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This paper aims to investigate whether the cyclicality of local real estate prices affects the systematic risk of local firms using a geography-based measure of land availability as a quasi-exogenous proxy for real estate price cyclicality.

This paper uses the geography-based land availability measure as a proxy for the procyclicality of real estate prices and the location of a firm’s headquarters as a proxy for the location of its real estate assets. Four-factor asset pricing model (market, size, value and momentum factors) is used to examine whether firms headquartered in more land-constrained metropolitan statistical areas have higher systematic risks.

The results show that real estate prices are more procyclical in areas with lower land availability and firms headquartered in these areas have higher systematic risk. This effect is more pronounced for firms with higher real estate holdings as a ratio of their tangible assets. Moreover, there are no abnormal returns to trading strategies based on land availability, consistent with stock market betas reflecting this local real estate factor.

This paper contributes to the literature on local asset pricing factors, the collateral role of firms’ real estate holdings and the co-movement of security prices of geographically close firms.

This paper has important managerial implications by showing that, when firms decide on the location of their buildings (e.g. headquarters building, manufacturing plant and retail outlet), the location’s influence on systematic risk should be part of the decision-making process.

This paper is among the first to use a geography-based measure of land availability to study whether the procyclicality of local real estate prices influences firm risk independent of the procyclicality of the local economy. Thus, both the portfolio formed and firm-level analyses provide a more direct evidence of the positive relation between the procyclicality of local real estate prices and firm risk.

The economic crisis of 2007–2009 had a major negative impact on financial institutions in general. Health and life insurance industry continues to face growth challenges even six years after the economic crisis. Due to the challenges faced by health and life insurance industry, several companies in this industry have merged and some decided to get out of this business altogether. This study benchmarks 10 life and health insurance companies on the basis of return on equity, investment yield, and loss ratio for the year 2009 and 2014.

The study aims to use individuals using the internet and fixed broadband subscriptions as a proxy for digitalization to empirically assess the effects of Foreign Direct Investment (FDI), digitalization and their interaction on income inequality in developed and developing countries from 2002 to 2019.

The paper used the system general method of moments estimators for 30 developed and 35 developing countries.

FDI increases income inequality in developed countries but decreases it in developing countries, digitalization reduces income inequality in both groups and interaction term narrows income inequality in developed countries but widens it in developing countries.

The paper is the first to introduce digitalization into the FDI – income inequality relationship. Furthermore, it provides empirical evidence to show the difference in the role of digitalization in this relationship between developed and developing countries.

The change of production methods, the industrial revolutions, technological developments, and digital transformation have affected almost all functions in the enterprises. Accounting and auditing areas are also quite affected by this transformation. Another important result of technology and digitalization is the rapid increase in errors, frauds, and irregularities. Enterprises are looking for new solutions and investigations against irregularities and frauds. Audits for errors, frauds, or irregularities are among the interests of forensic accounting. Many methods are used to identify errors and frauds in the forensic accounting. However, it is inevitable that digital technologies should be utilized in forensic accounting applications as a result of the rapid spread of automation and computer programs in enterprises within the framework of digitalized business activities. Hence, enterprises will be able to get more effective results through computer programs and artificial intelligence in terms of fraud audit in forensic accounting. Expert system applications use artificial intelligence to enable computer programs to behave just like people. One of the most widely used, most easily applicable, and most understandable types of expert system is rule-based expert system. The aim of this study is to determine the accounting fraud that may occur in enterprises within the framework of forensic accounting through rule-based expert systems. For this purpose, various applications have been implemented in a large-scale production enterprise through the use of rule-based expert systems for the determination of accounting fraud. Benford’s Law, risk levels, and various other criteria were used in the creation of expert systems. According to the results obtained from the study, it has been seen that by means of rule-based expert system applications, enterprises can better detect existing frauds and prevent further irregularities in the future. The study is important and it is expected that the study will contribute to the literature because it is shown in the study that the rule-based expert systems, applied in many fields under the title of social sciences, can also be applied in the field of forensic accounting and auditing.

As cable and satellite industry undergoes transformation in the 21st century with the onslaught of innovation-driven changes, it is important to know which company is doing better and which company is falling behind. This study compares the relative performance of eight cable companies using three factors: operating expense for every dollar of operating revenue, earnings before interest, taxes, depreciation, and amortization, and return on assets. We also evaluate the performance of each firm against itself for the period 2010–2013 to see if they show improvement or deterioration in operating efficiency.

