Asia-Pacific Journal of Financial Studies最新文献

An implicit tax is a reduction in the pretax rate of return driven by tax preferences. With increasingly stringent requirements of sustainable development, Chinese government actively promotes environmental protection with the direct corporate income tax rate preferences, which provide a unique opportunity to examine whether implicit taxes remain a significant tax cost in the environmental protection industry. This paper finds the existence of implicit taxes in environmental protection firms and the market structure impedes the realization of implicit taxes. The market power and market concentration reduce the negative effect of tax preferences on the firm's pretax rate of return. The environmental protection firms with lower competition bear lower implicit taxes. These findings are important to evaluate the effectiveness of the tax incentives on environmental protection firms and other tax-favored industries.

Agency theory has shown that multiple large shareholders have competing monitoring and entrenchment governance effects. Therefore, this paper studies the governance effects of multiple large shareholders to determine the dominant effect in the Chinese setting. A panel data model and F-test demonstrate that a significant positive relationship exists between multiple large shareholders and firm performance, but the positive relationship between multiple large shareholders and firm performance will be weakened by state-owned enterprises and politically connected enterprises. Furthermore, our findings suggest that multiple large shareholders can enhance firm performance by mitigating the agent–principal problem and the principal–principal problem. Additionally, a threshold model is introduced to explore the impact of other governance mechanisms on multiple large shareholders' governance, and our findings show that enhancing controlling shareholder governance and board size significantly weakens multiple large shareholders governance, but increasing the proportion of independent directors strengthens the positive relationship between multiple large shareholders and Tobin's Q and weakens the positive relationship between multiple large shareholders and ROA.

As shareholder capitalism has revealed its limitations since the outbreak of Covid-19, there has been a growing demand for a shift toward stakeholder capitalism. Environmental, social, and governance (ESG) management seeks an optimal way to allocate resources to both financial and social values in order to enhance stakeholder utility. Given the various legal, theoretical, and empirical limitations of pluralistic stakeholder capitalism, it is necessary to focus on achieving instrumental stakeholder capitalism. In this regard, we present three roles that finance should play in promoting more firms to adopt ESG management. First, infrastructure needs to be established to measure and assess ESG value in a fair and objective manner. Financial firms should make efforts to develop a non-financial disclosure and certification system, create an ESG index, expand research and investment in this area, and improve credit ratings. Second, there is a need to boost the intermediation of ESG-linked finance in order to enhance utility for firms, investors, and governments. Third, it is crucial to facilitate the trading of ESG value in the market, as this could provide incentives for firms and help them cover the costs associated with ESG investments.

We identify succession as a novel determinant of risk-taking in family firms. We find significantly higher risk-taking (mergers and acquisitions and cash flow volatility) and lower operating efficiency in firms controlled by families with multiple sons during the pre- rather than the postsuccession period compared to family firms with one or no sons. Presuccession risk-taking by sons decreases the following inheritance law amendments that require sharing of wealth among heirs, bolstering the causal interpretation of our findings. An infusion of outside talent via daughters' marriages also alleviates the relative rank-seeking behaviors of sons during succession tournaments.

In this study, we propose a two-step, less-volatile value-at-risk (LVaR) estimation using a generalized nearly isotonic regression (GNIR) model. In the proposed approach, a VaR sequence is first produced under the generalized autoregressive conditional heteroskedasticity (GARCH) framework. Then, the VaR sequence is adjusted by GNIR, and the generated estimate is denoted as LVaR. The results of an empirical investigation show that LVaR outperformed other VaR estimates under the classic equally weighted and exponentially weighted moving-average frameworks. Furthermore, we show not only that LVaR is less volatile, but also that it performed reasonably well in various backtests.

Using data from Singapore, South Korea, and Taiwan, we estimate the coefficient of relative risk aversion (RRA) in the constant relative risk aversion utility specification of the consumption-based capital asset pricing model. Conventional instrumental variables methods find that the coefficient of RRA is low but the inverse of it—the elasticity of intertemporal substitution in consumption—is also low. Such contradictory findings could be attributed to instruments being weak. Using weak-instrument robust tests, we find from the equity market data that the coefficient of RRA is rather high, which could potentially explain the high equity premiums in these three East Asian economies.

In this study, we empirically analyze Chinese firms listed on US exchanges to examine the standalone effects of geographic and market proximity on equity performance. In this regard, we find a negative association between Chinese institutional investors domiciled in the same country where investee firms are incorporated and improved earnings management. However, we find no significant relationship between US institutional ownership and earnings management. Hence, our findings support the geographic rather than the market proximity advantage. Furthermore, the geographic proximity advantage is more substantial in firms with high information opacity, and the results are not altered by choice of earnings management variables.

This paper aims to evaluate the predictive power of financial variables by using various machine learning methods. An analysis is conducted on data for the Korean stock market, which is representative of emerging markets, over 32 years from 1987 to 2018. The study shows that median regression is  a more efficient tool than mean regression in the presence of potential heterogeneity of stocks, significantly improving performance in terms of average realized monthly return. This suggests that median regression can have better predictive performance in emerging markets where there are likely to be outliers. Additionally, a gradient boosting machine (GBM) is found to be better than a traditional linear model both in prediction accuracy and portfolio performance. The hedged return from GBM is on average 2.89% per month with an annualized Sharpe ratio of 0.93 in the median regression. The neural network (NN) is also tested and shown to perform best when the number of hidden layers is two or three. Finally, we evaluatea list of predictor variables with various measures of variable importance. Variables of risk, price trend and liquidity are found to serve as important predictors.

In this study, we investigate whether extreme liquidity risk is priced in the China A-shares market. We find that the market extreme liquidity risk significantly and negatively predicts market returns up to 9 months. In addition, the extreme liquidity risk beta of individual stocks commands a positive monthly premium of 0.75%. Moreover, our findings show that the extreme liquidity risk beta can subsume the tail risk beta in predicting stock returns. Furthermore, our findings show that both the potential selling pressures caused by insiders and by institutional investors significantly and positively influence an individual stock's extreme liquidity risk beta. We also find that the potential selling pressure component of the extreme liquidity risk beta significantly and positively predicts stock returns. Taken together, our evidence demonstrates that a stock's extreme liquidity risk beta provides a channel through which the stock's potential selling pressure caused by both insiders and institutional investors influences its expected return in the China A-shares market.

This study investigates the pricing of liquidity risk in the Korean corporate bond market. We use three different liquidity factors — namely, aggregate market liquidity, liquidity innovation, and predicted liquidity. The empirical results show that, while a liquidity premium exists in the Korean corporate bond market when measured by the market liquidity factor, a liquidity discount occurs when measured by the predicted liquidity factor. Drawing on prior studies, we further describe that the lower (higher) returns for portfolios with a high sensitivity to unexpected liquidity shocks may be attributable to the infrequent (frequent) trading of AAA(A)-rated bonds in the Korean market. Finally, our findings suggest that while a liquidity premium exists in expectation, investors are penalized for taking predicted liquidity risks in the Korean corporate bond market.