Performance of Portfolios Based on the Expected Utility-Entropy Fund Rating Approach.

Yang and Qiu proposed and reframed an expected utility-entropy (EU-E) based decision model. Later on, a similar numerical representation for a risky choice was axiomatically developed by Luce et al. under the condition of segregation. Recently, we established a fund rating approach based on the EU-E decision model and Morningstar ratings. In this paper, we apply the approach to US mutual funds and construct portfolios using the best rating funds. Furthermore, we evaluate the performance of the fund ratings based on the EU-E decision model against Morningstar ratings by examining the performance of the three models in portfolio selection. The conclusions show that portfolios constructed using the ratings based on the EU-E models with moderate tradeoff coefficients perform better than those constructed using Morningstar. The conclusion is robust to different rebalancing intervals.

Stock price crash risk and military connected board: Evidence from Thailand.

Based on the agency and stakeholder theories, effective boards, acting as an internal governance mechanism, reduce agency costs. This paper asks whether military connected boards represent a good governance tool by exploring how military connected boards affect stock price crash risk. Using instrumental variable analysis, we document that firms with military connected boards have lower risk of stock price crashes. Our findings are unlikely to have endogeneity concerns and shed light on the role of military connected boards as an effective internal governance tool. Consistent with the conservatism hypothesis and stakeholder theory, by being transparent about firm-specific bad news, military connected boards could effectively monitor managers to ensure they act on all stakeholders' interests.

The future of digital donation crowdfunding.

Amidst the Coronavirus crisis, many fundraising projects have emerged to relieve financial burdens resulting from social distancing policies. Crowdfunding is a way to raise money to fund a business, project or charity, through either social media or other online platforms to reach hundreds of potential sponsors. We developed guidelines for effective donation-based crowdfunding through online platforms. Using Futures Research (FR) technique, we conducted our analyses in 3 phases. In Phase 1, we reviewed relevant literature and conducted in-depth interviews of related parties. In Phase 2, we interviewed experts using Ethnographic Futures Research (EFR) technique. In Phase 3, we visualized the future using the principles of Futures Wheel, Cross-impact Matrix and Scenarios. Based on our findings, effective donation-based crowdfunding platforms should adopt Blockchain technology for transparency and accountability, and incentivize donations to keep backers loyal. Founders should be required to obtain fundraising licenses from relevant regulators. Finally, laws and regulations that protect platform users should be standardized internationally. Our proposed guidelines hope to improve the quality and transparency of future fundraising activities.

Do algorithm traders mitigate insider trading profits?: Evidence from the Thai stock market.

This paper asks whether algorithm traders (AT) mitigate insider trading profits in the Thai stock market over the period of 2010-2016. We find that in general it does but not in the case of buy side, big trades nor the executive trades. Our findings suggest that, to some extent, AT can take important role to increase an efficiency in stock market by processing the public information and incorporating it into price at ultra-fast speed. Additional robustness checks based on the instrumental variable approach confirm our findings.

Jumps and Cojumps analyses of major and minor cryptocurrencies.

This paper empirically examines jumps and cojumps of both major and minor cryptocurrencies. Understanding the nature of their jumps and cojumps plays an important role in risk management, asset allocation and pricing of derivatives. We find that all cryptocurrencies display significant jumps. Furthermore, minor cryptocurrencies appear to have significantly higher jump intensity and jump size than major cryptocurrencies. Finally, we find that cojumps of the Thai stock market index and minor cryptocurrencies have a greater intensity than that of major cryptocurrencies.

The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US.

In this paper, we propose an alternative fund rating approach based on the Expected Utility-Entropy (EU-E) decision model, in which the measure of risk for a risky action was axiomatically developed by Luce et al. We examine the ability of this approach as an alternative fund rating approach for its ability to potentially mitigate the drawbacks of the risk measure used in Morningstar ratings, and investigate the ability of the EU-E model based and Morningstar ratings to predict mutual fund performance. Overall, we find that the risk measure used in both models plays a defining role in their ability to predict future fund performance, and that the EU-E model can effectively consider the behavioral decisions of an investor.