Implications & Recommendations

This study contributes to the existing literature by examining a sample of sin industries previously not examined exclusively. Further, by adopting an observation period that stretches beyond 2007, we have incorporated five years of additional data which has previously not been examined. This enabled us to comment on the performance of US sin stocks during a recent time period of troubled financial markets. Additionally, we have further contributed to academia by employing a rolling regression technique examining the persistency of US sin stock performance. The results show no indication of a changing trend in performance, and thus provide investors with information that the abnormal returns have been persistent over time. The results from the comparisons of weighting schemes show that there can be substantial effects on the outcome of an investor’s investment depending on the portfolio weighting. This observation further questions findings from previous research where no differences between equally and value weighted portfolios, thus highlighting the importance of the comparison. For SRI investors, we provide evidence that excluding sin stocks will have a negative impact on the performance as they exclude industries which, in this study, has proven to outperform the market.

It is argued here, and in previous research within the field of unethical investing that what is considered unethical constantly changes over time and might be very different from one region to another. Because of this dynamic attribute on the view on sin, we find it important to keep the field of research updated with performance measurement studies to track the future development. The findings in this study indicate that how the indices are weighted may play a significant role on the overall performance. Therefore, it would be interesting to see a deeper investigation on different weighting schemes. We have not focused on portfolio theory in particular; however the yields from an optimally constructed sin stock portfolio as well as other investment strategies could provide interesting evidence. In comparison with previous research, the results generated in this thesis are generally slightly more positive, something that may be due to the chosen time period. It should therefore prove interesting to develop the rolling regression initiated here, on a longer time span, for a deeper analysis of the dynamic behavior of the alpha over time. In this analysis, we would suggest the usage of daily data in order to get better significance which enhances the possibility to investigate shorter rolling periods than exploited in this study. Another interesting aspect to investigate is what other market factors affect these sin stocks. Hong & Kacperczyk (2009) have already proved that there is an effect associated with the shunning of sin stocks in the US. It should prove interesting to see if there are also effects from the variables tested by Salaber (2007) in Europe, namely if there are effects associated with religion, culture, litigation risk etc. on American sin stocks.

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APPENDIX 1 – Performance of Value Weighted Indices

The table presents the outcome of the time-series regressions of each of the sinful indices on the market portfolio and the value, size and momentum factors, over the period 1973 to 2012. The dependent variables are calculated as the total return of the indices over the risk-free rate. MKT denotes the return on the market portfolio in excess of the risk-free rate. SMB reflects the indices correlation with the small minus big portfolio. HML represents the correlation with the return difference of a portfolio of value stocks less growth stocks. MOM indicates the correlation a portfolio of past winners. Standard errors are shown in parenthesis under each coefficient. F-statistics, T-statistics and P-value of alpha are presented for each regression, as well as the R-squared and number of observation. The alpha is a monthly average during the observation period, in percent. Note that the stars ***, ** and * denote significance at the 1%, 5% and 10% levels.

SINDEX Performance 2007-2012

INDEX Alpha (%) MKT SMB HML MOM No. of obs. Adjusted R2 F-Statistic T-statistic of α P-Value of α Annual alpha 0,508*** 0,618***

INDEX Alpha (%) MKT SMB HML MOM No. of obs. Adjusted R2 F-Statistic T-statistic of α P-Value of α Annual alpha 0,621* 0,734***

APPENDIX 2 – Persistency of Industries Performance

The tables present the results from the rolling regression performance over 10 year periods for each of the industries. Presented are the values for Alpha, Standard Error and T-statistics for each regression plotted over time.

AINDEX

DINDEX

GINDEX

-0,4 -0,2 0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6

jun-83 okt-84 feb-86 jun-87 okt-88 feb-90 jun-91 okt-92 feb-94 jun-95 okt-96 feb-98 jun-99 okt-00 feb-02 jun-03 okt-04 feb-06 jun-07 okt-08 feb-10 jun-11

Alpha S:E T-stat

-1 -0,5 0 0,5 1 1,5 2

jun-83 nov-84 apr-86 sep-87 feb-89 jul-90 dec-91 maj-93 okt-94 mar-96 aug-97 jan-99 jun-00 nov-01 apr-03 sep-04 feb-06 jul-07 dec-08 maj-10 okt-11

Alpha S:E T-stat

-1,5 -1 -0,5 0 0,5 1 1,5 2

jun-83 okt-84 feb-86 jun-87 okt-88 feb-90 jun-91 okt-92 feb-94 jun-95 okt-96 feb-98 jun-99 okt-00 feb-02 jun-03 okt-04 feb-06 jun-07 okt-08 feb-10 jun-11

Alpha S:E T-stat

TINDEX

0 0,5 1 1,5 2 2,5 3

jun-83 okt-84 feb-86 jun-87 okt-88 feb-90 jun-91 okt-92 feb-94 jun-95 okt-96 feb-98 jun-99 okt-00 feb-02 jun-03 okt-04 feb-06 jun-07 okt-08 feb-10 jun-11

Alpha S:E T-stat

APPENDIX 3 – Robustness Checks

The table presents the outcome of the time-series regressions of each of the sinful indices on the market portfolio and the value, size and momentum factors, over the period 1973 to 2012. The dependent variables are calculated as the total return of the indices over the risk-free rate. MKT denotes the return on the market portfolio in excess of the risk-free rate. SMB reflects the indices correlation with the small minus big portfolio. HML represents the correlation with the return difference of a portfolio of value stocks less growth stocks. MOM indicates the correlation a portfolio of past winners. Standard errors are shown in parenthesis under each coefficient. F-statistics, T-statistics and P-value of alpha are presented for each regression, as well as the R-squared and number of observation. The alpha is a monthly average during the observation period, in percent. Note that the stars ***, ** and * denote significance at the 1%, 5% and 10% levels.

SINDEX-TINDEX

Performance of Equally Weighted Indices

INDEX Alpha (%) MKT SMB HML MOM No. of obs. Adjusted R2 F-Statistic T-statistic of α P-Value of α Annual alpha 0,363** 0,584***

INDEX Alpha (%) MKT SMB HML MOM No. of obs. Adjusted R2 F-Statistic T-statistic of α P-Value of α Annual alpha 1,020*** 0,735***

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