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The purpose of this paper is to examine the ability of hedge funds and funds of hedge funds to generate absolute returns using fund level data.

The absolute return profiles are identified using properties of the empirical distributions of fund returns. The authors use both Bayesian multinomial probit and frequentist multinomial logit regressions to examine the relationship between the return profiles and fund characteristics.

Some evidence is found that only some hedge funds strategies, but not all of them, demonstrate higher tendency to produce absolute returns. Also identified are some investment provisions and fund characteristics that can influence the chance of generating absolute returns. Finally, no evidence was found for performance persistence in terms of absolute returns for hedge funds but some limited evidence for funds of funds.

This paper is the first attempt to examine the hedge fund return profiles based on the notion of absolute return in great details. Investors and managers of funds of funds can utilize the identification method in this paper to evaluate the performance of their interested hedge funds from a new angle.

Using the properties of the empirical distribution of the hedge fund returns to classify them into different absolute return profiles is the unique contribution of this paper. The application of the multinomial probit and multinomial logit models in the fund performance and fund characteristics literature is also new since the dependent variable in the authors' regressions is multinomial.

The purpose of this paper is to examine the factors influencing Indonesian farmers’ use of the warehouse receipt system (WRS) and their choice of private and public warehouses.

Primary data were collected through questionnaires administered to 500 farmers in two districts, Subang and Cianjur, in West Java Province in Indonesia. Binary logit regression was employed to examine the factors influencing farmers’ use of the WRS. Binary and bivariate probit regressions were employed to determine the factors influencing farmers’ choice of private and public warehouses.

The empirical results of the binary logit regression revealed that age, land ownership, selling price, the use of the warehouse receipt as collateral security and the availability of transportation facility positively influenced farmers’ use of the WRS, whereas education, income, farm profit and participation in farmers’ group negatively influenced farmers’ use of the WRS. The results of the binary probit regressions revealed that profit, availability of insurance and processing facility positively influenced the farmers’ decision to use the private WRS, whereas education, production, selling price and distance from the farm to the warehouse negatively influenced farmers’ decision to use the private WRS. Age, education, selling price and distance from the farm to the warehouse positively influenced the farmers’ decision to use the public WRS, whereas production and availability of processing facility negatively influenced the decision of farmers to use the public WRS.

This study highlights the importance of education and government assistance regarding the provision of facilities and price indemnified insurance for successful implementation of the WRS.

This study provides an empirical contribution to the existing literature on the development of WRS in Indonesia. In terms of methods of analysis, previous studies used purely qualitative and descriptive methods, whereas this study employed econometric techniques (i.e. binary logit, binary probit and bivariate probit regressions) to examine the WRS in Indonesia. In addition, whereas previous studies explored the WRS in general, this study investigated the farmers’ use of the public and private warehouses in addition to exploring the WRS in general. Finally, the finding that the average annual profit of non-users was significantly higher than that of the users of the WRS is striking, and this could be attributed to the current challenges of the implementation of the WRS, including high transportation and warehouse rental costs.

Online shopping is expected to continue without slowing down because of the advantages that it presents to consumers in the digitalising world. This study aims to determine the factors regarding the social and environmental indicators and the demographical and economical factors that affect the online shopping tendencies of households in Turkey. The results of this research can be used to review the online shopping strategies by the decision-makers.

In this study, the cross-sectional data acquired from the Household Budget Research survey, which has been conducted by the Turkish Statistical Institute between 2015 and 2018, is used. In this data set consisting of 11,491 in 2015, 12,096 in 2016, 12,166 in 2017 and 11,828 in 2018, a total of 47,581 data from the households that are 15-year-old and older are used. To determine the factors affecting the online shopping behaviour of households, binary logistic regression and binary probit regression analyses are applied. As a result of these analyses, it has been decided that the most suitable model is the binary probit regression model.

According to the analysis results, it has been detected that factors such as educational status, age, marital status, employment status, income, life assurance ownership, credit card usage, automobile ownership and the year of the survey affect the online shopping behaviour of households.

In this study, factors affecting the tendency to do online shopping, which has gained big importance particularly with the COVID-19 pandemic, are determined. In Turkey, households’ tendency to do online shopping is affected by the demographical and economical factors and by the factors related to the social and environmental indicators. Determination of the effects of these factors has been a guide for the decision-makers and policymakers in explaining the tendency to shop online and creating a competitive advantage.

In this study, data consisting of a total of 47,581 observations, which has acquired from the Household Budget Research survey conducted by the Turkish Statistical Institute between 2015 and 2018, are used by applying a weighting process, and no study that is as comprehensive and inclusive as this study has been found in the literature, e-commerce that has become prevalent with the help of technological progress and changing habits in the past years is continuing to become prevalent more increasingly particularly after COVID-19 pandemic. Therefore, the value of this study underlies its contribution to e-commerce awareness.

