In Japanese, zero references often occur and many of them are categorized into zero ex-ophora, in which a referent is not mentioned in the document. However, previous studies have focused on only zero endophora, in which a referent explicitly appears. We present a zero reference resolution model considering zero exophora and author/reader of a document. To deal with zero exophora, our model adds pseudo entities corresponding to zero exophora to candidate referents of zero pronouns. In addition, we automatically detect mentions that refer to the author and reader of a document by using lexico-syntactic patterns. We represent their particular behavior in a discourse as a feature vector of a machine learning model. The experimental results demonstrate the effectiveness of our model for not only zero exophora but also zero endophora.