Jump Behavior Based Stock Asset Return And Default Risk Of The Companies Listed In China

Along with the development of world economy and the economic globalization, the financial industry has already been the core of every country's economy. However, its development and internationalization brings not only the dynamics and energy, but also the risk and impact. Especially, the developing countries including China and some emerging countries, which boast a short history of financial development and relatively imperfect financial system, have fewer opportunities to join in formulating the international financial principles and are unfamiliar with the emerging financial instruments, are more like to be hit by international financial risks and suffer more losses. Since 1990s, various financial crises, including Asian financial crisis and the global financial crisis resulted from US sub-prime mortgage crisis, have caused mass impacts on these markets and further strengthened their incompletion and instability. The assets in these markets enjoy more obvious double features of normal volatility and jump. Therefore, the research upon the jump risk of asset returns has already become one of the important and difficult issues in financial field.Along with China's economic development and open to the outside, more and more companies select the road of listing on the market to obtain the capital financing. Until now, the listed companies have already become the important participants and beneficiaries of China's economic development. However, facing the external environment of frequent international financial risks and internal environment of various sudden events such as earthquake, disaster of snowstorm and floodwater, many listed companies unavoidably suffer impacts and losses, which cause the increase of the frequency of jump in their assets returns. Therefore, the issues, including how to describe the asset return features and measure credit risk of China's listed companies in new context, how to model the asset return change process with jump and how to improve the credit risk evaluating system, are very important for managing and controlling the risks of listed companies.Recently, the researches about credit risk in foreign countries have paid more and more attention to the jump factors. However, most of them try to isolate the jump risk from traded data of financial derivatives such as stock option and credit swap. But, China's derivative market only has a very short history and owns small amount of traded data, so this scheme is unworkable when analyzing the jump change in the default risk of companies in China. On the other side, China also features a relatively smaller scale of bond market, facilities and system of which are imperfect. The default risk premium of bond is only linked to the credit grade, which is evaluated by credit rating agency referring to the obtainable limited financing data and resources. But these data and resources usually cannot wholly, actually and immediately reflect various external information, so it also needs to introduce the changing stock market data and information into credit rating system of bonds to improve its rating ability. This method not only helps to elevate the credit-risk indentifying ability of model, but also plays important role in constructing internal credit rating model for banks and listed companies, pricing the defaultable bond and improving the early-warning ability.For this research purposes, the whole jump-behavior based research system of "claim asset change process→total asset change asset→default risk" measurement, which analyzes the change of asset value and total capital structure caused by jump factors, is completely illustrated and constructed. It establishes the non-linear relationship between claim value and asset value on the basis of option pricing model with jump and transfers the impact of jump on the claim asset to the total asset so as to introduce jump factors into default risk measurement.When studying the jump behavior of stock return, it constructs the threshold-based state-dependent autoregressive jump intensity (TSD-ARJI) GARCH model, which taking the significant influence and the threshold effect of state-variables on the expected jump intensity into account and comprehensively analyzing time variation, clustering and state-dependence of jump behavior as well as non-symmetry and clustering of normal volatility. Then, it applies the model to contrast the risk components of ST and non-ST stocks and discuss the volatility contamination between cross-shareholding companies. Both goodness of fit and forecast evaluation show TSD-ARJI-GARCH model performs better in contrast to the existing models. It can better describe the time variation and clustering of jump behavior, more accurately reflect the influence of the information change of state variables on the jump behavior, conquer the over-identification of ARJI-GARCH upon the jump point and more effectively discriminate the jump features of ST and non-ST stocksWhen measuring the impact of jump factors on default risk, it takes the listed companies in China as the samples and uses information contained in the claim market to indirectly measure the asset value change with jump and the default probability. It not only studies the influence of macro and systematic factors and sudden events on jump behavior, but also analyzes the unique jump features of individual stock caused by idiosyncrasy. Then, it contrasts jump-diffusion models and pure diffusion models in measuring default risk. The empirical research results show the global financial crisis, disaster of snowstorm and earthquake in 2007 and 2008, obviously induced abnormal jumps of all stocks. In this period, default risk of listed companies increased significantly. The jump risk not only presented extensively and systematically, but also was influenced by idiosyncrasy. Thus, each company featured unique jump behavior and default risk. After taking the jump factors into consideration, the default risk can be divided into jump-style default risk and continuity-style default risk. In short term or when the ratio of asset value to reliability is relatively lower, the jump part dominates the whole risk to make the default probability larger than that estimated by pure diffusion model. On the contrary, in long term or when the ratio of asset value to reliability is relatively higher, the diffusion part dominates the whole risk to make the default probability smaller than that estimated by pure diffusion model.