Abstract

In order to reinforce traditional credit indicators such as credit rate or financial ratio, many financial market data; such as the stock prices or their returns are used to evaluate corporate credit risk. Even though many structural models, which are using stock returns and their volatilities, are used to measure credit risk, empirical studies to find out how to measure desirable stock return volatility or which interval data is better for measuring the volatility are not enough. So, we tried to find out empirical evidences of following two questions. First, whether stock return volatility could be used as a timely indicator for credit events, such as bankruptcy or credit rate change. Second, which measure and which interval data are the best to calculate stock return volatility for credit indicator. We have reached the following empirical conclusions based on recent Korean stock market data. First, stock return volatility could be useful for early warning of credit events, because the volatility showed meaningful increase before the credit event. Second, 90~150 daily stock return data are useful to measure the volatility. Short-term data, less than 90 days are too sensitive to market circumstances and they easily increase without any credit level change. On the contrary, volatilities based on long-term data, more than 150 days are too smooth to use as a timely credit indicator. Third, in aspect of the measure of volatility, realized volatility which assume the averages of short-term stock returns are ‘zero’ is more efficient than traditional standard deviation. Those conclusions are based on recent Korean stock market data, so further robustness test should be followed.

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