论文标题
收入电话中的信用信息
Credit Information in Earnings Calls
论文作者
论文摘要
我们开发了一种新颖的技术，可以从季度收益电话的文本中提取与信用相关的信息。这些信息没有受到基本变量或市场变量的跨越，预测未来的信贷差异变化。这种可预测性的原因之一是，我们的基于文本的措施可以预测未来的信贷差异风险和公司盈利能力。更加牢固和呼叫级的复杂性提高了我们对利差变化的措施的预测能力。样本外投资组合测试表明，我们措施中的信息对于投资者很有价值。这两个结果都表明，投资者并未将收入电话中包含的信贷相关信息完全内化。
We develop a novel technique to extract credit-relevant information from the text of quarterly earnings calls. This information is not spanned by fundamental or market variables and forecasts future credit spread changes. One reason for such forecastability is that our text-based measure predicts future credit spread risk and firm profitability. More firm- and call-level complexity increase the forecasting power of our measure for spread changes. Out-of-sample portfolio tests show the information in our measure is valuable for investors. Both results suggest that investors do not fully internalize the credit-relevant information contained in earnings calls.
