Securities Investment Fund Performance Evaluation Method And Empirical Analysis

In order to objectively evaluate the investment and management activity of the fund, it is important to measure the fund performance. In China, though limited by the short evaluation period, few sample funds and the available of the required financial data, it is still necessary and meaningful to comprehensively and systematically analyze the equity fund performance in their initial stage. This empirical study mainly employs the econometric approaches and quantitative analyze. The 4 prime parts of the paper are as follows.Firstly, I measure the total performance of the fund when applying 7 various single factor indexes, illustrate each of their applicability and weakness. The results indicate that the returns are more affected by the benchmark chosen than we previously believe. All in all, the M-2 measure and the Sharpe ratio are the rather meaningful and practical approaches among the seven indexes to rank-order feasible portfolios or funds for the analysts .In section two, the study examines the ability of risk control and diversification of the fund and composition of the returns. It shows that systematic risk is the principal part of the total risk and the downside risk contributed the large proportion to the standard error. Fama's excess returns decomposition indicated that benchmarks chosen seriously affects results; most of the total returns were realized through the selectivity returns, while the latter mainly came from the net selectivity returns. The third section is about the performance attribution analyze, focusing on the timing and security selectivity of the fund using various models. The evidence suggests that most funds have positive security selectivity coefficient and negative timing coefficient, though not significant by and large. And the condition is better in the bear market. The correlation of the timing and security selectivity is negative. Also the benchmark affects the results seriously. Finally, the study investigates performance persistence. No evidence supports the obvious persistence of the fund in general. The only strong proof is using past 6 months data to forecast the following 6 to 9 months returns, which shows significant persistence. When using the two-way tables, the sample funds universe can't reject the feature of the hot- hand, but not sufficient. In the simulation for testing persistence strategies, this paper empirically emphasizes that persistence varies by sampling period frequency.