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The Chinese fund market has witnessed significant developments in recent years. However, although there has been a range of studies assessing fund performance in developed industries, the rapidly developing fund industry in China has received very little attention. This study aims to examine the performance of open-end securities investment funds investing in Chinese domestic equity during the period May 2003 to September 2020. Specifically, applying a non-parametric bootstrap methodology from the literature on fund performance, the authors investigate the role of skill versus luck in this rapidly evolving investment funds industry.

This study evaluates the performance of Chinese equity securities investment funds from 2003–2020 using a bootstrap methodology to distinguish skill from luck in performance. The authors consider unconditional and conditional performance models.

The bootstrap methodology incorporates non-normality in the idiosyncratic risk of fund returns, which is a major drawback in “conventional” performance statistics. The evidence does not support the existence of “genuine” skilled fund managers. In addition, it indicates that poor performance is mainly attributable to bad stock picking skills.

The authors find that the top-ranked funds with positive abnormal performance are attributed to “good luck” not “good skill” while the negative abnormal performance of bottom funds is mainly due to “bad skill.” Therefore, sensible advice for most Chinese equity investors would be against trying to “pick winners funds” among Chinese securities investment funds but it would be recommended to avoid holding “losers.” At the present time, investors should consider other types of funds, such as index/tracker funds with lower transactions. In addition, less risk-averse investors may consider Chinese hedge funds [Zhao (2012)] or exchange-traded fund [Han (2012)].

The paper makes several contributions to the literature. First, the authors examine a wide range (over 50) of risk-adjusted performance models, which account for both unconditional and conditional risk factors. The authors also control for the profitability and investment risks in Fama and French (2015). Second, the authors select the “best-fit” model across all risk-adjusted models examined and a single “best-fit” model from each of the three classes. Therefore, the bootstrap analysis, which is mainly based on the selected best-fit models, is more precise and robust. Third, the authors reduce the possibility that findings may be sample-period specific or may be a survivor (upward) biased. Fourth, the authors consider further analysis based on sub-periods and compare fund performance in different market conditions to provide more implications to investors and practitioners. Fifth, the authors carry out extensive robustness checks and show that the findings are robust in relation to different minimum fund histories and serial correlation and heteroscedasticity adjustments. Sixth, the authors use higher frequency weekly data to improve statistical estimation.

Productivity and production risks affect the use of agricultural production practices and inputs, particularly in developing countries. This paper aims to investigate the effects of adopting drought-tolerant maize varieties (DTMVs) on farm productivity, yield variance and downside risk exposure of maize growing households of Zambia.

The study uses household survey data collected from 11 maize producing districts of Eastern, Southern and Copperbelt provinces of Zambia using a structured questionnaire. The Antle’s flexible moment-based approach was used in specifying, estimating and testing a stochastic production function. The study further applied an endogenous switching regression model to control for both observable and unobservable sources of bias.

The study revealed that DTMV adoption increases maize yield by 15 per cent and reduces the risk of crop failure: reducing yield variance by 38 per cent and exposure to downside risk by 36 per cent.

This study establishes the benefits of DTMV adoption in Zambia with regards to productivity, yield stability and downside risk in the face of climate change. Results from this study underscore the need for more concerted efforts to scale-out DTMVs for both maize productivity enhancement and for risk mitigation against weather shocks.

Some controversial cases of bail-in in the emerging countries have raised the question about whether for those countries to have in place a regulation for the bail-in is appropriate or not. To assess appropriateness, this paper investigates bail-in credibility among investors, as crucial condition for the credibility’s smooth implementation, by measuring the yield spread between bailinable and non-bailinable bonds.

The authors compare the yield spread of banks located in emerging countries that have in place a framework for the bail-in to the comparable yield spread measured for banks located in emerging countries without such framework. The comparison permits to detect whether there is a significant difference between the two spreads, which would suggest that bail-in regulation has been deemed credible by market participants where enforced, or not, which in this case would signal a problem of credibility.

The authors' results point out a significantly higher yield spread for banks located in emerging countries that have adopted a framework for the bail-in of creditors. Bail-in regulation has, therefore, being deemed credible in the adopting emerging countries, thus ensuring a crucial condition for bail-in regulation's smooth application. The authors also point out bank size and country's gross domestic product (GDP) growth as crucial moderators of bail-in expectations of market participants that can guide the implementation of bail-in rules in emerging countries.

This paper contributes to the literature on the credibility of bail-in with a new perspective from the emerging countries.

