A simple robust asset pricing model under statistical ambiguity
在统计模糊下推导出一个简单的稳健单因子市场模型，用相对熵作为模糊指数约束多先验集，并讨论其衡量模型偏差和检测误设的有效性。模型中的风险和模糊溢价为股票价格设定边界，可作为投资者应对极端市场事件的“安全边际”。
We derive a simple robust single-factor market model under statistical ambiguity that uses relative entropy as the ambiguity index constraining the multiple priors set. We also discuss theoretically the validity of relative entropy to measure model discrepancy and detect misspecification. The premium on both risk and ambiguity in our model would set a bound on stock prices that investors can use as a ‘margin of safety’ against extreme market events.