MUTUAL FUND PERFORMANCE

Mutual fund performance

Mutual Fund Performance

Data Analysis

The Sharpe Ratio Analysis

Historical data was gathered from portfolio.hu and a check was done to confirm its validity by comparing it to data gained from the Budapest Stock Exchange website. In order to compare the two data series, I used a macro that highlighted differences in share prices for the same dates. The portfolio.hu data proved to be incomplete in several cases; therefore, I relied on the bet.hu website for data download. I worked with 60 shares distributed variously between A and B category shares all traded on the UK Stock Exchange between August 2007 and August 2012. Using the VLOOKUP function in MS Excel, daily closing prices and dividends were adjusted according to trading days for each share. The task was to collect information on a specific date for all the shares on one row. In this process, I obtained numerous blank cells, which indicated unavailable data. In order to test the validity of the size and value factors in explaining returns on equity traded on the Budapest Stock Exchange, the gathered data from August 2007 and August 2012 of 60 stocks was mixed between A and B category stocks. The stocks were grouped into 6 portfolios according to size and book-to-market equity ratio. The small firms (S) were composed of companies with market capitalisation below the median irrespective of their book-to-market equity ratio, and the big firms (B) were those that were above the median. The high (H) book-to-market equity ratio firms were the top 30th percentile of the shareholder equity-to-market capitalisation ratio irrespective of size, the medium (M) category constituted the middle 40th percentile and the low (L) the lowest 30th percentile. To take a look at how valid this grouping was I performed a hierarchical cluster analysis using the statistical analysis software SPSS and Excel, once according to equity capitalisation and the second time, according to book-to-market equity ratio, using between groups linkage and squared Euclidean distance. I also repeated the results using within-groups linkage and Euclidean distance. In reading the dendrogram, the result is normally taken at a distance between 10 and 15 on the dendrogram scale. The formed clusters match with the previous grouping made according to percentiles and median as in Fama and French. Portfolios were formed at the beginning of each financial year, and regrouped accordingly every next January. The shares in the portfolios were value-weighted using their market capitalisation for weights, and categorised. The resultant 6 portfolios were the following: S/H, S/M, S/L, B/H, B/M, B/L. This meant that the first S/H portfolio contained shares that were small in size and with a high BE/ME. Following are the Sharpe ratios for the 60 firms that have been taken for the performance analysis:

Sharpe Ratios

1.29772

2.67098

2.23609

3.26127

1.76856

1.85077

2.42621

1.52953

1.45926

2.27058

1.96147

4.27064

1.82359

2.33223

2.89975

1.75114

1.88312

1.30625

1.90423

1.06428

1.79981

1.47289

0.72205

2.25725

1.86492

2.46970

1.38286

2.38008

1.94992

2.34461

3.68205

1.15826

3.33456

1.52153

2.12365

2.79922

5.13415

2.59887

0.98148

4.31356

2.16942

2.34505

2.87928

3.67569

2.41688

3.16502

3.17577

1.27342

2.59642

2.41115

2.64822

2.38112

2.67098

2.60511

2.95100

 

1.85077

3.30377

2.58512

 

2.27058

1.85430

4.07279

 

2.33223

2.60231

3.14234

 

1.30625

3.28952

4.69138

 

The ratios have been placed in order as the companies data was given for the analysis. The Sharpe ratios of all the firms do not vary too much though there are some firms which have outlier ...