Insurance companies exist to manage the risk of others, which is why they are perceived to be competitive in risk management (RM). Considering this, we investigate how different RM capabilities make insurers effective in RM. These capabilities include understanding risk and risk management (URRM), risk identification (RI), risk assessment and analysis (RAA) and risk monitoring (RMON) activities in insurance companies. In addition, the authors probe how these capabilities can jointly yield a competitive advantage for the insurance industry under the resource-based view (RBV) and dynamic capabilities perspective (DCP).

The authors present a latent variable RM model for the insurance industry and employ structural equation modeling (SEM) to test the hypotheses. Furthermore, the authors also conduct confirmatory factor analysis (CFA) and convergent and discriminant validity analysis for model fit and invariance testing, respectively.

The results show that insurers who investigated RM-related capabilities directly influence their risk management practices (RMPs). Moreover, improving these capabilities will make insurers more effective in managing the risks of others. Thus, RM as a business process will yield a competitive advantage for the insurance sector. The findings are supported by the theoretical insights presented by the RBV and DCP. Furthermore, the model also adheres to the convergent and discriminant validity cut-off values.

To the best of the authors’ knowledge, this is the first study examining insurers' RM practices as a source of a competitive advantage.

保險公司存在的目的是為其它公司或個人管理其風險；因此，保險公司在風險管理方面、被認為具有競爭能力。故此、我們擬研究不同的風險管理能力是如何能使保險公司有效地管理風險的呢？這些風險管理能力包括對風險及風險管理之了解、風險辨識、風險評估和分析，以及在保險公司內的風險監控活動。再者，我們探究這些風險管理能力如何根據資源基礎觀點及動態能力理論共同為保險業創造競爭優勢。

我們為保險業展示一個潛在變項風險管理模型，並使用結構方程模型，來測試我們的假設；而且，我們為模型適配度而進行了驗證性因素分析，又為不變性檢定而進行了驗證輻合及驗證區別效度分析。

研究結果顯示、若保險公司審査與風險管理相關之能力，這會直接影響其對風險管理之措施；而且，若保險公司能改善其風險管理之能力，這會使它們更有效地管理其它公司或個人的風險。因此，作為業務過程的一環、風險管理會為保險業創造競爭優勢。我們的研究結果，得到資源基礎理論及動態能力理論提供之理論見解所支持；而且，我們的模型從附驗證輻合及驗證區別效度的截止值。

據我們所知，本研究為首個研究、去探討保險公司的風險管理措施如何為它們創造競爭優勢。

Most of the major Islamic countries’ stock exchanges have not been able to perform at the same pace with the major emerging countries’ stock exchanges since the mid of 1990s. The purpose of this paper is to examine the implications of stock market liberalization on cost of capital as one of the crucial driver to stock market development and physical investment growth in emerging Islamic countries.

This study employs static panel data techniques on the sample of seven emerging Islamic countries over the years 1989-2008.

The findings of this study suggest that stock market liberalization significantly reduces cost of capital in the stock markets of sample Islamic countries, which carries policy-oriented implications. Reduction in the cost of capital increases the number of exchange-traded companies, profitability of projects and aggregate investment level; therefore, the study findings are highly concerned by the economic policymakers, corporations and investors alike.

In the literature, different proxies are employed to measure stock market liberalization and cost of capital as well. Due to data limitations, this study could not employ different proxies for both, especially for stock market liberalization, for robustness purpose. That limitation further restricted the coverage of Islamic stock markets and time period. Therefore, generalization of the study results for overall Islamic stock markets can be slightly drawn.

The paper provides further understanding regarding the effects of SML on cost of capital, thereby indirectly on the stock market development, in the context of EIC.

Poverty transitions can be explained by two opposing theories: the traditional sociological approach that focusses on social stratification and individualisation theory, which emphasises on life course risks for all strata. Both perspectives have been investigated extensively for income poverty while neglecting other important poverty indicators, such as deprivation or the receipt of social assistance. The purpose of this paper is to focus on the latter to investigate the impact of social stratification (e.g. social class), life course risks (e.g. health problems), and their interactions on the probability of social assistance entry for Germany.

The analysis utilises survey data containing a sample of first-time social assistance entrants and a sample of the residential population. Applying case-control methodology, logistic regression is conducted to model the impact of social stratification determinants, life course risks, and their interactions on the probability of social assistance entry.

Social stratification determinants, particularly social class, have a significant effect. However, their effect is weaker than the effect of life course risks. Contrary to the prediction of individualisation theory, the poverty-triggering impact of life course risks varies substantially by social stratum. The combination of both theories yields high predictive power.