The purpose of this paper is to propose predictive models of speculative revaluation attacks, which would facilitate currency risk hedging in emerging and developed countries.

The purpose of this paper is achieved using the methodology of multiple triangulation. Paper combines different theoretical perspectives (three generations of speculative attack models), two sources of data (emerging countries and developed countries) and three methods (logit regression, probit regression and artificial neural networks, ANN) for identification of leading indicators and forecasting of speculative attacks. Combination of multiple observations (data), underlying theories and methods allowed achieving least biased results.

A list of leading indicators of speculative revaluation attacks was generated based on previous researches and three generations of speculative attacks' models. Qualitative and quantitative differences of speculative revaluation attacks in emerging and developed countries were identified. The decision matrix of currency risk hedging in the context of speculative devaluation and revaluation attacks was proposed.

Although the sample of this researcher includes a wide range of countries (65 in total), their separation into developed and emerging countries is arbitrary (in the course of 35 years some countries have changed the status from emerging towards developed). The initial list of leading indicators is limited, includes mostly economic variables. It could be improved by encompassing political variables, credit ratings, consumer and business confidence indices.

Developed predictive models of speculative revaluation attacks may significantly reduce important element of risk – uncertainty – and, consequently, the cost of financial hedging.

This paper is one of the first public attempts to apply alternative methodology of ANN for forecasting speculative attacks. The results showed that latter method is more accurate than probit and logit regressions. Also, to the author's best knowledge, this is a first public attempt to separately analyse the phenomenon of speculative revaluation attacks.

The purpose of this study is to examine the effect of corporate social responsibility assurance practice (CSRAP) on the financial distress likelihood of listed firms in India. It uses the signalling theory to interpret the relationship among the variables of the study.

The study used the Indian stock market as the testing grounds and applied probit and panel probit regression to examine the data set with 800 firm-year observations from 2010 to 2019.

The study’s first findings show that firms with an assurance service have a negative correlation and are less likely to stay in financial distress situations for an extended period. However, corporate social responsibility (CSR) assurance has a positive but weak correlation with insignificance with financial distress likelihood of firms in India. The authors also find that the engagement of CSR assurance and level of assurance (limited assurance) does not cause a change in a firm financially distress likelihood of firms in India. However, as assurance service providers, auditing firms are more likely to reduce a firm’s likelihood of financial distress. Finally, the study shows that CSRAP (CSR assurance, assurance service providers and level of assurance) does not moderate the association between CSR expenditure and financial distress likelihood of listed firms in India.

The study findings are the first to examine the level of assurance and financial distress of firms according to the authors’ knowledge. This study also adds new knowledge to the factors that cause or reduces the financial distress of listed firms, including CSRAPs.

The purpose of this paper is to examine whether surge in foreign direct investment (FDI) inflows leads to surge in economic growth in 52 developing countries for the period 1990-2014.

The author used a threshold approach to identify surge incidences in gross domestic product (GDP) per capita growth rates and FDI inflows (measured as percentage of GDP) for each country included in the sample. Three different criteria are used to identify surge instances. As a preliminary analysis the author used the probit and complementary log–log regression methods to estimate the likelihood of growth surge occurrence. To correct the potential endogeneity problem the author jointly estimated the growth surge and FDI surge equations using the recursive bivariate probit (RBP) regression.

The author found that East Asia and the Pacific region has highest rate of growth surge incidences followed by South Asia. The results suggest that surge in FDI inflows significantly increases the likelihood of growth surge. The finding is robust to alternative surge definitions and methods of estimation.

The analysis reveals that inbound FDI flow is a critical driver of economic growth in developing countries. Large FDI inflows matters for achieving rapid economic growth. Therefore developing countries should adopt favourable policies to attract more FDI. Policymakers should focus on improving the investment climate of the country to boost domestic investment and to attract larger amount of FDI into the economy.

To the best of the author’s knowledge this is the first study to examine whether surge in FDI inflows stimulates surge in economic growth in developing countries. The analysis reveals that FDI surge is a robust predictor of rapid economic growth in developing countries.

This paper aims to assess the choice of supermarkets for purchasing fresh agricultural products among urban consumers in Ghana.

Likert scale was used to investigate reasons for purchasing agricultural products from supermarkets, while heteroskedastic probit was used to estimate the determinants. Beta regression was used to examine the determinants of the proportion of food expenditure on raw/unprocessed agricultural products.

