Portfolio Theory and Capital Asset Pricing Model

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Regression 1

The results from regression 1 indicate that there is no relationship between the return and the administration fee of a fund. Based on this result, general idea of no relationship between the return and administration fee is correct.
It is obvious that the fund company sets their fees based upon criteria other than expected return, such as promotion costs, facility costs, labour costs, etc. Of course, the fee varies from different fund companies due to size, location, investment and labour differences. Even in the same fund companies, the fund fee differs between individual funds due to how large the fund capital is and/or if the fund is a PPM fund.
From table 4.1, one can see that the total average administration fee of the Swedish fundsi was 0.29% per quarter. Of course, the PPM funds had the lowest average fee, 0.22% per quarter, due to their special agreements. They, in turn, were followed by the banks who had a quarterly fee of 0.32%, and finally the ‘others’ at 0.34% per quarter.
To continue, the total quarterly average return of the population was 3.50%. Interestingly, the ‘others’ had the lowest quarterly average return, even though they are, in general, more specialized than the bank and PPM funds. The bank funds had the highest quarterly average return of 3.64% followed by the PPM funds at 3.58%. However, the bank funds are found to have the most risk, the highest standard deviation, (11.97) followed by the ‘others’ (11.73) and the PPM funds (11.53).
Although there is no relationship between the administration fee and the return of a fund, one can still see that the banks have, on average, performed better than all other fund companies in the market during the given time period, though associated with a slightly higher risk.

Regression 2

The findings in regression 2 again show that there is no relationship between the return and the administration fee, but now the return is measured as risk-adjusted performance (the Sharpe ratio). None of the variables are statistically significant at the 95% confidence level. This, however, was expected since there was no relationship found in regression 1 between returns and administration fees.
The quarterly average Sharpe ratio for all the funds in this time-period was 0.07%, as can be seen in table 4.1. The banks and the PPM funds had the highest Sharpe ratio with 0.08 and 0.07 respectively. Once again, the ‘others’ performed worst of these three fund companies with a Sharpe ratio at 0.05. This means that the ‘others’ had the lowest risk-adjusted quarterly average return in this time period. Again, the bank and PPM funds performed better than the ‘others’.

Regression 3

In regression 3, the relationship between the market-adjusted return and the market-adjusted fee is analyzed. Also, the bank, PPM and the ‘others’ fund companies are examined. The regression is found to be statistically significant due to a high F-value (3.57). All variables, except the intercept term for the market-adjusted fee and the PPM dummy variable, had a sufficiently low p-value, making them significant at the 5% significance level.
Looking at the R-square value, only 0.80% of the variation in the Over/Under-Return is explained by the explanatory variables. This is very low and merely indicates that the administration fee is not a good explanation to the variation in the return which of course is fairly logical. The fund companies do not know the return, they do not have the privilege of having perfect forecasting ability, hence the low R-square value.
Focusing upon the market-adjusted administration fee, the Over/Under-Fee variable, one can see that if the Over/Under-Fee increases by 1%, the Over/Under-Return will actually decrease by 0.99%, ceteris paribus18.
In other words, this means that as the fund companies raises their administration fee compared to the market average administration fee, the return compared to the market average return for the investor actually decreases, and the individual ends up in a worse situation than before. The change in the market-adjusted administration fee is almost the same as the change in the market-adjusted return. This of course shows in the slope of the estimated equation being very close to 1 (0.99)
From the results of regression 3, one can say something about how the banks and PPM funds compare to the whole population. The dummy variables in the regression all have the same slope as the total population of funds, of course, but they have a different intercept. The equality of the slope is rather irrelevant to the study at hand since its purpose is not to estimate projections, but only to examine whether or not there is a relationship between the return and the administrative fee in this specific time period.
To continue, by focusing upon the bank dummy variable, one can see that it is significant at the 5% level. The value of the coefficient represents the intercept which was estimated to 0.27. This means that the bank funds have over-performed the market since 0.27 > 0. Due to the lack of significance of the intercept terms for Over/Under-Fee and PPM dummy, one cannot determine whether or not the banks have over-performed them in the market.
However, one can still interpret table 4.1 where the different quarterly average market-adjusted returns and administration fees for the population of funds are displayed. From there one can see that the banks had the highest quarterly average market-adjusted return (0.15%). They were followed by the PPM funds (0.08%). The ‘others’ had the lowest figure and actually under-performed the market due to a negative value (-0.22%).

READ Large deviations for heterogeneous neural networks

1 Introduction
2 Background
2.1 Risk and Return.
2.2 Banks.
2.3 PPM.
2.4 Fund fees
2.5 Capital Gain Tax
3 Theoretical framewor
3.1 Portfolio Theory and Capital Asset Pricing Model.
3.2 Risk-adjusted Performance and the Sharpe rati
4 Empirical Analysis
4.1 Limitations
4.2 Data
4.3 Method
4.4 Result.
5 Discussion
5.1 Regression 1.
5.2 Regression 2.
5.3 Regression 3
5.4 Regression 4
5.5 Previous research and the critique on bank
5.6 Caveats.
6 Conclusion
6.1 Further Studies
References