基金投资风格漂移识别——基于收益和风险双维度

修正EGARCH-M模型构建基金投资风格漂移识别模型,考量收益和风险两个维度。实证发现,在较长时期内,中国基金投资风格不存在严重的漂移现象不明显,但在较短时期内,基金投资风格没有表现出较大的漂移度,相对于股市上涨阶段,股市下跌阶段基金投资风格发生漂移的概率更高。与现有的两种主要基金投资风格漂移识别方法相比较,模型具有四个方面的优越性,实证研究表明模型是可行的。

The Drift Identification of Fund Investment Style Based on Two Dimensions of Return and Risk

The EGARCH-M model is adjusted to construct a new identification method, which can simultaneously examine the return and the risk. Our Empirical study finds that seen in a long period of time, the investment style of Chinese funds don''t exhibit serious drift, but in a shorter period, they show a great drift. Compared with a stock market rising phase, the fund investment style has higher drift probability in a stock market declining phase. Compared with the existing two identification methods for fund investment style drift, the new model has four advantages, and our empirical study shows that the model is workable.