The principal reasons for purchasing agricultural products from supermarkets are convenience, a guarantee of assorted products, high-quality products and food safety, constant supply of products, conducive shopping environment, excellent customer service and social influence. The probability of purchasing agricultural products from supermarkets is high for consumers who are either males, young, educated, high-income earners or salaried workers. Consumers residing closer to supermarkets have a greater probability of shopping for agricultural products from same. The proportion of food expenditure on unprocessed agricultural products increases with age but decreases with education and distance to local markets.

Few prior studies have investigated supermarket’s surge in developing countries and its connection with consumer food-outlet choice. Unfortunately, little is evident in the extant literature on consumers' choice of supermarkets as purchasing outlets for fresh agricultural products. Hence, this study closes the gap on consumers and fresh agricultural product purchases from supermarkets in Ghana. Results from the study will provide grounding evidence to supermarket owners to adjust their services to meet consumers’ needs and provide relevant information to evolving supermarkets or investors who may venture into the supermarket business on the attributes that influence consumers to use supermarkets as a purchasing outlet.

This study aims to investigate the effect of high insider ownership on firms’ internal controls over financial reporting. In particular, it examines how high insider ownership affects the likelihood of an adverse Sarbanes–Oxley Act Section (SOX Section 404) opinion and its subsequent remediation.

Tests of hypotheses use ineffective controls and remediation models. The initial tests in this study use ineffective internal controls over financial reporting probit regression models to investigate how high insider ownership affects the ex-post likelihood of an adverse 404 opinion. Two remediation models – a multinominal probit regression and probit regression model – are used to investigate the effect of high insider ownership on the likelihood of successfully remediating an adverse 404 opinion.

Results show that while the ex-ante likelihood of an adverse SOX Section 404 auditor’s internal control opinion increases with high insider ownership, high insider ownership firms are more likely to remediate ineffective 404 controls. This study rationalizes these diverse findings by asserting that prior to an adverse 404 opinion, entrenched managers avoid internal control financial reporting oversight and monitoring. After an adverse opinion, however, and within the context of an imminent and explicit value reducing 404 opinion, powerful high insider owner managers are motivated to remedy ineffective controls.

This research synthesizes existing streams of literature on insider ownership and the effectiveness of internal control over financial reporting quality to provide new information on the effects of high insider ownership on firms’ internal controls.

This chapter identifies three crisis warning indicators driven from trading in emerging markets’ carry trades, and empirically examines whether these indicators could predict two major financial crises that hit the global financial markets in the last decades — The 1997–1998 Asian crisis and the 2007–2008 global crisis. The probit regression is used to examine the power of the three indicators in forecasting financial crises, using data from eight Asian emerging countries which serve as proxies for emerging markets, independent of the origination of the crisis. I use both fixed effect and random effect estimation to measure crisis impacts. The empirical results show that financial crises could have been predicted. Probit estimation show that carry trade returns can predict a financial crisis, and the estimation results are robust to both panel level and country-level analysis. These three indicators are by no means an exhaustive list of all possible predictors of financial crisis. The literature suggests other fundamental indicators of financial crises such as the current account deficit and foreign debt. However, this chapter cannot fully consider these indicators for lack of data at this point in time. Although financial crisis may be better predicted by the well-known fundamental indicators, the contribution of this chapter is simply that carry trade-related indicators can help in predicting crises.

This paper aims to examine how different types of corporate political connections (PCs) affect auditor choice decisions (and, therefore, audit quality) and audit opinions following the 2013 Egyptian uprising.

This paper utilizes a unique hand-collected dataset on the type of PCs of Egyptian listed companies from 2014 to 2019. Several analyses are employed to test the hypotheses, including logit regression, probit regression and generalized linear mixed models (GLMM). A number of additional analyses are conducted to ensure the robustness of the results, including the instrumental variables (IVs) probit models and propensity score matching (PSM).

The results show that firms' choice of auditor and audit opinion is heavily influenced by firms' PCs. Companies with PCs through boards of directors and major shareholders hire Big 4 audit firms to enhance corporate legitimacy; however, government-linked companies usually retain non-Big 4 audit firms to avoid increased transparency and to conceal improper activities, including tunneling and rent-seeking. Further, the results indicate that companies with PCs through boards of directors or major shareholders are more likely to receive favorable audit opinions, whereas government-owned businesses are less likely to receive such opinions.

This study provides additional evidence to policymakers that binding regulations and guidelines are necessary to oversee politically connected firms (PCFs) and to enhance governance and investor protection.

This study provides the first empirical evidence on how corporate PCs influence the choice of auditors and the opinions of audit firms in Egypt. This paper also sheds light on the impact of different types of corporate PCs on the choice of auditors and audit opinions.