Advances in Pacific Basin Business, Economics and Finance: Volume 9

Using initial public offering (IPO) involuntary delisting data, this chapter examines whether and how motivated institutional investors affect the survivability of IPO firms. The empirical evidence shows that the likelihood of future delisting is much lower for IPOs with more motivated institutional investors. This impact is more pronounced for firms with higher information asymmetry. The motivated institutional investors also facilitate better post-IPO operating performance. The results are consistent with the prediction of the limited attention theory.

This study finds evidence that a stock return is inversely correlated with downside risk, confirming a pattern of risk-aversion behavior. Evidence from testing a stock return's response to a change in economic policy uncertainty indicates a significantly negative effect in the Chinese stock market; this conclusion holds true for testing the impacts of changes in fiscal and monetary policy uncertainties. However, the data produce a mixed effect for the change in fiscal policy uncertainty. The evidence produced from examining the geopolitical effect on the stock market strongly supports the presence of an adverse effect on stock market performance.

Deregulation shifts the responsibility for mitigation of agency problems from the regulatory parties to the firms' shareholders. We investigate whether and how governance structure changes in response to the dynamics of the new business environment after the Regulatory Reform Act of 1994 for the US trucking industry. We show that deregulation increases market competition in the trucking industry. The deregulated trucking firms not only adjust internal governance structure but also alter antitakeover provisions to adapt themselves to the competitive status of business environment after deregulation.

This chapter presents evidence of persistence in pricing new corporate bond issues. Both transition matrix and regression analyses show that cross-sectional differences in the yields of initial public bond offerings across issuers persist over time, and the persistence effect is stronger for firms with no rating changes, less frequent bond issuance, and higher information asymmetry. Our findings support the hypothesis of the “ride on past” behavior and confirm the value of information production accumulated from the past bond issuances for the pricing of newly issued bonds.

The main objective of this study is to investigate whether adoption of International Financial Reporting Standards (IFRS) improve the quality of financial reporting in Nigeria. Financial reporting quality was measured in terms of fundamental qualitative characteristics such as relevance and faithful representation and enhancing qualitative characteristics such as understandability, comparability, verifiability, and timeliness as contained in the conceptual framework. The study was conducted on a sample of 162 companies listed on the Nigerian Stock Exchange. A compound measurement tool in form of an index was developed to comprehensively assess the quality of financial reporting based on information disclosed in the financial statement of the selected companies. From both univariate and multivariate analysis, I found strong evidence suggesting that accounting standard used in the preparation of financial statement have significant influence on the quality of financial report of the reporting entity. The result persists for all the three models (overall financial reporting quality, fundamental, and enhancing qualitative characteristics) tested in this analysis. The result also revealed that apart from firm age and firm growth, most of the firm-specific variables investigated have statistically significant influence on the financial reporting quality.

Cyber risk refers to risk affecting information and technology assets of a corporation or government institution. As cyber risk management become important, insurance is one possible solution. However, lack of data and severe information asymmetries increase the difficulties in pricing-related insurance products. In this chapter, we discuss first-party insurance that indemnifies the loss when the insured encounters virus attack and provide pricing model for the policy using copula methodology. Simulation results show that model risk may exist in the distribution of server downtime hours and is minor in the distribution of incident frequency and number of personal computers (PCs) infected.

This chapter examines herd behavior across national borders. A dynamic latent factor model with Gibbs sampling is used to decompose the national herd behavior into the world, regional, and country-specific components. Testing the daily data from 2000 through 2014 for 47 countries, we find that the impact of world factor on national herd behavior is short-lived. This study indicates that world and regional factors play a significant role in explaining the variations of national herd behavior, constituting 33% of the herding variability. The significance of world and regional components is likely to produce a biased herding estimator.