This paper is the first to comprehensively test social stratification and individualisation theory with respect to social assistance receipt as a poverty indicator. It is the first paper that investigates the entire population at risk of social assistance entry in Germany.

The dividend month premium is the phenomenon that firms have abnormal returns in predicted dividend month. This study aims to examine the dividend month premium in the Korean stock market, using common stocks listed on the KOSPI and KOSDAQ from January 1999 to December 2016. Abnormal returns are estimated using the following asset price models: capital asset pricing model, Fama–French three-factor model and the Fama–French–Carhart four-factor model. This study finds positive abnormal returns in predicted dividend months, and even for the within-firm portfolio that buys stocks in the predicted dividend months and sells the same stocks in other months. The price impact and the subsequent reversals are greater with lower liquidity and higher dividend yield, implying that the price pressure from dividend-seeking investors affects this dividend month premium. In addition, the anomalies with the pre-declaration stock are smaller than the post-declaration stock, suggesting the necessity to improve the cash dividend policy of post-declaration for market efficiency.

Although it has often been studied in finance research, the relationship between dividend yields and stock returns remains an unresolved issue, especially in the Korean stock market. When firms continue to pay non-decreasing dividends for three or five years, they may establish a dividend reputation, which could affect this relationship. The author found firms that pay more dividends, larger firms, older firms, more profitable firms, less leveraged firms, firms with less volatile returns, firms with foreign holdings of more than 5%, and firms with more concentrated ownership build dividend reputations. The author also found that the relationship between dividend yields and future stock returns depends on a firm’s dividend reputation. The evidence shows that when firms with higher yields have dividend reputations, they produce higher future returns, whereas there is no significant relationship between yields and returns for firms with no reputation. These results are inconsistent with the findings of studies that use developed market data. In addition, when larger firms with higher growth potential and firms with less concentrated ownership have dividend reputations, future returns are higher.

The credit ratings issued by the Big 3 ratings agencies are inaccurate and slow to respond to market changes. This paper aims to develop a rigorous, transparent and robust credit assessment and rating scheme for sovereigns.

This paper develops a regression-based model using credit default swap (CDS) data, and data on financial and macroeconomic variables to estimate sovereign CDS spreads. Using these spreads, the default probabilities of sovereigns can be estimated. The new ratings scheme is then used in conjunction with these default probabilities to assign credit ratings to sovereigns.

The developed model accurately estimates CDS spreads (based on RMSE values). Credit ratings issued retrospectively using the new scheme reflect reality better.

This paper reveals that both macroeconomic and financial factors affect both systemic and idiosyncratic risks for sovereigns.

The developed credit assessment and ratings scheme can be used to evaluate the creditworthiness of sovereigns and subsequently assign robust credit ratings.

The transparency and rigor of the new scheme will result in better and trustworthy indications of a sovereign’s financial health. Investors and monetary authorities can make better informed decisions. The episodes that occurred during the debt crisis could be avoided.

This paper uses both financial and macroeconomic data to estimate CDS spreads and demonstrates that both financial and macroeconomic factors affect sovereign systemic and idiosyncratic risk. The proposed credit assessment and ratings schemes could supplement or potentially replace the credit ratings issued by the Big 3 ratings agencies.

This paper aims to understand the significant farm and market-level factors that incentivize the adoption and marketing of pulses influencing its supply response to changing demand.

The authors first use a modified Nerlovian supply response model using secondary data to identify the major price and non-price factors influencing the supply of pigeon pea, black and green gram in the major pulses growing states in India. Second, using primary qualitative data the authors map the pulses value chain from farm to retail to identify the how proportional and fixed transaction costs (FCTs) influence market participation of pulses growers and limit the transmission of price and quality information.

The supply response model shows some positive influence of price on area allocation for pigeon pea and black gram and some negative effects of yield and price increase of competing crops on pigeon pea acreage. However, for the most part, the area of Kharif pulses is inelastic to prices in the long run. Irrigation, rainfall and yields in the lag year are shown to have a significant influence on area allocation for pulses. The market study reveals that low yields, low landholding size and geographical disadvantages of high agro-climatic risk and poor connectivity hinder market access of pulses farmers relative to other crops. Market power in favor of buyers and poor price and quality information is a disadvantage to sellers, influencing their ability to participate in markets.

A quantitative study would be required to identify the magnitude of farm and market-level transaction costs.

This study helps to understand the supply response of pulses and gives suggestions to direct policy to rectify this.