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Empirical Research On Performance Attribution Of Securities Investment Fund In China

Posted on:2020-06-30Degree:MasterType:Thesis
Country:ChinaCandidate:L LiuFull Text:PDF
GTID:2439330572488772Subject:Statistics
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Since the promulgation of the Interim Measures for the Management of Securities Investment Funds in 1997,China's securities investment fund market has entered a stage of rapid development.After 20 years of development,securities investment funds have increasingly become one of the main investment tools for most institutional investors and individual investors in China.Along with the continuous maturity and improvement of China's financial market system,the number of companies engaged in fund management has increased rapidly,fund products have been continuously enriched,and the fund scale has increased rapidly as well.There have also been many research and discussions related to the performance evaluation of securities investment funds in the academic community.Although there have been many researches related to fund performance evaluation in the domestic academic community,most of them are based on foreign research theories,and more use of fund net worth and daily yield data for analysis.Because there are many factors affecting the net value of the fund,it will interfere with our attribution analysis.Therefore,this paper intends to analyze the performance of the fund by using the position and transaction data.We first use the single-period Brinson model to decompose the single-end fund excess returns into three parts:asset allocation contribution,individual stock selection contribution and interactive contribution.Since the interactive contribution is not intuitive to explain,we will base the top-down investment decision-making approach.It merged with individual stock selection contributions.After the attribution analysis was performed for all time periods,the results of the multi-period attribution analysis were obtained by smoothing the decomposition results of each period using the Menchero model.In this paper,15 open-end securities investment funds are randomly selected.In order to make the conclusions more universal,the sample funds mainly choose hybrid funds,which include mixed-shares,partial-debt mixed and flexible allocation funds.Regarding the selection of sample intervals,in order to fully reflect the performance of funds in different market environments,we chose to use the sample interval from the beginning of 2014 to the end of 2018(have experienced a wave of bull and bear markets).In terms of the selection of benchmark indices,we selected the CSI 300 Index,the China Bond Composite Index and the interbank deposit interest rate as benchmarks for stocks,bonds and bank deposits.We conducted empirical analysis using sample funds and data related to benchmark indicators,and obtained the following conclusions.First of all,most fund managers have certain stock selection capabilities,but due to asset allocation and other reasons,the ability to allocate assets is not obvious.At the same time,due to the limited investment tools available in China's money market,open fund holders need to maintain certain l iquidity in order to cope with large redemptions that may occur in the future but are unpredictable.Assets will also offset some of the stock selection contributions to a certain extent.At the same time,we also found that when the entire stock market is in a rising stage,investors have increased their focus on asset allocation because of increased investment confidence,thus increasing stock positions.From this we can see that in terms of stock assets of fund products,asset allocation contribution is positively correlated with the market's continued rising market.When the market goes down,investors will appropriately lower their positions to prevent risks.On the other hand,due to the difficulty in selecting high-quality stocks at this time,the impact of individual stock selection on excess returns is less obvious.
Keywords/Search Tags:Securities Investment Fund, Performance Attribution, Brinson model, T-M Model
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