the select cities in Karnataka, India. The data was collected from 385 respondents through telephonic and mail survey using a structured questionnaire. The responses were analyzed using exploratory factor analysis and multiple regression. The result of the study indicated a positive association between the constructs ‘buying motives’, ‘aggregator attractiveness’, and customer satisfaction. The variation in customers` satisfaction is largely attributable to the convenience of order placing, food quality, availability of food and restaurant reviews, offers and discounts, faster home delivery, and the wide choice of restaurants listed on the aggregator’s website. Additionally, the aggregator attractiveness showed a higher impact on customer satisfaction as compared to buying motives.