Research On The Financial Alerting System Of Credit Default Among Listed Real Estate Companies

Nowadays, Credit plays a very important role in our daily lives, and it becomes thefootstone of social economy. Credits involve in all aspects of the market economy,both in the entity and virtual aspects. Companies trade with each other, and creditsarise from trades which belong to entity aspects, financial products with complexstructure which derived from basic financial instruments like bond and stock alsohave connections with credit, because this is the way they work in the money marketor capital market. Therefore, credit is of great essence in a market economy.Facing the increasing importance and complexity of credit system, it is necessaryfor us to establish credit related warning system, scholars from both academic fieldand practical field established handful of models concerning risk warning system,some of them are built on the complicated econometric theories, some are built on thebasis of some financial indicators, focus mainly on finding the relationship betweenthe financial indicator and credit default risk.The above two methods have advantages and disadvantages at the same time. Forcomplicated risk measurement models, on the one hand, calculation process isrelatively complex which means it is inconvenient for the users to carry out riskprediction work, on the other hand, the more complex the models, the more likely toomuch assumptions involve in. Complex risk measurement models have their ownadvantages, including using data with high frequency or less high frequency, which,in turn, makes the samples abundant, besides, the theoretical basis of econometricmodel itself is relatively strong and logical. For financial index method, the advantageis that models are simple and easy to manipulate, disadvantage concerns the limitationon sample volume.Real estate industry is an important component in the third industry, and it has beenone of the “pillars” of china economy, the operations in real estate industry involvewith a wide range of industries, so keeping a healthy and stable development trend inreal estate industry is very important to the economic development in China,especially during the economic transformation time. Since the growth rate of Chinaeconomy has been slowing down, people pay more attention on growth quality thanspeed，and market demand for housing shrinks, real estate companies will remainunder pressure. Changes of national macro factors, fierce competition inside industry and drawbacks in internal control system could all put great threats on thedevelopment of real estate industry.How to detect out credit default risk of real estate companies in advance, andformulate countermeasures to prevent situations getting worse is an inevitablequestion waits answering. From the perspective of the status quo in real estateindustry, credit default happens gradually, but not enough to establish the alertingsystem. In order to solve this problem, we drop off traditional ways and use adjustedKMV model (adjusted by ARMA-GARCH model) selectively to measure the creditrisk which will be represented by DD (Default Distance), and then, substitute actualdefault event with DD in the multivariate regression process, so as to establish thefinancial early warning system. After a comprehensive test, we concluded that CR(Short for current asset ratio), DTA (debt to asset or asset-liability ratio), ROLTC(return of long-term capital), Tobin’s Q and DFL (Degree of Financial Leverage) canbe used as financial alerting indexes for the real estate companies.