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The Chinese bond market has achieved rapid development over the years. However, since the "rigid payment" in China was broken in 2014, the number and size of bond defaults have climbed up promptly and caused huge volatility in bond and even stock markets. To better manage and control the risk of the Chinese corporate bonds market, deep learning can be used as a helpful tool to predict the corporate default risk. This paper constructs a security warning model based on deep neural networks after a reasonable selection of characteristic indicators. By comparing Multi-Layer Perceptron (MLP) with the logistic regression method, it is found that MLP is more suitable in the security warning model to predict the default risk. And, hyper-parameter analyses and ablation study are conducted to explore the performance and accuracy of the best MLP settings. The experimental results show that the deep learning method accommodating the widely chosen factors in the security warning model is effective in predicting corporate bond defaults in China. [ABSTRACT FROM AUTHOR]

Large corporations usually cover their capital and operating expenses by issuing bonds with fixed rates and different maturities. This paper proposes a multistage stochastic programming (MSP) model with multiple objectives to optimize bond issuance by satisfying the three common objectives of corporate managers, as follows: (i) Minimizing expected discounted cost under cash liquidity and financial leverage risk constraints. (ii) Minimizing financial leverage risk under expected discounted cost and cash liquidity risk constraints. (iii) Minimizing cash liquidity risk under expected discounted cost and financial leverage risk constraints. We measure liquidity risk as conditional payment-at-risk (C P a R), according to the corporation's financial characteristics. Financial leverage risk is captured by conditional financial leverage-at-risk C F L a R , which we design based on conditional value-at-risk (C V a R). Through empirical analysis of a company in China, we explore the efficient frontier curves for the three above objectives and provide the corresponding issuance compositions of an optimal bond portfolio. Our MSP model offers guidance for corporations on achieving a trade-off between cost and risk when issuing corporate bonds. [ABSTRACT FROM AUTHOR]

This study derives a liquidity and credit risk-adjusted capital asset pricing model and investigates the model using the data set in China's corporate bond market. Our research shows that the channels through which liquidity risk affects corporate bond return are individual bond liquidity risk, the interaction between individual bond liquidity risk and market liquidity risk. The channels through which credit risk affects corporate bond return are individual bond credit risk, the interaction between individual bond credit risk and market credit risk. The main channel through which the interaction between liquidity risk and credit risk affects corporate bond return is the interaction between individual bond liquidity risk and market credit risk. The model reveals the impact mechanism of individual risk and market risk on bond return and explains why the interaction between liquidity risk and credit risk affects bond pricing. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of multidimension liquidity, credit risk, and the interaction between liquidity and credit risk on corporate bond spreads based on a large transaction data set from July, 2006 to June, 2016, including the monthly data of 3716 bonds in China. Our main findings reveal that liquidity premiums are the main parts of corporate bond spreads. The interaction between liquidity and credit risk plays a significant role in determining corporate bond spreads. In addition, the differences between the interbank market and the exchange market have a significant impact on corporate bond spreads in normal period, and the interaction between liquidity and credit risk has an enhanced impact on corporate bond spreads during financial crisis. We also find that the interaction between liquidity and credit risk will increase with the increase of liquidity risk and credit risk and it is a time-varying dynamic process. [ABSTRACT FROM AUTHOR]

With the rapid development of the national economy, the film industry has risen rapidly under these conditions, and the development of film occupies a more important position in this process, which has led to the development of investment in the film field, an internationally recognized cultural space. This paper studies the commercial investment in the film field based on the edge detection of the digital image of the visual sensor. The purpose of the research is to point out the direction of commercial investment in the film industry by studying the effect of the edge detection of the digital image of the visual sensor on the application of the film object. The image edge detection algorithm based on wavelet transform and morphology and the application of these image edge detection algorithms such as wavelet theory analyze the shortcomings of movie, sound effects, and pictures and make a comparison before and after the improvement. Audiences, as the direct enjoyers of the cultural product of the film, their opinions, and evaluations of the film, largely determine the quality of the work. On the contrary, a good work can attract the public's attention and bring a large impact. The data acquisition in this process is mainly based on the questionnaire survey of the audience. The experimental results show that before applying digital image edge detection to transform the clip, 7 people thought that the clip needed to be further improved to improve the quality of the film itself, and only 1 person affirmed the film; after the modification, 9 people proposed the film praise; in addition, 15 people audience watched the film processed by the edge detection method and gave high evaluations to the three aspects of sound effects, special effects, and editing, especially the editing part, with a score of 8.9. [ABSTRACT FROM AUTHOR]

