Selecting a better valuation model to measure bubble level of stocks price: empirical study from internet-based finance stocks in A-share market

As a star of emerging industries in China, internet-based finance has been developing rapidly. This paper, considers selecting a more suitable valuation model to measure the intrinsic value and price bubble of Internet-based Finance stocks. By comparing the relative valuation accuracy of the Kim et al. model with the Frankel-Lee model and the F-O model applied in the prior studies, this study finds that the Kim et al. model highlights the industry-specific features and outperforms other models in interpreting stocks price variation. Especially, under the circumstance of soaring and slumping stocks price variation (e.g. 2015), it is essential to study the price bubbles of internetbased finance stocks at different points of Shanghai Stock Exchange Composite Index. Surprisingly, our empirical results suggest that the internet-based finance stocks have negative bubbles at the whole average level, and about half of them are undervalued. Moreover, there are positive correlations between the bubble level and three key factors including the trading volume, the price to book ratio and whether to do cross-industry business on internet-based finance. These findings imply that the Kim et al. model contributes to improving valuation accuracy of internet-based finance stocks and explainability of the price bubbles in A-share market

Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions

We introduce an evolving network model of credit risk contagion in the credit risk transfer (CRT) market. The model considers the spillover effects of infected investors, behaviors of investors and regulators, emotional disturbance of investors, market noise, and CRT network structure on credit risk contagion. We use theoretical analysis and numerical simulation to describe the influence and active mechanism of the same spillover effects in the CRT market. We also assess the reciprocal effects of market noises, risk preference of investors, and supervisor strength of financial market regulators on credit risk contagion. This model contributes to the explicit investigation of the connection between the factors of market behavior and network structure. It also provides a theoretical framework for considering credit risk contagion in an evolving network context, which is greatly relevant for credit risk management

A novel ensemble model with enhanced feature interpretability: for China’s SME credit risk

The raw data for this study is the private annual loan ledger data obtained from a commercial bank. Because it involves trade secrets and data compliance issues, a limited sample of desensitized data was uploaded.</p

New features, new perspectives: a novel ensemble model enhancing SME credit risk assessment

The raw datasets for this study are the private annual loan ledger data obtained from a commercial bank called ChinaZJB and the UCI datasets Polish 1, Polish 2, Polish 3, Australian, and Taiwan credit datasets for robustness checks. Because the ChinaZJB dataset involves trade secrets and data compliance issues, a limited sample of desensitized data was uploaded with the UCI datasets to show the data structure.</p