We empirically investigate the forecasting ability of USD-INR exchange rate volatility models by considering Google Trends data. Within a multiple regression framework, we use historical volatility and liquidity measures to build our benchmark volatility model (Chandra & Thenmozhi, 2014). Moreover, we extend Bulut (2018) to incorporate indexes for 15 keywords (price-related, income-related, and liquidity-related) from Google Trends data into our benchmark volatility model to evaluate the forecasting ability of the models. Our results indicate that Google Trends data can improve volatility prediction and that among the groups of keywords that we consider, the price-related keywords have the best forecasting ability. Incorporating data on searches for “prices” into the model produces the highest reduction in the forecasting error: a 22.75% decrease compared to the level in the benchmark model. Hence, these empirical findings indicate that Google Trends data contain information that influences exchange rate movements.

This study proposes a theoretical model for measuring the greenness factors of a firm. We develop the multifactor utility function and find that the proportion of investment in green bonds is higher if greenness factors account for by a firm and vice versa. Moreover, we further develop the global aspects of greenness measures which identify how much level of greenness is maintained by a firm to make the environment green. In terms of reduction in emissions based on global measures, we report that the proportion of investment in green bonds is higher. This study argues that the difference between firm-related and global measures of greenness refers to distortion in portfolio allocation. Lastly, we compare the results of five Asian countries and report that Japanese firms are appropriately following the greenness measures while the firms operating in developing countries including Indonesia, Malaysia, Pakistan, and Thailand are far behind in implementing the greenness measures.

This chapter introduces a risk control framework on credit card fraud instead of providing a solely binary classifier model. The anomaly detection approach is adopted to identify fraud events as the outliers of the reconstruction error of a trained autoencoder (AE). The trained AE shows fitness and robustness on the normal transactions and heterogeneous behavior on fraud activities. The cost of false-positive normal transactions is controlled, and the loss of false-negative frauds can be evaluated by the thresholds from the percentiles of reconstruction error of trained AE on normal transactions. To align the risk assessment of the economic and financial situation, the risk manager can adjust the threshold to meet the risk control requirements. Using the 95th percentile as the threshold, the rate of wrongly detecting normal transactions is controlled at 5% and the true positive rate is 86%. For the 99th percentile threshold, the well-controlled false positive rate is around 1% and 83% for the truly detecting fraud activities. The performance of a false positive rate and the true positive rate is competitive with other supervised learning algorithms.

This study investigates the relationship between the inflation targeting (IT) framework and the exchange rate pass-through (ERPT) to consumer prices in the emerging ASEAN economies (i.e., Indonesia, the Philippines, and Thailand) using a vector autoregressive (VAR) model with monthly data covering the sample period from January 1990 to July 2020. The empirical analysis is divided into two subperiods – pre-IT and post-IT periods. The impulse response analysis identified the existence of the ERPT during the pre-IT period and the loss of the ERPT during the post-IT period in all sample economies. The study speculated that the loss of the ERPT is attributable to the conformity to the Taylor principle in the IT framework in all sample economies.

This study takes advantage of abundant data from the Economics Department at National Tsing Hua University to empirically evaluate whether there exist academic performance differentials between undergraduate students from two entrance channels (exam-based and application-based methods) across courses and grades. We first evaluate the academic performance between the students based on two entrance channels, and then incorporate the General Scholastic Ability Test (GSAT) score (including five subjects of Chinese Literature, Mathematics, English, Science, and Society) into the independent variables to control for the students' ability. Our empirical results exhibit the students recruited through the application-based method outperform those admitted from the exam-based method in required courses after controlling for the students' individual characteristics. Nevertheless, we found that the advantage disappears for the elective courses. Furthermore, the academic gaps between the two groups of students tend to decline or disappear when students are seniors. The findings indicate that entrance exam scores (e.g., the Scholastic Assessment Test (SAT) scores in the United States) are good indicators for predict college academic performance, making the potential function of entrance exam in Taiwan relatively comparable to that in the United States. The findings also detail that individual GSAT scores on English, Math, and Society are positively and significantly associated with his/her performance on the core courses in Economics, supporting a significant learning progression from the curricula of senior high school to the undergraduate college education.