Healthcare industry, the largest sector of the US economy, is going through a dramatic transformation as the US economy recovers out of the current recession. In this chapter, we use data envelopment analysis, an operations research technique, to benchmark the performance of 12 publicly managed care organizations against one another for the period 2009–2011. We find that only 6 companies out of 12 are 100% efficient. We also identify the areas in which inefficient companies are lagging behind their efficient peers.

The purpose of this paper is to investigate whether real estate investment trusts (REITs) have any significant cost-efficiency advantages over real estate operating companies (REOCs).

The data for listed companies were extracted from the Bloomberg terminal. The authors analyzed financial ratios and conducted a non-parametric data envelope analysis (DEA) for 534 firms in the USA, Canada and some EU member states.

The results suggest that REITs were much more cost-efficient than REOCs by all the parameters in the DEA model during the entire three-year period under consideration. Although the debt-to-equity levels were similar, REOCs were more relying on short-term than long-term maturities, which made them more vulnerable against market corrections or shocks. Being larger in asset size did not necessarily guarantee greater economies of scale. Both – the cases of increasing economies of scale and diseconomies – were detected. The time period 2015–2017 showed the general trend of decreasing efficiency.

Very few papers on the topic of REITs have attempted to find out whether a different firm structure displays any differences in efficiency. Because the question of REITs and sustainable growth of the real estate market has become a prominent issue, this research can help EU countries to consider the option of adopting a REIT system. If this system were successfully implemented, the EU member states could benefit from a more sustainable and more rapid growth of their real estate markets.

We examine whether loan securitization has an impact on bank efficiency. Using a sample of large US commercial banks from 2002 to 2012, we find that bank loan securitization has a significant and positive impact on bank efficiency, and this relationship is stronger for banks with higher capital ratios, higher default risk, and lower level of liquidity and diversification. Our results are robust to Heckman self-selection correction and difference-in-difference (DID) analysis. In addition, these results are found mainly in non-mortgage loan securitizations but not in mortgage loan securitizations. Finally, we show that loan sales also have a positive impact on bank efficiency.

Purpose: Investors and portfolio managers can earn profitably when they correctly predict when stock prices will go up or down. For this reason, it is crucial to know the effect levels of the factors that affect stock prices. In addition to macroeconomic factors, the psychological behavior of investors also affects stock prices. Therefore, the study aims to reveal the different sensitivity levels of the stock index against macroeconomic and psychological factors.

Design/Methodology/Approach: In this study, dollar rate (USD), euro rate (EURO), time deposit interest rate (IR), gold price (GOLD), industrial production index (IPI), and consumer price index (CPI) (inflation (INF)) were used as macroeconomic factors, while Consumer Confidence Index (CCI) and VIX Fear Index (VIX) were used as psychological factors. In addition, the BIST-100 index, which is listed in Borsa Istanbul, was used as the stock index. The sensitivity of the stock index to macroeconomic and psychological factors was investigated using the Multivariate Adaptive Regression Spline (MARS) method using data from January 2012 to October 2020.

Findings: In the analyses performed using the MARS method, the coefficients of INF, USD, EURO, IR, CCI, and VIX Index were found to be statistically significant and effective on the stock index. Among these variables, INF has the highest effect on stocks. It is followed by USD, IR, EURO, CCI, and VIX. GOLD and IPI variables did not show statistical significance in the model. The most important difference of the MARS model from other regressions is that each factor’s effect on the stock index is analyzed by separating it according to the value of the factor. According to the results obtained from the MARS model: (1) it has been determined that USD, EURO, IR, and CPI have both positive and negative effects on the stock market index and (2) CCI and VIX have been found to have negative effects on stocks. These results provide essential information about how investors who plan to invest in the stock index should take into consideration different macroeconomic and psychological values.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the effects of factors affecting the stock index by decomposing it according to the values it takes. Also, this study provides additional information by listing the factors affecting the stock index in order of importance. These results will help investors, portfolio managers, company executives, and policy-makers understand the stock markets.

In this chapter, we evaluate the dollar amount spent on advertising relative to sales, profit margin, and growth rates to study the effectiveness of advertising in today’s retail environment, and whether it leads directly to higher sales and increased profits affording positive earnings for the investor. The study illustrates the use of data envelopment analysis (DEA) technique to benchmark 16 apparel firms to evaluate the effectiveness of their advertising dollars on the sales, profit margin, growth, return on assets (ROA), return on equity (ROE), and return on investment (ROI).