Analyst Forcast And Credit Spread Of Corporate Bonds In China’s Interbank Bond Market

Compared with macro risk, asset pricing in bonds is always complex but traceable. Traditional credit spread comes from the loan prcing of commercial bank, expert system、rating system and scoring model, which cares less about fixed quantity. All of the three methods assume some features of enterprise will last a long way, which lacks desirable theoretical basis. Merton (1974), however, clarified and extended the Black-Scholes model into the area of bonds pricing, finding a new way to calculate credit spread. Reduced model always suggests that defalt is exogenous, so that we can compute defalt probability, and calculate the value of bonds. In order to explain the puzzle of credit spread better, academia use econometics to conduct the credit spread.However, compared with international peers, the Chinese academia on credit spread is relatively underdeveloped. Currently, the Chinese academia’s reseaches in the field of credit spread mostly focus on introduction of mature models from abroad; due to reasons such as limitation of data availability, the limited number of empirical researches is mostly based on data of individual bonds, therefore their empirical conclusions lack in representativeness and implication for investment.At the same time, recent researches show that analysts forecast earnings of listed companies is significant correlation with asset prices In the stock market. Taking as2008-2012China corporate bonds for example, this study found, analysts’forecasts play the same role on asset prices in the bond market. Our findings including:there is a significant correlation between the degree of deviation of analysts’ forecasts and bond credit spreads, a significant negative correlation between the number of analysts tracking a listed company and bond credit spreads; but not find significant correlation between analysts forecast dispersion and bond credit spreads, we believe that’s because investors do not consider all predictions of their reports. This paper through systematic review of foreign researches, the secondary market liquidity indicators have less explanatory power for credit spreads of corporate bonds, which may be associated with factors such as inactive trading, frequent fictitious trades, and the one-sided pattern on the secondary market. Changes in GDP are negatively correlated with changes in credit spreads. Ratings and durations also get their correlation with credit spread.This study extends the research on the analysts’ forecasts and affecting factors of bond credit spreads.