From the angle of research and development (R&D) input, this paper analyzes how bond financing affects corporate total factor productivity (TFP). Based on the 2007–2019 data on listed enterprises, the influence and action mechanism of bond financing on corporate TFP were empirically examined. The results show that bond financing significantly boosts corporate TFP. The mechanism analysis reveals that bond financing promotes TFP by stimulating corporate R&D input. The research sheds new light on the relationship between finance and TFP from the perspective of bond financing and provides a reference for policymakers to boost corporate TFP by promoting bond financing. [ABSTRACT FROM AUTHOR]

This study investigates the factors impacting the price difference between the interbank market and the exchange market for the same bond using a large transaction dataset from July 2006 to June 2016 in China. We find that market liquidity and macrofactors mainly affect the price difference between the two markets for the same bond. And individual bond liquidity explains only a small part of the price difference. We also find that the interaction between liquidity and credit risk is an important factor affecting the price difference, and the effect is greater during financial crisis. [ABSTRACT FROM AUTHOR]

This paper proposes a generalized bond pricing model, accounting for all the effects of credit risk, liquidity risk, and their correlation. We use an informed trading model to specify the bond liquidity payoff and analyze the sources of liquidity risk. We show that liquidity risk arises from reduced information accuracy and market risk tolerance, and it is market risk tolerance that links credit and liquidity. Then, we extend the traditional bond pricing model with only credit risk by incorporating liquidity risk into the framework in which the probabilities of the two risk events are estimated by a joint distribution. Using numerical examples, we analyze the role of the correlation between credit and liquidity in bond pricing, especially during a financial crisis. We document that the varying correlation between default and illiquidity explains the phenomenon of bond death spiral observed in a financial crisis. Finally, we take the US corporate bond market as an example to demonstrate our conclusions. [ABSTRACT FROM AUTHOR]

In this paper, we consider a robust optimal investment-reinsurance problem with a default risk. The ambiguity-averse insurer (AAI) may carry out transactions on a risk-free asset, a stock, and a defaultable corporate bond. The stock's price is described by a jump-diffusion process, and both the jump intensity and the distribution of jump amplitude are uncertain, i.e., the jump is ambiguous. The AAI's surplus process is assumed to follow an approximate diffusion process. In particular, the reinsurance premium is calculated according to the generalized mean-variance premium principle, and the reinsurance type has to follow a self-reinsurance function. In performing dynamic programming, both the predefault case and the postdefault case are analyzed, and the optimal strategies and the corresponding value functions are derived under the worst-case scenario. Moreover, we give a detailed proof of the verification theorem and give some special cases and numerical examples to illustrate our theoretical results. [ABSTRACT FROM AUTHOR]

This article, titled "Retracted: Security Warning Model of Chinese Corporate Bond Defaults Based on Deep Neural Networks," has been retracted by the publisher, Hindawi, due to evidence of systematic manipulation of the publication and peer-review process. The publisher cannot vouch for the reliability or integrity of the article. Wiley and Hindawi have implemented additional measures to safeguard research integrity. The corresponding author has been given the opportunity to respond to the retraction. [Extracted from the article]

This paper analyzes the firm bond valuation and credit spread with an endogenous model for the pure default and callable default corporate bond. Regarding the stochastic instantaneous forward rates and the firm value as an infinite dimensional Poisson process, we provide some analytical results for the embedded American options and firm bond valuations. [ABSTRACT FROM AUTHOR]

The default of Suntech Power made the year 2013 in China "the first year of default" of bondmarkets. People are also clearly aware of the default risk of corporate bonds and find that fair pricing for defaultable corporate bonds is very important. In this paper we first give the pricing model based on incomplete information, then empirically price the Chinese corporate bond "11 super JGBS" from Merton's model, reduced-form model, and incomplete information model, respectively, and then compare the obtained prices with the real prices. Results show that all the three models can reflect the trend of bond prices, but the incomplete information model fits the real prices best. In addition, the default probability obtained from the incomplete information model can discriminate the credit quality of listed companies. [ABSTRACT FROM AUTHOR]